Auenchatbot KarlA
Doms, N.; Schlachter, T.; Hahn-Woernle, L.
2025. Umweltinformationssysteme - Digitalisierung für eine nachhaltige Planetare Zukunft – Tagungsband des 31. Workshops “Umweltinformationssysteme (UIS 2024)" der Fachgruppe „Umweltinformationssysteme" der Gesellschaft für Informatik (GI). Hrsg.: F. Fuchs-Kittowski, 249–262, Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-46394-6_15

Automated machine learning for time series forecasting in smart grid applications. PhD dissertation
Meisenbacher, S.
2025, May 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000181215

Addressing Low-Quality Domain Knowledge in Knowledge-Guided Machine Learning. PhD dissertation
Bielski, P.
2025, March 25. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000180298

Cross-Machine Multi-Phase Advanced Persistent Threat Detection and Investigation via Provenance Analytics. PhD dissertation
Liu, Q.
2025, February 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000179480

Methodenentwicklung zur automatisierten Hochdurchsatz-Biodiversitätsforschung unter Invertebraten. PhD dissertation
Wührl, L.
2025, February 10. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000178764

Messtechnische Methoden zur Identifikation von Modellparametern in Niederspannungsnetzen. PhD dissertation
Jumar, R.
2025, January 8. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000177786

Occupant-Oriented Demand Response with Model Predictive Heating Control in a Multi-Zone Residential Building. PhD dissertation
Frahm, M.
2025. KIT Scientific Publishing. doi:10.5445/KSP/1000174319

Federated reinforcement learning for sustainable and cost-efficient energy management
Sievers, J.; Henrich, P.; Beichter, M.; Mikut, R.; Hagenmeyer, V.; Blank, T.; Simon, F.
2025. Energy and AI, Art.-Nr.: 100521. doi:10.1016/j.egyai.2025.100521

AutoPQ: Automating quantile estimation from point forecasts in the context of sustainability
Meisenbacher, S.; Phipps, K.; Taubert, O.; Weiel, M.; Götz, M.; Mikut, R.; Hagenmeyer, V.
2025. Applied Energy, 392, 125931. doi:10.1016/j.apenergy.2025.125931

A New Numerical Approach to Transfer Functions of LTI-PDEs
Schaßberger, J. M.; Hagenmeyer, V.; Gröll, L.
2025. IFAC-PapersOnLine, 59 (1), 97–102. doi:10.1016/j.ifacol.2025.03.018

Maschinelles Lernen in der Niederspannung: Wie Modelle auf Basis von Messwerten die Prozesse im Verteilnetz unterstützen
Treutlein, M.; Schmidt, M.; Zahorka, S.; Kraus, F.; Mikut, R.; Hagenmeyer, V.
2025. Energiewirtschaftliche Tagesfragen, 75 (4), 69–72

TIMtrace: Coverage path planning for Thermal Interface Materials
Baeuerle, S.; Steimer, A.; Mikut, R.
2025. Thermal Science and Engineering Progress, 61, Article no: 103530. doi:10.1016/j.tsep.2025.103530

Spatial analysis of tails of air pollution PDFs in Europe
He, H.; Schäfer, B.; Beck, C.
2025. Environmental Data Science, 3, e30. doi:10.1017/eds.2024.43

ASAP: Automated Style-Aware Similarity Measurement for Selection of Annotated Pre-training Datasets in 2D Biomedical Imaging
Molina-Moreno, M.; Schilling, M. P.; Reischl, M.; Mikut, R.
2025. IEEE Access, 13, 54794–54807. doi:10.1109/ACCESS.2025.3555020

Analyzing deterministic and stochastic influences on the power grid frequency dynamics with explainable artificial intelligence
Drewnick, T.; Wen, X.; Oberhofer, U.; Rydin Gorjão, L.; Beck, C.; Hagenmeyer, V.; Schäfer, B.
2025. Chaos: An Interdisciplinary Journal of Nonlinear Science, 35 (3). doi:10.1063/5.0239371

openBIM – IFC in der Stahlbaufertigung
Jung, V.; Häfele, K.-H.; Geiger, A.; Huhn, M.; Stiegeler, S.; Brell-Çokcan, S.
2025. Stahlbau, 94 (3), 117–123. doi:10.1002/stab.202500008

EntoSieve: Automated Size‐Sorting of Insect Bulk Samples to Aid Accurate Megabarcoding and Metabarcoding
Ascenzi, A.; Wührl, L.; Feng, V.; Klug, N.; Pylatiuk, C.; Cerretti, P.; Meier, R.
2025. Molecular Ecology Resources. doi:10.1111/1755-0998.14097

Machine learning-driven multi-agent-based AC optimal power flow with effective dataset creation for data privacy and interoperability
Dindar, B.; Saner, C. B.; Çakmak, H. K.; Hagenmeyer, V.
2025. Sustainable Energy, Grids and Networks, 42, 101672. doi:10.1016/j.segan.2025.101672

Event-based vision in laser welding: An approach for process monitoring
Dold, P. M.; Nadkarni, P.; Boley, M.; Schorb, V.; Wu, L.; Steinberg, F.; Burggräf, P.; Mikut, R.
2025. Journal of Laser Applications, 37, Article no: 012040. doi:10.2351/7.0001526

Combined Frequency Control from Trains Thermal Inertia: An Assessment of Frequency Controllers Interaction
Araúz, J.; Wiegel, F.; Waczowicz, S.; Hagenmeyer, V.; Martinez, S.
2025. IEEE Open Journal of Power Electronics, 6, 464–473. doi:10.1109/OJPEL.2025.3547097

PIDE: Photovoltaic integration dynamics and efficiency for autonomous control on power distribution grids
Demirel, G.; Fernengel, N.; Grafenhorst, S.; Förderer, K.; Hagenmeyer, V.
2025. Energy Informatics, 8 (1), 32. doi:10.1186/s42162-025-00489-6

Assessing political bias in large language models
Rettenberger, L.; Reischl, M.; Schutera, M.
2025. Journal of Computational Social Science, 8 (2), Article no: 42. doi:10.1007/s42001-025-00376-w

Linear Active Disturbance Rejection Control-Based Voltage Controller for Buck and Boost DC/DC Converters in DC Distribution Grids
Korompili, A.; Ekin, O.; Stevic, M.; Hagenmeyer, V.; Monti, A.
2025. IEEE Access, 13, 19085 – 19109. doi:10.1109/ACCESS.2025.3533080

AI-based approach to dissect the variability of mouse stem cell-derived embryo models
Caldarelli, P.; Deininger, L.; Zhao, S.; Panda, P.; Yang, C.; Mikut, R.; Zernicka-Goetz, M.
2025. Nature Communications, 16 (1), Art.-Nr.: 1772. doi:10.1038/s41467-025-56908-5

Generating peak‐aware pseudo‐measurements for low‐voltage feeders using metadata of distribution system operators
Treutlein, M.; Schmidt, M.; Hahn, R.; Hertel, M.; Heidrich, B.; Mikut, R.; Hagenmeyer, V.
2025. IET Smart Grid, 8 (1). doi:10.1049/stg2.12210

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems
Dai, X.; Zhai, J.; Jiang, Y.; Guo, Y.; Jones, C. N.; Hagenmeyer, V.
2025. IEEE Transactions on Network Science and Engineering, 12 (2), 1210–1223. doi:10.1109/TNSE.2025.3526206

A novel metric for 6D pose estimation – Addressing errors and false detections for more reliable evaluation
Niedermaier, T.; Berens, F.; Reischl, M.; Elser, S.
2025. at - Automatisierungstechnik, 73 (2), 125–135. doi:10.1515/auto-2024-0121

Hybridizing 3D printing and electroplating for the controlled forming of metal structures within fused deposition modelled contours
Müller, T.; Scholz, S.; Ehrhardt, M.; Ruíz Trujillo, S.; Cogollo de Cádiz, M.; Díaz Lantada, A.; Guttmann, M.
2025. The International Journal of Advanced Manufacturing Technology, 136 (10), 4369–4381. doi:10.1007/s00170-025-15089-7

Improving 3D deep learning segmentation with biophysically motivated cell synthesis
Bruch, R.; Vitacolonna, M.; Nürnberg, E.; Sauer, S.; Rudolf, R.; Reischl, M.
2025. Communications Biology, 8 (1), Art.-Nr.: 43. doi:10.1038/s42003-025-07469-2

Droplet Microarrays for Miniaturized and High‐Throughput Experiments: Progress and Prospectives
Kartsev, D. D.; Urrutia Gómez, J. E.; Anna, P. A.; Levkin, P. A.
2025. Advanced Materials Interfaces, 12 (4), Art.-Nr.: 2400905. doi:10.1002/admi.202400905

A high-speed camera-based measurement system for monitoring and controlling the induced jet break-up fabrication of advanced ceramic breeder pebbles
Zhang, M.; Leys, O.; Vogelbacher, M.; Knitter, R.; Matthes, J.
2025. The International Journal of Advanced Manufacturing Technology, 136 (3-4), 1253–1265. doi:10.1007/s00170-024-14887-9

Highly Parallel and High‐Throughput Nanoliter‐Scale Liquid, Cell, and Spheroid Manipulation on Droplet Microarray
Urrutia Gómez, J. E.; Zhou, M.; Mandsberg, N. K.; Serna, J. A.; Padberg, J. von; Liu, S.; Reischl, M.; Levkin, P. A.; Popova, A. A.
2025. Advanced Functional Materials, 35 (1), Art.-Nr.: 2410355. doi:10.1002/adfm.202410355

Solution Processable Barrier Films Using A Filled Polymer to Encapsulate Flexible Printed Electronics
Chen, Z.; Gengenbach, U.; Gananian, S.; Moser, D.; Reichert, K.-M.; Huang, L.; Koker, L.
2025. IEEE Journal on Flexible Electronics, 4 (1), 4–11. doi:10.1109/JFLEX.2024.3512473

Enhancing Situational Awareness in Smart Grids through Event Correlation for ATT&CK Mapping
Canbolat Kaya, S.; Elbez, G.; Hagenmeyer, V.
2025. ACM International Conference on Future and Sustainable Energy Systems (ACM e-Energy 2025), Association for Computing Machinery (ACM). doi:10.1145/3679240.3734689

Construction and Control of Validated Highly Configurable Multi-Physics Building Models for the Sustainability Analysis of Multi-Energy Systems in a Co-Simulation Setup
Cheng, H.; Stock, J.; Xhonneux, A.; Çakmak, H. K.; Hagenmeyer, V.
2025. SoutheastCon 2025, 19–28, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SoutheastCon56624.2025.10971478

A Low-Code Approach for Creating Dynamic Map-Based Web Applications Using W3C Web Components
Schmidt, A.; Münch, T.
2025. Proceedings of the 17th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2025). Ed.: C. Kotropoulos, 72–74, International Academy Research and Industry Association (IARIA)

New Co-Simulation Variants for Emissions and Cost Reduction of Sustainable District Heating Planning
Cheng, H.; Buccoliero, V.; Kocher, A.; Hagenmeyer, V.; Çakmak, H. K.
2025. IEEE PES 16th Asia-Pacific Power and Energy Engineering Conference (APPEEC 2024), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/APPEEC61255.2024.10922291

Comparative Analysis of Force Myography and Electromyography Signals in Isokinetic Ankle and Knee Joint Motion
Marquardt, C.; Kurz, G.; Dežman, M.; Stein, T.; Asfour, T.
2025. IEEE/RAS-EMBS International Conference on Rehabilitation Robotics, Chicago, 12th - 16th May 2025

Synthesizing Distribution Grid Congestion Data Using Multivariate Conditional Time Series Generative Adversarial Networks
Demirel, G.; Hauf, J.; Butt, H.; Förderer, K.; Schäfer, B.; Hagenmeyer, V.
2025. 2024 IEEE Sustainable Power and Energy Conference (iSPEC), 385–390, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/iSPEC59716.2024.10892479

A fuzzy logic approach for economic energy-efficient heat pump operation in thermal building control
Kovačević, J.; Süß, A.-C.; Çakmak, H. K.; Hagenmeyer, V.
2025. 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, 14th-17th October 2024, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE62998.2024.10863470

A Machine Learning-Based Privacy-Preserving Approach to Incorporate Distributed Generators in AC Optimal Power Flow
Dindar, B.; Saner, C. B.; Polat, D. Y.; Çakmak, H. K.; Hagenmeyer, V.
2025. 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), Dubrovnik, 14th-17th October 2024, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE62998.2024.10863010

Analytical Evaluation of Time-based Cryptography
Ramadan, M.; Gadekar, P.; Hagenmeyer, V.; Elbez, G.
2025. Title: Proceedings of the 11th International Conference on Information Systems Security and Privacy 2025. Editor: Gabriele Lenzini, Paolo Mori, Steven Furnell (Eds.)

Evaluating Large Language Models in Cybersecurity Knowledge with Cisco Certificates
Keppler, G.; Kunz, J.; Hagenmeyer, V.; Elbez, G.
2025. Secure IT Systems. Ed.: L.H. Iwaya, 219–238, Springer Nature Switzerland. doi:10.1007/978-3-031-79007-2_12

Leveraging Artificial Intelligence for Creating Material Passports from Building Stock Documents: A Workflow for Promoting Circularity in the Built Environment
Lauble, S.; Geiger, A.; Zielke, P.
2025. CTU Prag

Scheduling Electric Currents in Converter-Dominated Power Grids with Time-Slotted Energy Packets
Schneider, K.; Schulz, D.; Helmig, D.; Wiegel, F.; Hagenmeyer, V.; Hiller, M.; Zitterbart, M.
2025. Energy Informatics – 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I. Ed.: B. Jørgensen, 3–20, Springer Nature Switzerland. doi:10.1007/978-3-031-74738-0_1

Impact and Integration of Mini Photovoltaic Systems on Electric Power Distribution Grids
Demirel, G.; Grafenhorst, S.; Förderer, K.; Hagenmeyer, V.
2025. Energy Informatics – 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part II. Ed.: B. Jørgensen, 247–265, Springer Nature Switzerland. doi:10.1007/978-3-031-74741-0_16

Dynamic Phenotype Mapping in Evolutionary Algorithms for Energy Hub Scheduling
Poppenborg, R.; Phipps, K.; Beichter, M.; Förderer, K.; Mikut, R.; Hagenmeyer, V.
2025. Energy Informatics – 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part II. Ed.: B. Jørgensen, 205–223, Springer Nature Switzerland. doi:10.1007/978-3-031-74741-0_14

Natural and synthetic datasets for rapid deep-learning-based optical measurement of printed linear structures
Polomoshnov, M.; Ashif, N. R. M.; Reischl, M.
2025, April 23. doi:10.35097/kf4tg7xk649w984q

Dataset: AVIATOR: A MITRE Emulation Plan-Derived Living Dataset for Advanced Persistent Threat Detection and Investigation
Liu, Q.
2025. doi:10.35097/8s5b0u5yqgfs2y0d

Experimental Data of Two Buildings Supplied by Heat Pump and District Heating under Multiple Heating Scenarios during Winter 2023-2024
Tajalli-Ardekani, E.; Dietze, S.; Moser, T.; Seddiqi, A.; Holzhaeuer, M.; Koubaa, M. A.; Spatafora, L.; Waczowicz, S.; Süß, W.; Hagenmeyer, V.
2025. doi:10.5281/zenodo.14810475

Characterization of grid-oriented control of heat pumps via SG-Ready
Beichter, S.; Süß, A.-C.; Galenzowski, J.; Dillmann, J.; Dietze, S.; Mikut, R.; Waczowicz, S.; Hagenmeyer, V.
2025, January 24. doi:10.5281/zenodo.14678762

deiluca/StembryoNet: AI-based approach to dissect the variability of mouse stem cell-derived embryo models: Code
Deininger, L.
2025. doi:10.5281/zenodo.14605177

AI-based approach to dissect the variability of mouse stem cell-derived embryo models: Data
Caldarelli, P.; Deininger, L.
2025. doi:10.5281/zenodo.14605093

4th Helmholtz Open Science Forum on the NFDI - "Helmholtz Contributions to FAIRness and Data Quality"
Genderjahn, S.; Meistring, M.; Vleugel, M.; Brune, S.; Frickenhaus, S.; Murphy, B.; Nimptsch, K.; Nunes da Rocha, U.; Selzer, M.; Süß, W.; Weber, F.
2025. (S. Genderjahn & M. Meistring, Eds.), Helmholtz Open Science Office. doi:10.48440/os.helmholtz.082

Tolerancing of the Atomiser Unit of an Aerosol-on-Demand Jet-Printhead
Ungerer, M.; Walter, T. P.; Sieber, I.
2024. Simulation and Modeling Methodologies, Technologies and Applications – 13th International Conference, SIMULTECH 2023 Rome, Italy, July 12-14, 2023 Revised Selected Papers. Ed.: G. Wagner, 61–78, Springer Nature Switzerland. doi:10.1007/978-3-031-77603-8_4

Integrating distributed energy resources in real-world sector-coupled microgrids: challenges, strategies, and experimental insights
Wiegel, F.; An, S.; Wachter, J.; Beichter, S.; Süß, A.-C.; Ekin, Ö.; Hagenmeyer, V.
2024. System Level Control and Optimisation of Microgrids. Ed.: A. Parisio, 147–173, Institution of Engineering and Technology (IET). doi:10.1049/PBPO149E_ch6

Automation Level Taxonomy for Time Series Forecasting Services: Guideline for Real-World Smart Grid Applications
Meisenbacher, S.; Galenzowski, J.; Förderer, K.; Suess, W.; Waczowicz, S.; Mikut, R.; Hagenmeyer, V.
2024. Energy Informatics – 4th Energy Informatics Academy Conference, EI.A 2024, Kuta, Bali, Indonesia, October 23–25, 2024, Proceedings, Part I. Ed.: B. Jørgensen, 277–297, Springer Nature Switzerland. doi:10.1007/978-3-031-74738-0_18

An Application of a New Nonlinearity Measure to a Rotary Dryer Model
Schaßberger, J. M.; Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2024. 34th European Symposium on Computer Aided Process Engineering / 15th International Symposium on Process Systems Engineering, 853–858, Elsevier. doi:10.1016/B978-0-443-28824-1.50143-5

Quantitative Analysis of Whole-Mount Fluorescence-Stained Tumor Spheroids in Phenotypic Drug Screens
Nuernberg, E.; Bruch, R.; Hafner, M.; Rudolf, R.; Vitacolonna, M.
2024. 3D Cell Culture. Ed.: Z. Sumbalova Koledova, 311–334, Springer US. doi:10.1007/978-1-0716-3674-9_20

Automatisierte Erzeugung von openBIM-Gebäudemodellen in der Entwurfsphase
Zhong, Y.; Hempel, S.; Geiger, A.
2024. Künstliche Intelligenz im Bauwesen. Hrsg.: S. Haghsheno, 83–99, Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-42796-2_5

Distribution Grid Monitoring Based on Widely Available Smart Plugs
Grafenhorst, S.; Förderer, K.; Hagenmeyer, V.
2024. Energy Informatics – Third Energy Informatics Academy Conference, EI.A 2023, Campinas, Brazil, December 6–8, 2023, Proceedings, Part II. Ed.: B. Jørgensen, 195–212, Springer Nature Switzerland. doi:10.1007/978-3-031-48652-4_13

Managing Anomalies in Energy Time Series for Automated Forecasting
Turowski, M.; Neumann, O.; Mannsperger, L.; Kraus, K.; Layer, K.; Mikut, R.; Hagenmeyer, V.
2024. Energy Informatics. Proceedings. Ed.: B. Jørgensen. Pt. 1, 3–29, Springer Nature Switzerland. doi:10.1007/978-3-031-48649-4_1

Automating Value-Oriented Forecast Model Selection by Meta-learning: Application on a Dispatchable Feeder
Werling, D.; Beichter, M.; Heidrich, B.; Phipps, K.; Mikut, R.; Hagenmeyer, V.
2024. Energy Informatics : Third Energy Informatics Academy Conference, EI.A 2023, Campinas, Brazil, December 6–8, 2023, Proceedings, Part I / Ed.: B. Jørgensen, 95–116, Springer Nature Switzerland. doi:10.1007/978-3-031-48649-4_6

Optimized Energy Hub Scheduling Using Evolutionary Algorithms. PhD dissertation
Poppenborg, R.
2024, December 19. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000177487

Entwicklung eines Metall-Keramik-Verbundes für thermo-mechanisch hochbelastbare Sichtfenster. PhD dissertation
Spatafora, L.
2024, November 18. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000176190

Stability in Time-Delay Systems. PhD dissertation
Scholl, T. H.
2024, November 4. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000175831

Occupant-Oriented Demand Response with Model Predictive Heating Control in a Multi-Zone Residential Building. PhD dissertation
Frahm, M.
2024, September 13. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000174124

Spectra-based Neural Networks for Uncovering Novel Substances in Material Discovery Experiments. PhD dissertation
Schützke, J.
2024, August 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000173486

Challenges in Deep Learning Based Forecasting of Time Series with Calendar-driven Periodicities. PhD dissertation
Heidrich, B.
2024, June 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000171463

Applications of Machine Learning in Materials Science. PhD dissertation
Zhao, Y.
2024, June 4. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000171281

Quantifying and Interpreting Uncertainty in Time Series Forecasting. PhD dissertation
Phipps, K.
2024, June 3. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000171223

Entwicklung und Analyse von Merkmalen für datengetriebene Ansätze zur Schadenserkennung an Brücken basierend auf Einflusslinien aus nichtinvasiven Messverfahren. PhD dissertation
Döring, A.
2024, March 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000169164

Interaction of external forcing and noise in bio-inspired oscillator systems. PhD dissertation
Kumpost, V.
2024, March 12. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000169163

Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction. PhD dissertation
Lingelbach, Y.
2024. doi:10.5445/KSP/1000169018

Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction. PhD dissertation
Lingelbach, Y.
2024, March 5. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000169012

Development of novel ozone sensors for medical therapy. PhD dissertation
Petani, L.
2024, March 4. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000168947

Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data. PhD dissertation
Li, L.
2024. doi:10.5445/KSP/1000168541

Datenzentriertes Deep Learning für die Hochdurchsatzbildverarbeitung in interdisziplinären Projekten. PhD dissertation
Schilling, M.
2024, January 15. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000167262

Zum Gedenken an Prof. Dr.-Ing. habil. Hans-Helmut Wilfert
Bretthauer, G.; Klingner, M.
2024. at - Automatisierungstechnik, 72 (10), 1002–1004. doi:10.1515/auto-2024-0140

Zum Gedenken an Prof. em. Dr.-Ing. Franz Mesch
Bretthauer, G.; Beyerer, J.; Stiller, C.
2024. at - Automatisierungstechnik, 72 (12), 1209–1211. doi:10.1515/auto-2024-0159

Flattening the Peak Demand Curve through Energy Efficient Buildings: A Holistic Approach Towards Net-Zero Carbon
Akhmentov, Y.; Fedotova, E.; Frysztacki, M.
2024. Applied energy

Focus on monitoring and control of complex supply systems
Delabays, R.; Pagnier, L.; Schäfer, B.; Tyloo, M.; Witthaut, D.
2024. Journal of Physics: Complexity, 5 (4), Article no: 040201. doi:10.1088/2632-072X/acfadd

Field Survey of Wireless M-Bus Encryption for Energy Metering Applications in Residential Buildings
Hiller Gaertringen, F. von; Galenzowski, J.; Bao, K.; Waczowicz, S.; Hagenmeyer, V.
2024. ACM SIGEnergy energy informatics review, 4 (4), 193–206. doi:10.1145/3717413.371743

Open BIM - IFC in der Stahlbaufertigung
Jung, V.; Häfele, K.-H.; Geiger, A.; Huhn, M.; Stiegeler, S.; Brell-Cokcan, S.
2024. Stahlbau

A spheroid whole mount drug testing pipeline with machine-learning based image analysis identifies cell-type specific differences in drug efficacy on a single-cell level
Vitacolonna, M.; Bruch, R.; Schneider, R.; Jabs, J.; Hafner, M.; Reischl, M.; Rudolf, R.
2024. BMC Cancer, 24 (1), Art.-Nr.: 1542. doi:10.1186/s12885-024-13329-9

An open-source software for the simulation of fixational eye movements
Allgeier, S.; Anzlinger, F.; Bohn, S.; Mikut, R.; Neumann, O.; Reichert, K.-M.; Stachs, O.; Sperlich, K.
2024. Current Directions in Biomedical Engineering, 10 (4), 25–28. doi:10.1515/cdbme-2024-2007

ML-Based XPS Quantification Supported by Synthetic Dataset Generation
Orth, A.; Höfer, H.; Nefedov, A.; Jalali, M.; Wöll, C.; Reischl, M.
2024. Current Directions in Biomedical Engineering, 10 (4), 482–485. doi:10.1515/cdbme-2024-2118

Using Large Language Models for Extracting Structured Information From Scientific Texts
Rettenberger, L.; Münker, M. F.; Schutera, M.; Niemeyer, C. M.; Rabe, K. S.; Reischl, M.
2024. Current Directions in Biomedical Engineering, 10 (4), 526–529. doi:10.1515/cdbme-2024-2129

Quantitative Convolutional Neural Network Based Multi-Phase XRD Pattern Analysis
Höfer, H. H.; Orth, A.; Schweidler, S.; Breitung, B.; Aghassi-Hagmann, J.; Reischl, M.
2024. Current Directions in Biomedical Engineering, 10 (4), 307–310. doi:10.1515/cdbme-2024-2075

Invariant Sets of a Nonlinear Oscillator with Delayed Restoring Force: Comparison System Approach
Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2024. IFAC-PapersOnLine, 58 (27), 178–183. doi:10.1016/j.ifacol.2024.10.320

Lyapunov-Krasovskii Functionals of Robust Type and Their Legendre-Tau-Based Approximation
Scholl, T. H.; Hagenmeyer, V.; Gröll, L.
2024. IFAC-PapersOnLine, 58 (27), 219–224. doi:10.1016/j.ifacol.2024.10.327

Improving Maraging Steel 350 Machinability via Wiper Insert-Enhanced Face Milling
Abbas, A. T.; Helmy, M. O.; Alqosaibi, K. F.; Parvez, S.; Hasan, A. S.; Elkaseer, A.
2024. Metals, 14 (5), Art.-Nr.: 514. doi:10.3390/met14050514

Adaptable Accelerometer Signal Processing Pipelines for Smartphone based Evenness Estimation
Münke, F. R.; Schenk, M.; Murr, S.; Reischl, M.
2024. Journal of Signal Processing Systems, 96 (10), 617–626. doi:10.1007/s11265-024-01939-2

Repetitive ultramicrotome trimming and SEM imaging for characterizing printed multilayer structures
Huang, L.; Mach, T. P.; Binder, J. R.; Thelen, R.; Curticean, R.; Wacker, I.; Schröder, R. R.; Gengenbach, U.
2024. Scientific Reports, 14 (1), Art.-Nr.: 28716. doi:10.1038/s41598-024-79717-0

Distribution grid monitoring based on feature propagation using smart plugs
Grafenhorst, S.; Förderer, K.; Hagenmeyer, V.
2024. Energy Informatics, 7 (1), Article no: 116. doi:10.1186/s42162-024-00427-y

Low-Code in Web-Applikationen: fachabteilungen stärken – IT Abteilung entlasten
Schmidt, A.; Münch, T.
2024. Forschung aktuell, 18–21

The complementary role of energy system and power grid models: An analysis of the European energy transformation from a holistic perspective
Lotze, J.; Moser, M.; Savvidis, G.; Keles, D.; Hagenmeyer, V.
2024. Energy Conversion and Management, 315, Art.-Nr. 118761. doi:10.1016/j.enconman.2024.118761

Perpetual innovative products from circular factories for sustainable production
Lanza, G.; Martin, M.; Bretthauer, G.
2024. at - Automatisierungstechnik, 72 (9), 771–773. doi:10.1515/auto-2024-0107

Biological engineering – an engineering discipline crucial to the future of our civilization
Adamy, J.; Nuber, U. A.; Koeppl, H.; Bretthauer, G.
2024. at - Automatisierungstechnik, 72 (7), 579–584. doi:10.1515/auto-2024-0061

Coordinated price-based control of modulating heat pumps for practical demand response and peak shaving in building clusters
Langner, F.; Kovačević, J.; Zwickel, P.; Dengiz, T.; Frahm, M.; Waczowicz, S.; Çakmak, H. K.; Matthes, J.; Hagenmeyer, V.
2024. Energy and Buildings, 324, 114940. doi:10.1016/j.enbuild.2024.114940

Analyzing spatio-temporal dynamics of dissolved oxygen for the River Thames using superstatistical methods and machine learning
He, H.; Boehringer, T.; Schäfer, B.; Heppell, K.; Beck, C.
2024. Scientific Reports, 14 (1), Art.-Nr.: 21288. doi:10.1038/s41598-024-72084-w

From in vitro to in silico: a pipeline for generating virtual tissue simulations from real image data
Nürnberg, E.; Vitacolonna, M.; Bruch, R.; Reischl, M.; Rudolf, R.; Sauer, S.
2024. Frontiers in Molecular Biosciences, 11. doi:10.3389/fmolb.2024.1467366

Generating synthetic energy time series: A review
Turowski, M.; Heidrich, B.; Weingärtner, L.; Springer, L.; Phipps, K.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2024. Renewable and Sustainable Energy Reviews, 206, 114842. doi:10.1016/j.rser.2024.114842

Analysing and Predicting Extreme Frequency Deviations: A Case Study in the Balearic Power Grid
Sharfeddine, Z.; Pütz, S.; Tamhane, V.; Hagenmeyer, V.; Schäfer, B.
2024. Energy Informatics Review Newsletter: EIR Newsletter

On the correlation between pre-processing workflow and dimensional accuracy of 3D printed parts in high-precision Material Jetting
Chen, K. J.; Elkaseer, A.; Scholz, S. G.; Hagenmeyer, V.
2024. Additive Manufacturing, 91, Art.-Nr.: 104335. doi:10.1016/j.addma.2024.104335

A self-supervised embedding of cell migration features for behavior discovery over cell populations
Molina-Moreno, M.; González-Díaz, I.; Mikut, R.; Díaz-de-María, F.
2024. Computer Methods and Programs in Biomedicine, 255, 108337. doi:10.1016/j.cmpb.2024.108337

The role of energy storage systems for a secure energy supply: A comprehensive review of system needs and technology solutions
De Carne, G.; Maroufi, S. M.; Beiranvand, H.; De Angelis, V.; D’Arco, S.; Gevorgian, V.; Waczowicz, S.; Mather, B.; Liserre, M.; Hagenmeyer, V.
2024. Electric Power Systems Research, 236, Art.-Nr.: 110963. doi:10.1016/j.epsr.2024.110963

Adaptive Training for Robust Object Detection in Autonomous Driving Environments
Berens, F.; Koschinski, Y.; Badami, M. K.; Geimer, M.; Elser, S.; Reischl, M.
2024. IEEE Transactions on Intelligent Vehicles, 1–15. doi:10.1109/TIV.2024.3439001

Control-oriented modeling of direct-heat co-current rotary dryers for energy demand flexibility
Schaßberger, J. M.; Gröll, L.; Hagenmeyer, V.
2024. Computers & Chemical Engineering, 189, Art.-Nr.: 108774. doi:10.1016/j.compchemeng.2024.108774

Image-based recognition of parasitoid wasps using advanced neural networks
Shirali, H.; Hübner, J.; Both, R.; Raupach, M.; Reischl, M.; Schmidt, S.; Pylatiuk, C.
2024. Invertebrate Systematics, 38, Article no: IS24011. doi:10.1071/IS24011

A multiparametric analysis including single-cell and subcellular feature assessment reveals differential behavior of spheroid cultures on distinct ultra-low attachment plate types
Vitacolonna, M.; Bruch, R.; Agaçi, A.; Nürnberg, E.; Cesetti, T.; Keller, F.; Padovani, F.; Sauer, S.; Schmoller, K. M.; Reischl, M.; Hafner, M.; Rudolf, R.
2024. Frontiers in Bioengineering and Biotechnology, 12. doi:10.3389/fbioe.2024.1422235

Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, In Silico Structure–Activity, and Immunoassay Performance
Phan-Xuan, T.; Schweidler, S.; Hirte, S.; Schüller, M.; Lin, L.; Khandelwal, A.; Wang, K.; Schützke, J.; Reischl, M.; Kübel, C.; Hahn, H.; Bello, G.; Kirchmair, J.; Aghassi-Hagmann, J.; Brezesinski, T.; Breitung, B.; Dailey, L. A.
2024. ACS Nano, 18 (29), 19024–19037. doi:10.1021/acsnano.4c03053

Automated handling of biological objects with a flexible gripper for biodiversity research; [Automatisierte Handhabung biologischer Objekten mit einem flexiblen Greifer für die Biodiversitätsforschung]
Wührl, L.; Keller, L.; Klug, N.; Shirali, H.; Meier, R.; Pylatiuk, C.
2024. at - Automatisierungstechnik, 72 (7), 672–678. doi:10.1515/auto-2023-0238

Detection of COVID-19 in Chest X-Ray Images Using a CNN Model toward Medical Applications
Mohsen, S.; Scholz, S. G.; Elkaseer, A.
2024. Wireless Personal Communications, 137 (1), 69–87. doi:10.1007/s11277-024-11309-7

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling
Dai, X.; Guo, Y.; Jiang, Y.; Jones, C. N.; Hug, G.; Hagenmeyer, V.
2024. Electric Power Systems Research, 234, Artk:Nr.: 110627. doi:10.1016/j.epsr.2024.110627

Automated Building Layout Generation: Implementation and Comparison of Streamer Early Design Configurator and SDaC Layout Designer
Zhong, Y.; Hempel, S.; Geiger, A.; Haefele, K.-H.; Hagenmeyer, V.
2024. Journal of building engineering, 95, 110163. doi:10.1016/j.jobe.2024.110163

Enhancing Temperature Responsiveness of PNIPAM Through 3D‐Printed Hierarchical Porosity
Liu, W.; Wang, Z.; Serna, J. A.; Debastiani, R.; Gomez, J. E. U.; Lu, L.; Yang, W.; Dong, Z.; Levkin, P. A.
2024. Advanced Functional Materials, Artkl.Nr.: 2403794. doi:10.1002/adfm.202403794

Gossen’s first law in the modeling for demand side management: a thorough heat pump case study with deep learning based partial time series data generation
Li, C.; Brecher, G.; Kovačević, J.; Çakmak, H. K.; Förderer, K.; Matthes, J.; Hagenmeyer, V.
2024. Energy Informatics, 7, 47. doi:10.1186/s42162-024-00353-z

Uncertainty-aware particle segmentation for electron microscopy at varied length scales
Rettenberger, L.; Szymanski, N. J.; Zeng, Y.; Schuetzke, J.; Wang, S.; Ceder, G.; Reischl, M.
2024. npj Computational Materials, 10 (1), Artkl.Nr.: 124. doi:10.1038/s41524-024-01302-w

Cyber–physical event reasoning for distributed energy resources
Müller, N.; Bao, K.; Heussen, K.
2024. Sustainable Energy, Grids and Networks, 39, Art.-Nr.: 101400. doi:10.1016/j.segan.2024.101400

Open Data-Driven Automation of Residential Distribution Grid Modeling With Minimal Data Requirements
Weber, M.; Janecke, L.; Çakmak, H. K.; Hagenmeyer, V.
2024. IEEE Transactions on Smart Grid, 15 (6), 5721–5732. doi:10.1109/TSG.2024.3406765

The DaNa projects: public communication of (nano)material safety data—from conspiracy theories to study quality
Kühnel, D.; Krug, H. F.; Steinbach, C.; Nau, K.
2024. Frontiers in Toxicology, 6. doi:10.3389/ftox.2024.1382458

A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids
Schröter, J.; Deininger, L.; Lupse, B.; Richter, P.; Syrbe, S.; Mikut, R.; Jung-Klawitter, S.
2024. Scientific Data, 11 (1), 514. doi:10.1038/s41597-024-03330-z

Generating probabilistic forecasts from arbitrary point forecasts using a conditional invertible neural network
Phipps, K.; Heidrich, B.; Turowski, M.; Wittig, M.; Mikut, R.; Hagenmeyer, V.
2024. Applied Intelligence. doi:10.1007/s10489-024-05346-9

The impact of heat pumps on day-ahead energy community load forecasting
Semmelmann, L.; Hertel, M.; Kircher, K. J.; Mikut, R.; Hagenmeyer, V.; Weinhardt, C.
2024. Applied Energy, 368, 123364. doi:10.1016/j.apenergy.2024.123364

Towards global insect biomonitoring with frugal methods
Brydegaard, M.; Pedales, R. D.; Feng, V.; Yamoa, A. saint- doria; Kouakou, B.; Månefjord, H.; Wührl, L.; Pylatiuk, C.; Amorim, D. de S.; Meier, R.
2024. Philosophical Transactions of the Royal Society B: Biological Sciences, 379 (1904). doi:10.1098/rstb.2023.0103

Using conditional Invertible Neural Networks to perform mid‐term peak load forecasting
Heidrich, B.; Hertel, M.; Neumann, O.; Hagenmeyer, V.; Mikut, R.
2024. IET Smart Grid, 7 (4), 460–472. doi:10.1049/stg2.12169

Towards holistic insect monitoring: species discovery, description, identification and traits for all insects
Meier, R.; Hartop, E.; Pylatiuk, C.; Srivathsan, A.
2024. Philosophical transactions of the Royal Society of London / Series B, 379 (1904). doi:10.1098/rstb.2023.0120

Image-based identification of optical quality and functional properties in inkjet-printed electronics using machine learning
Polomoshnov, M.; Reichert, K.-M.; Rettenberger, L.; Ungerer, M.; Hernandez-Sosa, G.; Gengenbach, U.; Reischl, M.
2024. Journal of Intelligent Manufacturing. doi:10.1007/s10845-024-02385-4

Hierarchical-stochastic model predictive control for a grid-interactive multi-zone residential building with distributed energy resources
Langner, F.; Frahm, M.; Wang, W.; Matthes, J.; Hagenmeyer, V.
2024. Journal of Building Engineering, 89, 109401. doi:10.1016/j.jobe.2024.109401

Nonlinear analysis of the synchronous reference frame phase-locked loop under unbalanced grid voltage
Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2024. Nonlinear Dynamics, 112, 9225–9243. doi:10.1007/s11071-024-09532-9

Evaluating Toxicity of Chemicals using a Zebrafish Vibration Startle Response Screening System
Hayot, G.; Marcato, D.; Cramer von Clausbruch, C. A.; Pace, G.; Strähle, U.; Colbourne, J. K.; Pylatiuk, C.; Peravali, R.; Weiss, C.; Scholz, S.; Dickmeis, T.
2024. Journal of visualized experiments : JoVE, 203, Art.-Nr.: e66153. doi:10.3791/66153

Context-aware composition of agent policies by Markov decision process entity embeddings and agent ensembles
Merkle, N.; Mikut, R.
2024. Semantic Web, 15 (4), 1443–1471. doi:10.3233/SW-233531

Effect of Milling Strategy on the Surface Quality of AISI P20 Mold Steel
Abbas, A. T.; Abdelnasser, E.; Naeim, N.; Alqosaibi, K. F.; Al-Bahkali, E. A.; Elkaseer, A.
2024. Metals, 14 (1), Art.-Nr.: 48. doi:10.3390/met14010048

Ensuring Data Privacy in AC Optimal Power Flow with a Distributed Co-Simulation Framework
Dai, X.; Kocher, A.; Kovačević, J.; Dindar, B.; Jiang, Y.; Jones, C. N.; Çakmak, H.; Hagenmeyer, V.
2024. Electric power systems research, 235, Art.-Nr.: 110710. doi:10.1016/j.epsr.2024.110710

A Novel Approach to Light Detection and Ranging Sensor Placement for Autonomous Driving Vehicles Using Deep Deterministic Policy Gradient Algorithm
Berens, F.; Ambs, J.; Elser, S.; Reischl, M.
2024. SAE international journal of connected and automated vehicles, 7 (3), Art.Nr.12–07. doi:10.4271/12-07-03-0019

Rapid Flow Behavior Modeling of Thermal Interface Materials Using Deep Neural Networks
Baeuerle, S.; Gebhardt, M.; Barth, J.; Mikut, R.; Steimert, A.
2024. IEEE Access, 12, 17782–17792. doi:10.1109/ACCESS.2024.3359169

ObiWan-Microbi: OMERO-based integrated workflow for annotating microbes in the cloud
Seiffarth, J.; Scherr, T.; Wollenhaupt, B.; Neumann, O.; Scharr, H.; Kohlheyer, D.; Mikut, R.; Nöh, K.
2024. SoftwareX, 26, Article no: 101638. doi:10.1016/j.softx.2024.101638

Entomoscope: An Open-Source Photomicroscope for Biodiversity Discovery
Wührl, L.; Rettenberger, L.; Meier, R.; Hartop, E.; Graf, J.; Pylatiuk, C.
2024. IEEE Access, 12, 11785–11794. doi:10.1109/ACCESS.2024.3355272

Surface-Patterned DNA Origami Rulers Reveal Nanoscale Distance Dependency of the Epidermal Growth Factor Receptor Activation
Mayer, I.; Karimian, T.; Gordiyenko, K.; Angelin, A.; Kumar, R.; Hirtz, M.; Mikut, R.; Reischl, M.; Stegmaier, J.; Zhou, L.; Ma, R.; Nienhaus, G. U.; Rabe, K. S.; Lanzerstorfer, P.; Domínguez, C. M.; Niemeyer, C. M.
2024. Nano Letters, 24 (5), 1611–1619. doi:10.1021/acs.nanolett.3c04272

A reproducible extrusion printing process with highly viscous nanoparticle inks
Ungerer, M.; Debatin, C.; Martel, J.; Maurer, V.; Reichert, K.-M.; Hofmann, A.; Gengenbach, U.
2024. Engineering Research Express, 6, Article no: 015042. doi:10.1088/2631-8695/ad1cb0

A Review of Adaptable Conventional Image Processing Pipelines and Deep Learning on limited Datasets
Münke, F. R.; Schützke, J.; Berens, F.; Reischl, M.
2024. Machine vision and applications, 35, Article no: 25. doi:10.1007/s00138-023-01501-3

Model predictive control for demand flexibility of a residential building with multiple distributed energy resources
Strauch, P.; Wang, W.; Langner, F.
2024. Energy and Buildings, 305, Article no: 113884. doi:10.1016/j.enbuild.2023.113884

Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI
Titz, M.; Pütz, S.; Witthaut, D.
2024. Applied Energy, 356, 122351. doi:10.1016/j.apenergy.2023.122351

What ODE-Approximation Schemes of Time-Delay Systems Reveal about Lyapunov-Krasovskii Functionals
Scholl, T. H.; Hagenmeyer, V.; Gröll, L.
2024. IEEE Transactions on Automatic Control, 69 (7), 4614–4629. doi:10.1109/TAC.2023.3347497

Accelerating Materials Discovery: Automated Identification of Prospects from X‐Ray Diffraction Data in Fast Screening Experiments
Schuetzke, J.; Schweidler, S.; Muenke, F. R.; Orth, A.; Khandelwal, A. D.; Breitung, B.; Aghassi-Hagmann, J.; Reischl, M.
2024. Advanced Intelligent Systems, 6 (3), Art.-Nr.: 2300501. doi:10.1002/aisy.202300501

Systematic Investigation of Novel, Controlled Low‐Temperature Sintering Processes for Inkjet Printed Silver Nanoparticle Ink
Chen, Z.; Gengenbach, U.; Koker, L.; Huang, L.; Mach, T. P.; Reichert, K.-M.; Thelen, R.; Ungerer, M.
2024. Small, 20 (21), Art.-Nr.: 2306865. doi:10.1002/smll.202306865

CoNIC Challenge: Pushing the frontiers of nuclear detection, segmentation, classification and counting
Graham, S.; Vu, Q. D.; Jahanifar, M.; Weigert, M.; Schmidt, U.; Zhang, W.; Zhang, J.; Yang, S.; Xiang, J.; Wang, X.; Rumberger, J. L.; Baumann, E.; Hirsch, P.; Liu, L.; Hong, C.; Aviles-Rivero, A. I.; Jain, A.; Ahn, H.; Hong, Y.; Azzuni, H.; Xu, M.; Yaqub, M.; Blache, M.-C.; Piégu, B.; Vernay, B.; Scherr, T.; Böhland, M.; Löffler, K.; Li, J.; Ying, W.; Wang, C.; Snead, D.; Raza, S. E. A.; Minhas, F.; Rajpoot, N. M.
2024. Medical Image Analysis, 92, Article no: 103047. doi:10.1016/j.media.2023.103047

Digital twin of a droplet microarray platform: Evaporation behavior for multiple droplets on patterned chips for cell culture
Wu, Y.; Urrutia Gómez, J. E.; Zhang, H.; Wang, F.; Levkin, P. A.; Popova, A. A.; Nestler, B.
2024. Droplet, 3 (1), Art.-Nr. e94. doi:10.1002/dro2.94

On the reproducibility of extrusion-based bioprinting: round robin study on standardization in the field
Grijalva Garces, D.; Strauß, S.; Gretzinger, S.; Schmieg, B.; Jüngst, T.; Groll, J.; Meinel, L.; Schmidt, I.; Hartmann, H.; Schenke-Layland, K.; Brandt, N.; Selzer, M.; Zimmermann, S.; Koltay, P.; Southan, A.; Tovar, G. E. M.; Schmidt, S.; Weber, A.; Ahlfeld, T.; Gelinsky, M.; Scheibel, T.; Detsch, R.; Boccaccini, A. R.; Naolou, T.; Lee-Thedieck, C.; Willems, C.; Groth, T.; Allgeier, S.; Köhler, B.; Friedrich, T.; Briesen, H.; Buchholz, J.; Paulus, D.; von Gladiss, A.; Hubbuch, J.
2024. Biofabrication, 16 (1), Art.-Nr.: 015002. doi:10.1088/1758-5090/acfe3b

TRIM11 expression in non-small cell lung cancer is associated with poor prognosis
Kuempers, C.; Jagomast, T.; Paulsen, F. O.; Heidel, C.; Bohnet, S.; Schierholz, S.; Reischl, M.; Dreyer, E.; Olchers, T.; Reck, M.; Kirfel, J.; Perner, S.
2024. Histology and histopathology, 39, 437–446. doi:10.14670/HH-18-647

Deconstructing 3D Structured Materials by Modern Ultramicrotomy for Multimodal Imaging and Volume Analysis across Length Scales
Wacker, I.; Curticean, R.; Ryklin, D.; Weidinger, B.; Mayer, F.; Huang, L.-Y.; Hoffmann, J.; Islam, M.; von Coelln, N.; Schmitt, T.; Huck, C.; Tegeder, P.; Feist, F.; Kammerer, J. A.; Barner-Kowollik, C.; Wegener, M.; Blasco, E.; Gengenbach, U.; Schröder, R. R.
2024. Advanced Functional Materials, 34 (20), Art.-Nr.: 2302025. doi:10.1002/adfm.202302025

Exploring the Antibacterial Effects of Ozonated Oils in Medicine: A Study on Escherichia coli Inhibition
Petani, L.; Jung, A.-M.; Frietsch Musulin, R.-R.; Sturm, G.; Kaster, A.-K.; Pylatiuk, C.
2024. Ozone: Science & Engineering, 46 (2), 174–181. doi:10.1080/01919512.2023.2233746

Early Attack Detection for Securing GOOSE Network Traffic
Elbez, G.; Nahrstedt, K.; Hagenmeyer, V.
2024. IEEE Transactions on Smart Grid, 15 (1), 899–910. doi:10.1109/TSG.2023.3272749

Lowering barriers to a large-scale implementation of grid booster projects by introducing a hybrid concept
Lotze, J.; Dorn, M.; Hagenmeyer, V.
2024. 2024 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), 14th - 17th October 2024, Dubrovnik, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE62998.2024.10863660

Web Application Penetration Testing with Artificial Intelligence: A Systematic Review
Sánchez, G.; Olayinka, O.; Pasikhani, A.
2024. 2024 22nd International Symposium on Network Computing and Applications (NCA), 24-26 October 2024 Bertinoro, Italy, 236–245, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/NCA61908.2024.00043

Grid Aware Portfolio Optimization of a Multi-Energy DER
Grafenhorst, S.; Demirel, G.; Förderer, K.; Hagenmeyer, V.
2024. 2024 IEEE Sustainable Power and Energy Conference (iSPEC), Kuching, Sarawak, 24th-27th November 2024, 245–250, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/iSPEC59716.2024.10892444

Feedforward control of flat hybrid automata: a behavioral systems theory approach
Zahn, F.; Kleinert, T.; Hagenmeyer, V.
2024. 2024 IEEE 63rd Conference on Decision and Control (CDC), Milan, Italy, 16-19 December 2024, 6238 – 6244, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC56724.2024.10885982

Real-time Pricing Mechanism for V2G Using Distributed Bilevel Optimization
You, J.; Dai, X.; Jiang, Y.; Yin, H.; Shi, Y.; Jones, C. N.
2024. 2024 IEEE 63rd Conference on Decision and Control (CDC), Milan, Italy, 16-19 December 2024, 4629–4634, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC56724.2024.10886533

User Study on the Trustworthiness, Usability and Explainability of Intent-based and Large Language Model-based Career Planning Conversational Agents
Zylowski, T.; Sautchuk-Patricio, N.; Hettmann, W.; Anderer, K.; Fischer, K.; Wölfel, M.; Henning, P.
2024. ICETC ’24: Proceedings of the 2024 16th International Conference on Education Technology and Computers, Porto, 18th - 21st September 2024, 46 – 53, Association for Computing Machinery (ACM). doi:10.1145/3702163.3702409

Explainable Reinforcement Learning for Optimizing Electricity Costs in Building Energy Management
Butt, H. S.; Huang, Q.; Schäfer, B.
2024. 2024 3rd International Conference on Energy Transition in the Mediterranean Area (SyNERGY MED), Limassol, Cyprus, 21-23 October 2024, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SyNERGYMED62435.2024.10799400

A Spatial Decomposition Method for Solving the Security-Constrained Unit Commitment Problem
Madhusoodhanan, A. K.; Giuntoli, M.; Schmitt, S.; Harjunkoski, I.; Poland, J.; Leibfried, T.
2024. 2024 IEEE International Humanitarian Technologies Conference (IHTC), 7 S., IEEEXplore. doi:10.1109/IHTC61819.2024.10855143

Intrinsic Explainable Artificial Intelligence Using Trainable Spatial Weights on Numerical Weather Predictions
Neumann, O.; Beichter, M.; Heidrich, B.; Friederich, N.; Hagenmeyer, V.; Mikut, R.
2024. ACM

inLiSAMP, a Modularly ’Designed Fluid Downhole Sampler for Deep Geothermal Applications - Proof of Concept
Berentelg, G.; Dietze, S.; Hagenmeyer, V.
2024. Using the Earth to Save the Earth, 268–293, Geothermal Resources Council (GRC)

Improving Anomaly Detection with Adaptive Dynamic Threshold: A Review and Enhanced Method
Attar, A. A.; Fabarisov, T.; Bao, K.; Hagenmeyer, V.
2024. 2024 8th International Conference on System Reliability and Safety (ICSRS), 5 S

Aviator: A MITRE Emulation Plan-Derived Living Dataset for Advanced Persistent Threat Detection and Investigation
Liu, Q.; Bao, K.; Hagenmeyer, V.
2024. 2024 IEEE International Conference on Big Data (BigData), 5610–5619, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigData62323.2024.10826006

Distributed Control Strategy for Grid Supportive Loads in DC Microgrids
Ekin, Ö.; Balakrishnan, A.; Spatafora, L.; Hagenmeyer, V.
2024. 2024 9th IEEE Workshop on the Electronic Grid (eGRID), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGRID62045.2024.10842713

Can SINDy identify power grid frequency dynamics?
Wen, X.; Oberhofer, U.; Rydin Gorjao, L.; Yalcin, G. C.; Hagenmeyer, V.; Schäfer, B.
2024. Workshop: Tackling Climate Change with Machine Learning (ICLR 2024)

The Gap between Experiment and Simulation: Grid Forming Inverter Control during Islanding Transition
Baumgarten, K.; Wachter, J.; Wiegel, F.; Jumar, R.; Hagenmeyer, V.
2024. 9th IEEE Workshop on the Electronic Grid (eGRID), Santa Fe, New Mexico, 19th-21st November 2925, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGRID62045.2024.10842947

Automating Substation Modeling Using Labeled Images
Madhusoodhanan, A. K.; Hoffmann, J.; Schmidt, P. E.; Schott, M.; Kühnapfel, U.; Hagenmeyer, V.
2024. 13th International Conference on Renewable Energy Research and Applications (ICRERA), 9th - 13th November 2024, Nagasaki, Japan, 1050–1054, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICRERA62673.2024.10815180

Industrial Application of the Shapley value-based Redispatch Cost Allocation to Large-Scale Power Grids requires AC Optimal Power Flow
Bauer, R.; Dai, X.; Hagenmeyer, V.
2024. 2024 IEEE Power & Energy Society General Meeting (PESGM), Seattle, 21st-25th July 2024, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PESGM51994.2024.10688852

Performing Entity Relationship Model Extraction from Data and Schema Information as a Basis for Data Integration
Schmurr, P.; Schmidt, A.; Stucky, K.-U.; Suess, W.; Hagenmeyer, V.
2024. Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management. Ed.: L. Gruenwald. Vol. 3, 316–322, SciTePress. doi:10.5220/0013012600003838

EAP4EMSIG - Experiment Automation Pipeline for Event-Driven Microscopy to Smart Microfluidic Single-Cells Analysis
Friederich, N.; Yamachui Sitcheu, A. J.; Nassal, A.; Pesch, M.; Yildiz, E.; Beichter, M.; Scholtes, L.; Akbaba, B.; Lautenschlager, T.; Neumann, O.; Kohlheyer, D.; Scharr, H.; Seiffarth, J.; Nöh, K.; Mikut, R.
2024. Proceedings : 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024. Ed.: H. Schulte, 169–192, KIT Scientific Publishing

AutoWP: Automated wind power forecasts with limited computing resources using an ensemble of diverse wind power curves
Meisenbacher, S.; Selzer, S. A.; Dado, M.; Beichter, M.; Martin, T. J.; Zdrallek, M.; Bretschneider, P.; Hagenmeyer, V.; Mikut, R.
2024. Proceedings : 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024. Ed.: H. Schulte, 1–19, KIT Scientific Publishing

Machine Learning-Based Feature Selection for Intrusion Detection Systems in IEC 61850-Based Digital Substations
Eynawi, A.; Mumrez, A.; Elbez, G.; Hagenmeyer, V.
2024. 2024 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 7 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm60555.2024.10738031

Enable Business Users to Embed Dynamic Database Content in Existing Web-Based Systems Using Web Components and Generic Web Services
Schmidt, A.; Münch, T.
2024. Proceedings of the 20th International Conference on Web Information Systems and Technologies, 296–306, SciTePress. doi:10.5220/0013000000003825

FAIRlead: A Conceptual Framework for a Model Driven Software Development Approach in the Field of FAIR Data Management
Schmidt, A.; Koubaa, M.; Liu, N.; Schmurr, P.; Stucky, K. U.; Süss, W.
2024. Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 323–330, SciTePress. doi:10.5220/0013013700003838

Quantifying Domain-Application Knowledge Mismatch in Ontology-Guided Machine Learning
Bielski, P.; Witterauf, L.; Jendral, S.; Mikut, R.; Bach, J.
2024. Proceedings of the 16th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2024). Ed.: D. Aveiro. Vol. 2, 216–226, SciTePress. doi:10.5220/0013065900003838

Detection of Municipal Heat Plan Documents Using Semantic Recognition Methods
Doms, N.; Schlachter, T.
2024. Energy Informatics. Academy (EI.A) , Bali, 23rd-25th October 2024, 155–172, Springer

A Platform Ecosystem Providing New Data For The Energy Transition
Duchon, M.; Buchenberg, P.; Matar, J.; Shoyari, M. F.; Kessler, I.; Perzylo, A.; Kuhn, P.; Hamacher, T.; Suriyamoorthy, G.; Schlachter, T.; Süß, W.; Nguyen, X. T.; Salari, H. E.; Latko, J.; Xu, M.; Shamovich, M.; Schlütter, D.; Frisch, J.; Kraft, M.; Rustagi, K.; Ayasse, C.; Steinke, F.; Metzger, M.; Kuper, L.
2024. DACH+ Energy Informatics Conference 2024, Lugano, CH, Association for Computing Machinery (ACM)

Multiobjective Optimization of Energy Pulsation and Power Dissipation in Modular Multilevel Converters
Kappenstein, S.; Hagenmeyer, V.; Gröll, L.
2024. IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON 2024), Institute of Electrical and Electronics Engineers (IEEE)

Heuristic vs. Analytical Energy Hub Optimization: Design, Implementation, and Trade-Offs
Grafenhorst, S.; Ohm, J.; Poppenborg, R.; Förderer, K.; Hagenmeyer, V.
2024. 2024 IEEE 12th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 18-20 August 2024, 145–150, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE62220.2024.10739589

Automated Characterisation of Printed Electronics Under Adjustable Ambient Conditions
Ungerer, M.; Chen, Z.; Mach, T. P.; Reichert, K.-M.; Gengenbach, U.; Lindmüller, M.; Binder, J. R.; Reischl, M.; Koker, L.
2024. 2024 International Semiconductor Conference (CAS), Sinaia, Romania, 09-11 October 2024, 69–72, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAS62834.2024.10736741

Effiziente Cyber-Resilienz
Bao, K.; Elbez, G.
2024. Forschung für ein resilientes Energiesystem in Zeiten globaler Krisen: Jahrestagung 2023 des ForschungsVerbunds Erneuerbare Energien 10. und 11. Oktober 2023

Vibrational Control for Energy Balancing in Modular Multilevel Converters
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2024. 2024 IEEE 65th International Scientific Conference on Power and Electrical Engineering of Riga Technical University (RTUCON), 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/RTUCON62997.2024.10830807

Geometric Relationships in Constant Output Control
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2024. 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT), Valletta, Malta , 1st - 4th July 2024, 1774–1779, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CoDIT62066.2024.10708406

Energy-Based Prior Latent Space Diffusion Model for Reconstruction of Lumbar Vertebrae from Thick Slice MRI
Wang, Y.; Lee, Y. Y. R.; Dolfini, A.; Reischl, M.; Konukoglu, E.; Flouris, K.
2024. Deep Generative Models : 4th MICCAI Workshop, DGM4MICCAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings. Ed.: A. Mukhopadhyay, 22–32, Springer Nature Switzerland. doi:10.1007/978-3-031-72744-3_3

Experimental Assessment of the Effect of Print Orientation on the Geometrical Accuracy of Microfeatures in Multi-Material 3D Inkjet Printing
Chen, K. J.; Elkaseer, A.; Scholz, S. G.
2024. Proceedings of WCMNM 2024

A Novel Approach for Removing Decaying DC Offset from Fault Current Signals Using Cumulative Sum – Fast Moving Average (CumSum-FMA) Hybrid Algorithm
Abel, P.; Wiegel, F.; Kyesswa, M.; Waczowicz, S.; Hagenmeyer, V.
2024. 2024 IEEE 15th International Symposium on Power Electronics for Distributed Generation Systems (PEDG), Luxemburg, 23rd-26th June 2024, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PEDG61800.2024.10667422

Advancing Biodiversity Research with AI-Driven Automation
Shirali, H.; Wührl, L.; Klug, N.; Meier, R.; Pylatiuk, C.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, 12th – 14th June 2024, Karlsruher Institut für Technologie (KIT)

Demand Response for a Novel Decentralized Power-To-Methanol Process
Kollmer, M.; Vogelbacher, M.; Terzi, M.; Singh, M.; Vidal-Vazquez, F.; Matthes, J.
2024. Proceedings IEEE 7th International Conference on Smart Energy Systems and Technologies, Torino, Italy, 10-12 September 2024., 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEST61601.2024.10694417

ePowCoRe: A Novel Generic Representation of Power Grids Enabling Open-Source Model Conversion Modules
Weber, M.; Kocher, A.; Çakmak, H. K.; Hagenmeyer, V.
2024. Proceedings of 2024 Open Source Modelling and Simulation of Energy Systems (OSMSES), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES62085.2024.10668981

Grid supporting nonlinear control for AC-coupled DC Microgrids
Ekin, Ö.; Perez, F.; Wiegel, F.; Hagenmeyer, V.; Damm, G.
2024. 2024 IEEE Sixth International Conference on DC Microgrids (ICDCM), Columbia, SC, USA, 05-08 August 2024, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICDCM60322.2024.10664838

Why Reinforcement Learning in Energy Systems Needs Explanations
Butt, H. S.; Schafer, B.
2024. Proceedings of the 2024 Workshop on Explainability Engineering, 26–30, Association for Computing Machinery (ACM). doi:10.1145/3648505.3648510

Identifying Complex Dynamics of Power Grid Frequency
Wen, X.; Oberhofer, U.; Gorjão, L. R.; Yalcin, G. C.; Hagenmeyer, V.; Schäfer, B.
2024. The 15th ACM International Conference on Future and Sustainable Energy Systems, 408–414, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661944

Modular Platform for Automated Characterisation of Printed Structures, Devices and Circuits
Koker, L.; Reichert, K.-M.; Gengenbach, U.; Reischl, M.; Ungerer, M.
2024. 2024 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), 2-5 June 2024. Ed.: IEEE, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DTIP62575.2024.10613049

Method for Automated Parametric Studies and Evaluation Using the Example of an Aerosol-on-Demand Jet-Printhead
Pfannenstiel, H.; Ungerer, M.; Sieber, I.
2024. SIMULTECH 2024: Proceedings of the 14th International Conference on Simulation and Modeling Methodologies, Technologies and Applications. Ed.: F. De Rango, 69–79, SciTePress. doi:10.5220/0012758100003758

Design-and Simulation of a Body-Worn Optical Xylene Measuring Device for Use in Pathology
Sieber, I.; Deleut, A.; Petani, L.; Pylatiuk, C.
2024. 2024 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DTIP62575.2024.10613356

Process Development for Digital Fabrication of Radio Frequency Transmission Lines with Off-the-Shelf Equipment
MD Ashif, N. R.; Gengenbach, U.; Sieber, I.
2024. 2024 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DTIP62575.2024.10613213

Digital Twin Architecture to Use for Optimizing an AoD-Printing Process
Pfannenstiel, H.; Ungerer, M.; Sieber, I.
2024. 2024 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DTIP62575.2024.10613180

Line Management in the Energy Packet Grid
Weßbecher, M.; Wiegel, F.; An, S. X.; Schneider, K.; Schulz, D.; Zitterbart, M.; Hiller, M.; Hagenmeyer, V.
2024. Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems (e-Energy ’24), 182–191, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661954

Forecasting Electric Vehicle Charging Behavior in Workplace Charging Infrastructure with Limited Privacy-Restricted Real Data
Stein, A.; Beichter, S.; Hage, J.; Beichter, M.; Schwarz, B.; Waczowicz, S.; Hiller, M.; Hagenmeyer, V.; Munzke, N.; Mikut, R.
2024. 2024 IEEE Transportation Electrification Conference and Expo (ITEC), 7 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ITEC60657.2024.10598951

Investigation of solution processable moisture barrier films based on a polymer and filler materials
Chen, Z.; Gengenbach, U.; Gananian, S.; Moser, D.; Reichert, K.-M.; Koker, L.
2024. IEEE International Conference on Flexible Printable Sensors and Systems (FLEPS 2024), IEEEXplore

Erste Konzepte zur automatisierten semantischen, geographischen und zeitlichen Verschlagwortung umweltbezogener Textdokumente
Doms, N.; Schlachter, T.; Hahn-Woernle, L.
2024. Umweltinformationssysteme - Digitalisierung im Zeichen des Klimawandels und der Energiewende : Tagungsband des 30. Workshops “Umweltinformationssysteme (UIS2023)“ des Arbeitskreises „Umweltinformationssysteme“ der Fachgruppe „Informatik im Umweltschutz‘‘ der Gesellschaft für Informatik (GI), Hrsg. : F. Fuchs-Kittowski, A. Abecker, F. Hosenfeld, C. Jolk. doi:10.1007/978-3-658-43735-0_17

Feasibility of Forecasting Highly Resolved Power Grid Frequency Utilizing Temporal Fusion Transformers
Pütz, S.; El Ashhab, H.; Hertel, M.; Mikut, R.; Götz, M.; Hagenmeyer, V.; Schäfer, B.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 447–453, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661963

Decision-Focused Retraining of Forecast Models for Optimization Problems in Smart Energy Systems
Beichter, M.; Werling, D.; Heidrich, B.; Phipps, K.; Neumann, O.; Friederich, N.; Mikut, R.; Hagenmeyer, V.
2024. e-Energy ’24 : Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 170–181, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661952

New feature based on influence lines for anomaly detection in bridge monitoring
Döring, A.; Vogelbacher, M.; Schneider, O.; Müller, J.; Hinz, S.; Matthes, J.
2024. Bridge Maintenance, Safety, Management, Digitalization and Sustainability, 12th Bridge Maintenance, Safety, Management, Digitalization and Sustainability (IABMAS 2024), Kopenhagen, Dänemark, 24.06.2024–28.06.2024, Artkl.Nr.: 4140, CRC Press

A Comparative Analysis of Machine Learning Algorithms for Aggregated Electric Chargepoint Load Forecasting
Li, C.; Zhang, M.; Förderer, K.; Matthes, J.; Hagenmeyer, V.
2024. 2024 9th International Conference on Sustainable and Renewable Energy Engineering (ICSREE 2024), Marseille, May 9th-11th 2024, Ed.: J. Lin, Art.-Nr.: 01004, EDP Sciences. doi:10.1051/e3sconf/202454501004

TSO-DSO Interaction: Privacy-Preserving Optimal Power Flow with Distributed Generators Using a Machine Learning-Based Approach
Dindar, B.; Saner, C. B.; Çakmak, H. K.; Hagenmeyer, V.
2024. 2023 IEEE PES 15th Asia-Pacific Power and Energy Engineering Conference (APPEEC), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/APPEEC57400.2023.10562006

Privacy Protection in Collaborative Geographically Distributed Co-Simulation of Multimodal Energy Systems
Kocher, A.; Kovačević, J.; Süß, A.-C.; Saner, C. B.; Dindar, B.; Ehsan, M. A.; Çakmak, H. K.; Hagenmeyer, V.
2024. e-Energy ’24 : Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, Singapore, 4th-7th June 2024, 639–647, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661990

Improving Reduced-Order Building Modeling: Integration of Occupant Patterns for Reducing Energy Consumption
Kovačević, J.; Li, C.; Förderer, K.; Çakmak, H. K.; Hagenmeyer, V.
2024. Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 15th ACM International Conference on Future and Sustainable Energy Systems (2024), Singapur, Singapur, 04.06.2024–07.06.2024, 569–579, Association for Computing Machinery (ACM). doi:10.1145/3632775.3662163

Interoperability Assessment of IEC 61850 Devices in a Multivendor Digital Substation
Keppler, G.; Bonetti, A.; Canbolat, S.; Mumrez, A.; Hagenmeyer, V.; Elbez, G.
2024. 6th Global Power, Energy and Communication Conference (GPECOM2024), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/GPECOM61896.2024.10582663

Extended Abstract: Assessing GNSS Vulnerabilities in Smart Grids
Canbolat, S.; Fruböse, C.; Elbez, G.; Hagenmeyer, V.
2024. 21st Conference on Detection of Intrusions and Malware and Vulnerability Assessment (DIMVA ’24), Springer. doi:10.1007/978-3-031-64171-8_28

Attacking Learning-based Models in Smart Grids: Current Challenges and New Frontiers
Sanchez, G.; Elbez, G.; Hagenmeyer, V.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 589–595, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661984

A method for the compensation of thermal reflections in radiation based temperature measurements in combustion chambers
Matthes, J.; Waibel, P.; Gröll, L.; Vogelbacher, M.
2024. 14th European Conference on Industrial Furnaces and Boilers (INFUB 2024), Salgados, Portugal, 2.–5. April 2024

Technologiespektrum und Strategien für resilientere Energiesysteme
Scheller, F.; Lenz, V.; Müller-Langer, F.; Henke, M.; Vehse, M.; Gerhardt, N.; Schossig, P.; Ungerland, J.; Groß, T.; Matthes, J.; Stelzer, V.; Vogelbacher, M.; Kollmer, M.; Riepl, M.
2024. FVEE-Jahrestagung am 10. und 11. Oktober 2023: "Forschung für ein resilientes Energiesystem in Zeiten globaler Krisen", ForschungsVerbund Erneuerbare Energien (FVEE)

Enabling Interoperability in Steel Construction – New Concepts for Using IFC for Steel Fabrication
Jung, V.; Häfele, K.-H.; Geiger, A.; Huhn, M.; Stiegeler, S.; Brell-Cokcan, S.
2024. NSCC Sweden, NORDIC STEEL Construction Conference 2024 (2024) Luleå, Schweden, 26.06.2024–28.06.2024

Metadata Extraction from a Huge Time Series Database
Schmidt, A.; Koubaa, M. A.; Liu, N.; Stucky, K.-U.; Süß, W.
2024. Proceedings of the first NFDI4Energy Conference, Zenodo. doi:10.5281/zenodo.10625406

Web Components for Database Developers
Schmidt, A.; Münch, T.
2024. Proceediungs of the Sixteenth International Conference on Advances in Databases, Knowledge, and Data Applications Andreas Schmidt, Erik Buchmann (Editors), 20–22

Security Fence Inspection at Airports Using Object Detection
Friederich, N.; Specker, A.; Beyerer, J.
2024. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) Workshops, 310–319, Institute of Electrical and Electronics Engineers (IEEE)

CityGML Data Preparation for Thermal Building Simulation on District Level
Geiger, A.; Häfele, K.-H.; Hagenmeyer, V.
2024. IBPSA (International Building Performance Simulation Association)

Fault Detection in 3D-Printing with Deep Learning
Rettenberger, L.; Beyer, N.; Sieber, I.; Reischl, M.
2024. 2024 IEEE International Conference on Consumer Electronics (ICCE), 4 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCE59016.2024.10444198

Towards a Conception and the Implementation of FAIR Data Management Tools for the Energy Domain
Stucky, K.-U.; Koubaa, M. A.; Liu, N.; Schmidt, A.; Süß, W.; Hagenmeyer, V.
2024. 1. NFDI4Energy Conference, 5 S., Zenodo. doi:10.5281/zenodo.10614813

Real-Time Coordination of Integrated Transmission and Distribution Systems: Flexibility Modeling and Distributed NMPC Scheduling
Dai, X.; Guo, Y.; Jiang, Y.; Jones, C. N.; Hug, G.; Hagenmeyer, V.
2024. 23rd Power Systems Computation Conference, Paris, 4th-6th June 2024, arxiv

Verifiable Certificateless Signcryption Scheme for Smart Grids
Ramadan, M.; Elbez, G.; Hagenmeyer, V.
2024. 2023 7th International Conference on System Reliability and Safety (ICSRS), 181–189, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICSRS59833.2023.10381069

Gossen’s First Law in the Modeling for Demand Side Management: A First Heat Pump Case Study
Li, C.; Förderer, K.; Moser, T.; Spatafora, L.; Hagenmeyer, V.
2024. Energy Informatics. Hrsg.: B.N. Jørgensen. Pt. 2, 111–125, Springer Nature Switzerland. doi:10.1007/978-3-031-48652-4_8

Design, simulation, and evaluation of a low-cost photometer for dissolved ozone measurement
Petani, L.; Tils, D.; Wührl, L.; Sieber, I.; Pylatiuk, C.
2024. 2024 IEEE International Conference on Microwaves, Communications, Antennas, Biomedical Engineering & Electronic Systems (COMCAS 2024) Tel Aviv, Israel, 09.07.2024–11.07.2024. Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/COMCAS58210.2024.10666220

Proceedings - 34. Workshop Computational Intelligence: Berlin, 21.-22. November 2024
Schulte, H.; Hoffmann, F.; Mikut, R. (Eds.)
2024. KIT Scientific Publishing. doi:10.5445/KSP/1000174544

DBKDA 2024 : the Sixteenth International Conference on Advances in Databases, Knowledge, and Data Applications ; March 10th –14th, 2024, Athens, Greece
Schmidt, A.; Buchmann, E. (Eds.)
2024. Think Mind

Robust monitoring organoid growth
Deininger, L.
2024. doi:10.5281/zenodo.10568828

Field Survey of Wireless M-Bus Encryption for Energy Metering Applications in Residential Buildings
Hiller Gaertringen, F. von; Galenzowski, J.; Bao, K.; Waczowicz, S.; Hagenmeyer, V.
2024, October 1. doi:10.5281/zenodo.13234544

Measured active power of a photovoltaic plant on the roof of IAI-Building
Koubaa, M. A.
2024, December 4. doi:10.35097/gcxka04cr416n4k2

Machine learning-based feature selection for intrusion detection systems in IEC 61850-based digital substations
Eynawi, A.; Mumrez, A.; Elbez, G.; Hagenmeyer, V.
2024, September 17

Optimized Energy Hub Scheduling Using Evolutionary Algorithms - Supplementary Materials
Poppenborg, R.
2024, November 26. doi:10.35097/hubh72dd9d5mt43g

Highly Parallel and High-Throughput Nanoliter-Scale Liquid, Cell, and Spheroid Manipulation on Droplet Microarray
Gómez, J. E. U.
2024, November 5. doi:10.35097/61p3v2hfwxrppafw

ePowCoRe: A Generic Representation of Power Grids Enabling Open-Source Model Conversion Modules
Weber, M.; Kocher, A.
2024. doi:10.5281/zenodo.13827587

PyAPI-RTS: A Python library to read and manipulate RSCAD draft files
Weber, M.
2024, February 19. doi:10.5281/zenodo.10679087

CopyPasteImputation: Copy-Paste Imputation (CPI) for Energy Time Series
Weber, M.; Turowski, M.
2024, February 19. doi:10.5281/zenodo.10679066

„Kein Anlass für Katastrophenszenarien“ – Mit KI Tools tragen KIT Forschende zur Stabilität in den grünen Stromnetzen der Zukunft bei - Campus-Report am 21.05.2024
Fuchs, S.; Schäfer, B.
2024. doi:10.5445/IR/1000170882

On the Development of a Reconfigurable Platform for the Control of Multiple Collaborative Robots from a Software Engineering Perspective
Salem, M.; Elkaseer, A.; Müller, T.; Scholz, S.
2023. Proceedings of the Future Technologies Conference (FTC) 2023, Volume 1. Ed.: Kohei Arai, 74–91, Springer Nature Switzerland. doi:10.1007/978-3-031-47454-5_6

Automated floorplan generation using mathematical optimization
Zhong, Y.; Geiger, A.
2023. ECPPM 2022 - eWork and eBusiness in Architecture, Engineering and Construction 2022 – Proceedings of the 14th European Conference on Product and Process Modelling (ECPPM 2022), September 14-16, 2022, Trondheim, Norway., 404–410, CRC Press. doi:10.1201/9781003354222-52

A Hybrid Learning-Driven Computer Vision Framework for Reverse Engineering via Enhanced 3D Shape Reconstruction
Salem, M.; Elkaseer, A.; Rees, A.; Scholz, S. G.
2023. Proceedings of the Future Technologies Conference (FTC) 2022, Volume 2, 848–861, Springer International Publishing. doi:10.1007/978-3-031-18458-1_58

Critical Assessment of Current State of the Art in Wearable Sensor Nodes with Energy Harvesting Systems for Healthcare Applications
Alattar, A. E.; Elkaseer, A.; Scholz, S.; Mohsen, S.
2023. Proceedings of the Future Technologies Conference (FTC) 2022. Vol.: 3. Ed.: K. Arai, 398–412, Springer International Publishing. doi:10.1007/978-3-031-18344-7_27

Light-Field Camera Based Spatial Multiple Small Particle Tracking with Post-processing
Zhang, M.; Matthes, J.; Aleksandrov, K.; Gehrmann, H.-J.; Vogelbacher, M.
2023. Advances in Automation, Mechanical and Design Engineering – SAMDE 2021. Ed.: M. Laribi, 95–123, Springer International Publishing. doi:10.1007/978-3-031-09909-0_8

Computational, Label, and Data Efficiency in Deep Learning for Sparse 3D Data. PhD dissertation
Li, L.
2023, November 30. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000165034

Deep Learning-Based Particle Detection and Instance Segmentation for Microscopy Images. PhD dissertation
Scherr, T.
2023, October 20. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000163187

A Concept for Deployment and Evaluation of Unsupervised Domain Adaptation in Cognitive Perception Systems. PhD dissertation
Schutera, M.
2023, October 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000162895

Development of a compact wireless SAW Pirani vacuum microsensor with extended range and sensitivity. PhD dissertation
Toto, S.
2023, September 25. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161670

Robot-Assisted Full Automation Interface: Touch-Response On Zebrafish Larvae. PhD dissertation
Wang, Y.
2023, August 10. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161245

A Novel Plenoptic Camera based Measurement System for the Analysis of Flight and Combustion Properties of Refuse-derived Fuel Particles Utilizing Tracking-by-Detection. PhD dissertation
Zhang, M.
2023, August 3. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000161108

Ein generisches und hoch skalierbares Framework zur Automatisierung und Ausführung wissenschaftlicher Datenverarbeitungs- und Simulationsworkflows. PhD dissertation
Liu, J.
2023, July 13. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000160430

A Generic Flexible and Scalable Method for Using Evolutionary Algorithms in Cluster Computing Environments. PhD dissertation
Khalloof, H.
2023, July 3. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000160054

Multiple Object Tracking in Light Microscopy Images Using Graph-based and Deep Learning Methods. PhD dissertation
Löffler, K.
2023, June 29. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000158917

The Role of Spatial Scale in Electricity System Optimisation Models. PhD dissertation
Frysztacki, M. M.
2023, April 6. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000157620/v2

Automation of section acquisition for array tomography. PhD dissertation
Hoffmann, J.
2023, February 6. Karlsruher Institut für Technologie (KIT)

Automation of section acquisition for Array Tomography. PhD dissertation
Hoffmann, J.
2023. Karlsruher Institut für Technologie (KIT)

Facilitating and Enhancing the Performance of Model Selection for Energy Time Series Forecasting in Cluster Computing Environments. PhD dissertation
Shahoud, S.
2023, January 23. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000154568

Data-Driven Methods for Managing Anomalies in Energy Time Series. PhD dissertation
Turowski, M.
2023, July 6. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000154434

Neue Methodik zur Optimierung von Druckverfahren für die Herstellung funktionaler Mikrostrukturen und hybrider elektronischer Schaltungen. PhD dissertation
Ungerer, M.
2023, December 19. Karlsruher Institut für Technologie (KIT)

From Ideal to Stack-like Contacting of an SOC
Grosselindemann, C.; Esau, D.; Dorn, M.; Bauer, F. M.; Wissmeier, L.; Weber, A.
2023. ECS Transactions, 111 (6), 533–546. doi:10.1149/11106.0533ecst

Precision Face Milling of Maraging Steel 350: An Experimental Investigation and Optimization Using Different Machine Learning Techniques
Abbas, A. T.; Helmy, M. O.; Al-Abduljabbar, A. A.; Soliman, M. S.; Hasan, A. S.; Elkaseer, A.
2023. Machines, 11 (11), Art.-Nr.: 1001. doi:10.3390/machines11111001

WITHDRAWN: Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision
Streier, R.; Wirtz, S.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Zhang, M.; Vogelbacher, M.; Matthes, J.; Scherer, V.
2023. Fuel, 338, Art.-Nr.: 127122. doi:10.1016/j.fuel.2022.127122

Input and state constrained inverse optimal control with application to power networks
Jouini, T. K.; Sun, Z.; Renganathan, V.; Hagenmeyer, V.
2023. IFAC-PapersOnLine, 56 (2), 5451 – 5456. doi:10.1016/j.ifacol.2023.10.196

Withdrawal notice to: Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision [Fuel 338 (2023) 127122]
Streier, R.; Wirtz, S.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Zhang, M.; Vogelbacher, M.; Matthes, J.; Scherer, V.
2023. Fuel, 345, Art.-Nr.: 127898. doi:10.1016/j.fuel.2023.127898

Prof. Dr.-Ing. habil. Joachim Rudolph zum 60. Geburtstag
Bretthauer, G.
2023. at - Automatisierungstechnik, 71 (10), 909–911. doi:10.1515/auto-2023-0170

Chromatic Swept-Source Laser Scanning - Konzept für eine zellauflösende konfokale Laserspaltlampe? [Chromatic Swept-Source Laser Scanning - Concept for a Cell-Resolving Confocal Laser Slit Lamp?]
Sperlich, K.; Bohn, S.; Reichert, K.-M.; Stolz, H.; Guthoff, R. F.; Stachs, O.; Allgeier, S.
2023. Klinische Monatsblätter für Augenheilkunde, 240 (12), 1375 – 1382. doi:10.1055/a-2184-9382

Survey of real-world grid incidents – opportunities, arising challenges and lessons learned for the future converter dominated power system
Wachter, J.; Gröll, L.; Hagenmeyer, V.
2023. IEEE Open Journal of Power Electronics, 5, 50–69. doi:10.1109/OJPEL.2023.3343167

Wire Electrical Discharge Machining of AISI304 and AISI316 Alloys: A Comparative Assessment of Machining Responses, Empirical Modeling and Multi-Objective Optimization
Aboueleaz, M. A.; Naeim, N.; Abdelgaliel, I. H.; Aly, M. F.; Elkaseer, A.
2023. Journal of Manufacturing and Materials Processing, 7 (6), Article no: 194. doi:10.3390/jmmp7060194

An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids
Deininger, L.; Jung-Klawitter, S.; Mikut, R.; Richter, P.; Fischer, M.; Karimian-Jazi, K.; Breckwoldt, M. O.; Bendszus, M.; Heiland, S.; Kleesiek, J.; Opladen, T.; Hübschmann, O. K.; Hübschmann, D.; Schwarz, D.
2023. Scientific Reports, 13, Art.-Nr.: 21231. doi:10.1038/s41598-023-48343-7

Determination of the statistical distribution of drag and lift coefficients of refuse derived fuel by computer vision
Streier, R.; Wirtz, S.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Zhang, M.; Vogelbacher, M.; Matthes, J.; Scherer, V.
2023. Fuel, 352, 128847. doi:10.1016/j.fuel.2023.128847

Physics-Informed Machine Learning for Power Grid Frequency Modeling
Kruse, J.; Cramer, E.; Schäfer, B.; Witthaut, D.
2023. PRX energy, 2 (4), Art.-Nr.: 043003. doi:10.1103/PRXEnergy.2.043003

Local versus global stability in dynamical systems with consecutive Hopf bifurcations
Böttcher, P. C.; Schäfer, B.; Kettemann, S.; Agert, C.; Witthaut, D.
2023. Physical Review Research, 5 (3), Art-Nr.: 033139. doi:10.1103/PhysRevResearch.5.033139

A two-stage parallel hybrid method for power system dynamic security assessment = Eine zweistufige parallele hybride Methode zur dynamischen Sicherheitsbewertung von Stromnetzen
Kyesswa, M.; Çakmak, H. K.; Kühnapfel, U.; Hagenmeyer, V.
2023. at - Automatisierungstechnik, 71 (12), 1002–1017. doi:10.1515/auto-2023-0079

Model Predictive Control of Distributed Energy Resources in Residential Buildings Considering Forecast Uncertainties
Langner, F.; Wang, W.; Frahm, M.; Hagenmeyer, V.
2023. Energy and Buildings, 303, Article no: 113753. doi:10.1016/j.enbuild.2023.113753

The Kopernikus ENSURE Co-Demonstration Platform
Mehlmann, G.; Kühnapfel, U.; Wege, F.; Winkens, A.; Scheibe, C.; Vogel, S.; Noglik, P.; Gratza, M.; Richter, J.; Weber, M.; Burlakin, I.; Kuri, A.; Wagner, T.; Hubschneider, S.; Poppenborg, R.; Heins, T.; Förderer, K. M.; Ulbig, A.; Monti, A.; Hagenmeyer, V.; Luther, M.
2023. IEEE Open Journal of Power Electronics, 4, 987–1002. doi:10.1109/OJPEL.2023.3332515

Influence of Technological Parameters on Chip Formation and Chip Control in Precision Hard Turning of Ti-6Al-4V
Abdelnasser, E.; El-Sanabary, S.; Nassef, A.; Barakat, A.; Elkaseer, A.
2023. Micromachines, 14 (10), 1–19. doi:10.3390/mi14101973

On the quantitative assessment of the effect of multiple process parameters on the printed layer height in 3D inkjet printing
Elkaseer, A.; Chen, K. J.; Kuchta, M.; Scholz, S. G.
2023. Virtual and Physical Prototyping, 18 (1), Art.-Nr.: e2269898. doi:10.1080/17452759.2023.2269898

Improving generative adversarial networks for patch-based unpaired image-to-image translation
Böhland, M.; Bruch, R.; Bäuerle, S.; Rettenberger, L.; Reischl, M.
2023. IEEE Access, 11, 127895–127906. doi:10.1109/ACCESS.2023.3331819

3072 – Understanding the relationship between stem cell heterogeneity and reconstitution kinetics in hematopoietic systems: Insights from in-depth single-cell analysis of clonally-derived systems
Grünschläger, F.; Al-Sabah, J.; Correa, E. R.; Kumpost, V.; Malmierca, P. H.; Mathioudaki, A.; Anstee, N.; Gräsel, J.; Vonficht, D.; Zaugg, J.; Mikut, R.; Milsom, M.; Trumpp, A.; Hübschmann, D.; Haas, S.
2023. Experimental Hematology, 124, S86. doi:10.1016/j.exphem.2023.06.179

Using weather data in energy time series forecasting: the benefit of input data transformations
Neumann, O.; Turowski, M.; Mikut, R.; Hagenmeyer, V.; Ludwig, N.
2023. Energy Informatics, 6 (1), Art.-Nr.: 44. doi:10.1186/s42162-023-00299-8

Secure Equality Test Technique Using Identity-Based Signcryption for Telemedicine Systems
Ramadan, M.; Raza, S.
2023. IEEE Internet of Things Journal, 10 (18), 16594–16604. doi:10.1109/JIOT.2023.3269222

Prof. Dr.-Ing. Ulrich Epple zum 70. Geburtstag
Bretthauer, G.
2023. at - Automatisierungstechnik, 71 (8), 720–721. doi:10.1515/auto-2023-0125

Transformer training strategies for forecasting multiple load time series
Hertel, M.; Beichter, M.; Heidrich, B.; Neumann, O.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2023. Energy Informatics, 6 (S1), Art.-Nr.: 20. doi:10.1186/s42162-023-00278-z

Two-stage quality monitoring of a laser welding process using machine learning – An approach for fast yet precise quality monitoring
Dold, P. M.; Bleier, F.; Boley, M.; Mikut, R.
2023. at - Automatisierungstechnik, 71 (10), 878–890. doi:10.1515/auto-2023-0044

Selected contributions from the Workshop “Computational Intelligence”
Mikut, R.; Kroll, A.; Schulte, H.
2023. at - Automatisierungstechnik, 71 (10), 817–819. doi:10.1515/auto-2023-0159

A fully automated touch-response behavior inspection pipeline on zebrafish larvae
Wang, Y.; Pylatiuk, C.; Mikut, R.; Peravali, R.; Reischl, M.
2023. at - Automatisierungstechnik, 71 (10), 845–852. doi:10.1515/auto-2023-0013

Abstracts of the 12th DACH+ Conference on Energy Informatics 2023
Grafenhorst, S.; Förderer, K.; Hagenmeyer, V.
2023. Energy Informatics, 6 (S2). doi:10.1186/s42162-023-00272-5

A new hybrid risk assessment process for cyber security design of smart grids using fuzzy analytic hierarchy processes
Canbolat, S.; Elbez, G.; Hagenmeyer, V.
2023. Automatisierungstechnik. doi:10.1515/auto-2023-0089

Synchronization of oscillatory growth prepares fungal hyphae for fusion
Wernet, V.; Kriegler, M.; Kumpost, V.; Mikut, R.; Hilbert, L.; Fischer, R.
2023. eLife, 12, Art.-Nr.: e83310. doi:10.7554/eLife.83310

Longitudinal evaluation of the subbasal nerve plexus at identical corneal regions by large-area confocal microscopy
Bohn, S.; Stache, N.; Sterenczak, K.; Sperlich, K.; Allgeier, S.; Köhler, B.; Mikut, R.; Reichert, K.-M.; Guthoff, R.; Stachs, O.
2023. Investigative ophthalmology & visual science, 64 (8), Art.-Nr.: 4025

Unsupervised GAN epoch selection for biomedical data synthesis
Böhland, M.; Bruch, R.; Löffler, K.; Reischl, M.
2023. Current Directions in Biomedical Engineering, 9 (1), 467–470. doi:10.1515/cdbme-2023-1117

A Lightweight Framework for Semantic Segmentation of Biomedical Images
Münke, F. R.; Rettenberger, L.; Popova, A.; Reischl, M.
2023. Current Directions in Biomedical Engineering, 9 (1), 190–193. doi:10.1515/cdbme-2023-1048

Mask R-CNN Outperforms U-Net in Instance Segmentation for Overlapping Cells
Rettenberger, L.; Münke, F. R.; Bruch, R.; Reischl, M.
2023. Current Directions in Biomedical Engineering, 9 (1), 335–338. doi:10.1515/cdbme-2023-1084

Meteorological conditions during periods of low wind speed and insolation in Germany: The role of weather regimes
Mockert, F.; Grams, C. M.; Brown, T.; Neumann, F.
2023. Meteorological Applications, 30 (4), Art.Nr.: e2141. doi:10.1002/met.2141

CyPhERS: A cyber-physical event reasoning system providing real-time situational awareness for attack and fault response
Müller, N.; Bao, K.; Matthes, J.; Heussen, K.
2023. Computers in Industry, 151, Art.-Nr.: 103982. doi:10.1016/j.compind.2023.103982

Multi-Objective Optimization of AISI P20 Mold Steel Machining in Dry Conditions Using Machine Learning—TOPSIS Approach
Abbas, A. T.; Sharma, N.; Alsuhaibani, Z. A.; Sharma, A.; Farooq, I.; Elkaseer, A.
2023. Machines, 11 (7), Art.-Nr.: 748. doi:10.3390/machines11070748

Customized Uncertainty Quantification of Parking Duration Predictions for EV Smart Charging
Phipps, K.; Schwenk, K.; Briegel, B.; Mikut, R.; Hagenmeyer, V.
2023. IEEE Internet of Things Journal, 10 (23), 20649–20661. doi:10.1109/JIOT.2023.3299201

Can BioSAXS detect ultrastructural changes of antifungal compounds in Candida albicans?–an exploratory study
Hilpert, K.; Rumancev, C.; Gani, J.; Collis, D. W. P.; Lopez-Perez, P. M.; Garamus, V. M.; Mikut, R.; Rosenhahn, A.
2023. Frontiers in Pharmacology, 14, Art.-Nr.: 1141785. doi:10.3389/fphar.2023.1141785

Effect of Wiper Edge Geometry on Machining Performance While Turning AISI 1045 Steel in Dry Conditions Using the VIKOR-ML Approach
Abbas, A. T.; Sharma, N.; Soliman, M. S.; El Rayes, M. M.; Sharma, R. C.; Elkaseer, A.
2023. Machines, 11 (7), Art.-Nr.: 719. doi:10.3390/machines11070719

Endogenous learning for green hydrogen in a sector-coupled energy model for Europe
Zeyen, E.; Victoria, M.; Brown, T.
2023. Nature Communications, 14 (1), Art-Nr.: 3743. doi:10.1038/s41467-023-39397-2

Predicting the power grid frequency of European islands
Lund Onsaker, T.; Nygård, H. S.; Gomila, D.; Colet, P.; Mikut, R.; Jumar, R.; Maass, H.; Kühnapfel, U.; Hagenmeyer, V.; Schäfer, B.
2023. Journal of Physics: Complexity, 4 (1), Article no: 015012. doi:10.1088/2632-072X/acbd7f

Understanding electricity prices beyond the merit order principle using explainable AI
Trebbien, J.; Rydin Gorjão, L.; Praktiknjo, A.; Schäfer, B.; Witthaut, D.
2023. Energy and AI, 13, Article no: 100250. doi:10.1016/j.egyai.2023.100250

Experimental Investigation of Surface Roughness and Material Removal Rate in Wire EDM of Stainless Steel 304
Naeim, N.; AbouEleaz, M. A.; Elkaseer, A.
2023. Materials, 16 (3), Art.-Nr. 1022. doi:10.3390/ma16031022

PyPSA-Earth. A new global open energy system optimization model demonstrated in Africa
Parzen, M.; Abdel-Khalek, H.; Fedotova, E.; Mahmood, M.; Frysztacki, M. M.; Hampp, J.; Franken, L.; Schumm, L.; Neumann, F.; Poli, D.; Kiprakis, A.; Fioriti, D.
2023. Applied Energy, 341, 121096. doi:10.1016/j.apenergy.2023.121096

Application of CFD in Control-Oriented Modeling of a DTB’s Hydrodynamics
Schaßberger, J. M.; Gröll, L.
2023. IFAC-PapersOnLine, 55 (40), 55–60. doi:10.1016/j.ifacol.2023.01.048

Brain Tumor Classification Using Hybrid Single Image Super-Resolution Technique with ResNext101_32x8d and VGG19 Pre-Trained Models
Mohsen, S.; Ali, A. M.; El-Rabaie, E.-S. M.; ElKaseer, A.; Scholz, S. G.; Hassan, A. M. A.
2023. IEEE Access, 11, 55582–55595. doi:10.1109/ACCESS.2023.3281529

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron
El Rayes, M. M.; Abbas, A. T.; Al-Abduljabbar, A. A.; Ragab, A. E.; Benyahia, F.; Elkaseer, A.
2023. Metals, 13 (6), Art.-Nr.: 1098. doi:10.3390/met13061098

Corrigendum to “ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles” [Energy Build. 265 (2022) 112096]
Quintana, M.; Stoeckmann, T.; Park, J. Y.; Turowski, M.; Hagenmeyer, V.; Miller, C.
2023. Energy and Buildings, 286, Art.-Nr.: 112930. doi:10.1016/j.enbuild.2023.112930

Herrn Prof. Franz Mesch zum 90. Geburtstag
Bretthauer, G.; Beyerer, J.; Stiller, C.
2023. at - Automatisierungstechnik, 71 (2), 176–178. doi:10.1515/auto-2023-0006

Inverse methods: How feasible are spatially low-resolved capacity expansion modelling results when disaggregated at high spatial resolution?
Frysztacki, M. M.; Hagenmeyer, V.; Brown, T.
2023. Energy, 281, Art.-Nr.: 128133. doi:10.1016/j.energy.2023.128133

Taxane-Induced Neuropathy and Its Ocular Effects—A Longitudinal Follow-up Study in Breast Cancer Patients
Stache, N.; Bohn, S.; Sperlich, K.; George, C.; Winter, K.; Schaub, F.; Do, H.-V.; Röhlig, M.; Reichert, K.-M.; Allgeier, S.; Stachs, O.; Stachs, A.; Sterenczak, K. A.
2023. Cancers, 15 (9), Art.-Nr.: 2444. doi:10.3390/cancers15092444

Charge controlled interactions between DNA-modified silica nanoparticles and fluorosurfactants in microfluidic water-in-oil droplets
Sheshachala, S.; Huber, B.; Schuetzke, J.; Mikut, R.; Scharnweber, T.; Domínguez, C. M.; Mutlu, H.; Niemeyer, C. M.
2023. Nanoscale Advances, 5 (15), 3914–3923. doi:10.1039/D3NA00124E

Development and Numerical Optimization of a System of Integrated Agents for Serial Production Lines
Alkhalefah, H.; Umer, U.; Abidi, M. H.; Elkaseer, A.
2023. Processes, 11 (5), Art.-Nr.: 1578. doi:10.3390/pr11051578

Occupant-oriented demand response with multi-zone thermal building control
Frahm, M.; Dengiz, T.; Zwickel, P.; Maaß, H.; Matthes, J.; Hagenmeyer, V.
2023. Applied Energy, 347, Art.-Nr.: 121454. doi:10.1016/j.apenergy.2023.121454

The Cell Tracking Challenge: 10 years of objective benchmarking
Maška, M.; Ulman, V.; Delgado-Rodriguez, P.; Gómez-de-Mariscal, E.; Nečasová, T.; Guerrero Peña, F. A.; Ren, T. I.; Meyerowitz, E. M.; Scherr, T.; Löffler, K.; Mikut, R.; Guo, T.; Wang, Y.; Allebach, J. P.; Bao, R.; Al-Shakarji, N. M.; Rahmon, G.; Toubal, I. E.; Palaniappan, K.; Lux, F.; Matula, P.; Sugawara, K.; Magnusson, K. E. G.; Aho, L.; Cohen, A. R.; Arbelle, A.; Ben-Haim, T.; Raviv, T. R.; Isensee, F.; Jäger, P. F.; Maier-Hein, K. H.; Zhu, Y.; Ederra, C.; Urbiola, A.; Meijering, E.; Cunha, A.; Muñoz-Barrutia, A.; Kozubek, M.; Ortiz-de-Solórzano, C.
2023. Nature Methods, 20, 1010–1020. doi:10.1038/s41592-023-01879-y

Validating neural networks for spectroscopic classification on a universal synthetic dataset
Schuetzke, J.; Szymanski, N. J.; Reischl, M.
2023. npj Computational Materials, 9 (1), 100. doi:10.1038/s41524-023-01055-y

A comparative co-simulation analysis to improve the sustainability of cogeneration-based district multi-energy systems using photovoltaics, power-to-heat, and heat storage
Erdmann, A.; Marcellan, A.; Stock, J.; Neuroth, D.; Utama, C.; Suriyah, M.; Steinle, S.; Müller, F.; Hering, D.; Francke, H.; Gritzbach, S.; Henke, M.; Pflugradt, N.; Çakmak, H.; Kotzur, L.; Stolten, D.; Leibfried, T.; Müller, D.; Schlatmann, R.; Xhonneux, A.; Hagenmeyer, V.; Ulbrich, C.
2023. Energy conversion and management, 291, Artkl.Nr.: 117226. doi:10.1016/j.enconman.2023.117226

Categorization and Evaluation Methods for Control Strategies of Bilateral Tasks in Arm Prosthetics
Hetto, T.; Schulz, S.; Reischl, M.
2023. IEEE Access, 11, 52501–52508. doi:10.1109/ACCESS.2023.3278836

Repurposing FDA‐Approved Drugs for Temozolomide‐resistant IDH1 Mutant Glioma using High‐Throughput Miniaturized Screening on Droplet Microarray Chip
Cui, H.; Sun, X.; Schilling, M.; Herold-Mende, C.; Reischl, M.; Levkin, P. A.; Popova, A. A.; Turcan, Ş.
2023. Advanced Healthcare Materials, 12 (24), Art.-Nr.: 2300591. doi:10.1002/adhm.202300591

Broad ranges of investment configurations for renewable power systems, robust to cost uncertainty and near-optimality
Neumann, F.; Brown, T.
2023. iScience, 26 (5), 106702. doi:10.1016/j.isci.2023.106702

A Novel Plenoptic Camera-Based Measurement System for the Investigation into Flight and Combustion Behavior of Refuse-Derived Fuel Particles
Zhang, M.; Vogelbacher, M.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Streier, R.; Wirtz, S.; Scherer, V.; Matthes, J.
2023. ACS Omega, 8 (19), 16700–16712. doi:10.1021/acsomega.2c08004

Camera based flame stability monitoring and control of multi-burner systems using deep learning based flame detection
Matthes, J.; Waibel, P.; Kollmer, M.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Vogelbacher, M.
2023. Thermal Science and Engineering Progress, 41, Artkl.Nr.: 101859. doi:10.1016/j.tsep.2023.101859

Random fractal-enabled physical unclonable functions with dynamic AI authentication
Sun, N.; Chen, Z.; Wang, Y.; Wang, S.; Xie, Y.; Liu, Q.
2023. Nature Communications, 14, Article no: 2185. doi:10.1038/s41467-023-37588-5

Effects of Tool Edge Geometry and Cutting Conditions on the Performance Indicators in Dry Turning AISI 1045 Steel
Abbas, A. T.; El Rayes, M. M.; Al-Abduljabbar, A. A.; Ragab, A. E.; Benyahia, F.; Elkaseer, A.
2023. Machines, 11 (3), 397. doi:10.3390/machines11030397

Investigations of Ratio-Based Integrated Influence Lines as Features for Bridge-Damage Detection
Döring, A.; Vogelbacher, M.; Schneider, O.; Müller, J.; Hinz, S.; Matthes, J.
2023. Infrastructures, 8 (4), Art.-Nr. 72. doi:10.3390/infrastructures8040072

Synthesis of large scale 3D microscopic images of 3D cell cultures for training and benchmarking
Bruch, R.; Keller, F.; Böhland, M.; Vitacolonna, M.; Klinger, L.; Rudolf, R.; Reischl, M.
2023. PLOS ONE, 18 (3), Article no: e0283828. doi:10.1371/journal.pone.0283828

Automated high-throughput image processing as part of the screening platform for personalized oncology
Schilling, M. P.; El Khaled El Faraj, R.; Urrutia Gómez, J. E.; Sonnentag, S. J.; Wang, F.; Nestler, B.; Orian-Rousseau, V.; Popova, A. A.; Levkin, P. A.; Reischl, M.
2023. Scientific Reports, 13, Article no: 5107. doi:10.1038/s41598-023-32144-z

The Rise of GoodFATR: A Novel Accuracy Comparison Methodology for Indicator Extraction Tools
Caballero, J.; Gomez, G.; Matic, S.; Sánchez, G.; Sebastián, S.; Villacañas, A.
2023. Future Generation Computer Systems, 144, 74–89. doi:10.1016/j.future.2023.02.012

Energy Hub Gas: A Modular Setup for the Evaluation of Local Flexibility and Renewable Energy Carriers Provision
Poppenborg, R.; Chlosta, M.; Ruf, J.; Hotz, C.; Düpmeier, C.; Kolb, T.; Hagenmeyer, V.
2023. Energies, 16 (6), Art.-Nr.: 2720. doi:10.3390/en16062720

Microscopic Fluctuations in Power-Grid Frequency Recordings at the Subsecond Scale
Schäfer, B.; Rydin Gorjão, L.; Yalcin, G. C.; Förstner, E.; Jumar, R.; Maass, H.; Kühnapfel, U.; Hagenmeyer, V.
2023. (H. Sayama, Ed.) Complexity, 2023, Art.-Nr.: 2657039. doi:10.1155/2023/2657039

Vapour polishing of fused deposition modelling (FDM) parts: a critical review of different techniques, and subsequent surface finish and mechanical properties of the post-processed 3D-printed parts
Mathew, A.; Kishore, S. R.; Tomy, A. T.; Sugavaneswaran, M.; Scholz, S. G.; Elkaseer, A.; Wilson, V. H.; John Rajan, A.
2023. Progress in Additive Manufacturing, 8, 1161–1178. doi:10.1007/s40964-022-00391-7

Temperature-based quality analysis in ultrasonic welding of copper sheets with microstructural joint evaluation and machine learning methods
Schwarz, E. B.; Bleier, F.; Guenter, F.; Mikut, R.; Bergmann, J. P.
2023. Welding in the World, 67, 1437–1448. doi:10.1007/s40194-023-01463-0

Oscillating combustion of different fuel types for NOₓ reduction in grate furnaces and coal burners
Jolibois, N.; Gehrmann, H.-J.; Aleksandrov, K.; Hauser, M.; Stapf, D.; Jäger, B.; Wirtz, S.; Scherer, V.; Danz, P.; Matthes, J.; Vogelbacher, M.; Waibel, P.
2023. Fuel, 340, Art.-Nr.: 127504. doi:10.1016/j.fuel.2023.127504

Self-Supervised Learning for Annotation Efficient Biomedical Image Segmentation
Rettenberger, L.; Schilling, M.; Elser, S.; Boehland, M.; Reischl, M.
2023. IEEE Transactions on Biomedical Engineering, 70 (9), 2519–2528. doi:10.1109/TBME.2023.3252889

Multi-Objective Optimization of Performance Indicators in Turning of AISI 1045 under Dry Cutting Conditions
Abbas, A. T.; Al-Abduljabbar, A. A.; El Rayes, M. M.; Benyahia, F.; Abdelgaliel, I. H.; Elkaseer, A.
2023. Metals, 13 (1), 96. doi:10.3390/met13010096

Import options for chemical energy carriers from renewable sources to Germany
Hampp, J.; Düren, M.; Brown, T.
2023. PLOS ONE, 18 (2), Art.-Nr.: e0262340. doi:10.1371/journal.pone.0281380

A Photovoltaic System Model Integrating FAIR Digital Objects and Ontologies
Schweikert, J.; Stucky, K.-U.; Süß, W.; Hagenmeyer, V.
2023. Energies, 16 (3), Art.-Nr.: 1444. doi:10.3390/en16031444

A Digital Framework for Locally and Geographically Distributed Simulation of Power Grids
Kyesswa, M.; Weber, M.; Wiegel, F.; Wachter, J.; Waczowicz, S.; Kühnapfel, U.; Hagenmeyer, V.
2023. Energy Technology, 11 (3). doi:10.1002/ente.202201186

An In-depth Comparison of Experiment Tracking Tools for Machine Learning Applications
Budras, T.; Blanck, M.; Berger, T.; Schmidt, A.
2023. International Journal on Advances in Software, 15 (3 & 4), 152–164

Noise facilitates entrainment of a population of uncoupled limit cycle oscillators
Kumpost, V.; Hilbert, L.; Mikut, R.
2023. Journal of The Royal Society Interface, 20 (198), Art.-Nr.: 20220781. doi:10.1098/rsif.2022.0781

Analytical uncertainty propagation for multi-period stochastic optimal power flow
Bauer, R.; Mühlpfordt, T.; Ludwig, N.; Hagenmeyer, V.
2023. Sustainable Energy, Grids and Networks, 33, Art.-Nr.: 100969. doi:10.1016/j.segan.2022.100969

Model Diagnostics and Forecast Evaluation for Quantiles
Gneiting, T.; Wolffram, D.; Resin, J.; Kraus, K.; Bracher, J.; Dimitriadis, T.; Hagenmeyer, V.; Jordan, A. I.; Lerch, S.; Phipps, K.; Schienle, M.
2023. Annual Review of Statistics and Its Application, 10. doi:10.1146/annurev-statistics-032921-020240

A Purely Visual Re-ID Approach for Bumblebees (Bombus terrestris)
Borlinghaus, P.; Tausch, F.; Rettenberger, L.
2023. Smart Agricultural Technology, 3, Art.-Nr.: 100135. doi:10.1016/j.atech.2022.100135

Probabilistic load forecasting using post-processed weather ensemble predictions
Ludwig, N.; Arora, S.; Taylor, J. W.
2023. Journal of the Operational Research Society, 74 (3), 1008–1020. doi:10.1080/01605682.2022.2115411

Controlling non-stationarity and periodicities in time series generation using conditional invertible neural networks
Heidrich, B.; Turowski, M.; Phipps, K.; Schmieder, K.; Süß, W.; Mikut, R.; Hagenmeyer, V.
2023. Applied Intelligence, 53 (8), 8826–8843. doi:10.1007/s10489-022-03742-7

Stability Criteria for Time-Delay Systems from an Insightful Perspective on the Characteristic Equation
Scholl, T. H.; Gröll, L.
2023. IEEE Transactions on Automatic Control, 68 (4), 2352–2359. doi:10.1109/TAC.2022.3174001

DiversityScanner-360°: An Automated System for Digitizing Invertebrate Bulk Samples
Wührl, L.; Rotmann, K.; Meier, R.; Hartop, E.; Klug, N.; Pylatiuk, C.
2023. 2023 3rd International Conference on Robotics, Automation and Artificial Intelligence (RAAI), Singapore, Singapore, 14-16 December 2023, 226–230, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/RAAI59955.2023.10601274

Probabilistic Forecasting of Day-Ahead Electricity Prices and their Volatility with LSTMs
Trebbien, J.; Pütz, S.; Schäfer, B.; Nygård, H. S.; Gorjão, L. R.; Witthaut, D.
2023. Powering solutions for decarbonized and resilient future smartgrids, 5 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE56780.2023.10407112

Resilienz im Quartier
Reim, M.; Zanger, J.; Kröner, M.; Krautkremer, B.; Kühnbach, M.; März, S.; Stelzer, V.; Waczowicz, S.; Streib, G.; Trenks, H.; Galenzowski, J.; Albiez, M.; Beil, M.
2023. Jahrestagung 2023 des Forschungsverbund Erneuerbare Energien (FVEE) – Forschung für ein resilientes Energiesystem in Zeiten globaler Krisen, Berlin, 10th-11th October 2023

Wärmenetz-gekoppelte Speicherung im tiefen Untergrund
Schill, E.; Waczowicz, S.; Kohl, T.; Stricker, K.; Bracke, R.; Sass, I.; Rink, K.
2023. Forschung für die Wärmewende – klimaneutral, ­effizient und flexibel : Beiträge zur FVEE-Jahrestagung 2022, Berlin, 12th -13th October 2022, 96–101, ForschungsVerbund Erneuerbare Energien (FVEE)

Hypergraph- Based Fast Distributed AC Power Flow Optimization
Dai, X.; Lian, Y.; Jiang, Y.; Jones, C. N.; Hagenmeyer, V.
2023. 2023 62nd IEEE Conference on Decision and Control (CDC), 4572 – 4579, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC49753.2023.10383354

Experimental Analysis of Immersion & Invariance Adaptive Control for an Interleaved DC/DC Boost Converter with Unknown Load Type
Wachter, J.; Gröll, L.; Hagenmeyer, V.
2023. 2023 IEEE PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE56780.2023.10407194

Continuous Measurement of Individual Formaldehyde Exposure with a DIY Photometer
Petani, L.; Lorenz, M.; Pylatiuk, C.
2023. 2023 IEEE SENSORS, Vienna, Austria, 29th October 2023 - 1st November 2023, 1–4, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SENSORS56945.2023.10325275

Dissolved ozone sensing in water and blood based on commercial screen-printed and BDD electrodes
Petani, L.; Llupa, L.; Peng, Z.; Ogata, G.; Koker, L.; Gengenbach, U.; Einaga, Y.; Pylatiuk, C.
2023. IEEE Biomedical Circuits and Systems Conference (BioCAS), Toronto, ON, Canada, 19th-21st October 2023, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BioCAS58349.2023.10388985

Flatness of Some DC Microgrid Topologies
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2023. 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, 16th-18th October 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380906

Application of Model-Free Control to Reduce the Total Harmonic Distortion of Inverters
Wachter, J.; Gröll, L.; Hagenmeyer, V.
2023. 2023 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, Germany, 16-18 October 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380817

Towards a Real-World Dispatchable Feeder
Beichter, S.; Beichter, M.; Werling, D.; Galenzowski, J.; Weise, V.; Hildenbrand, C.; Wiegel, F.; Mikut, R.; Waczowicz, S.; Hagenmeyer, V.
2023. 2023 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, Germany, 16-18 October 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380834

Composing Power Flow Patterns through Coordinated Dispatch of Energy Packets
Schulz, D.; Schneider, K.; Weßbecher, M.; Hagenmeyer, V.; Zitterbart, M.; Hiller, M.
2023. 2023 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, Germany, 16-18 October 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380818

Modes of Energy Packets in the Energy Packet Grid
Schneider, K.; Weßbecher, M.; Schulz, D.; Hagenmeyer, V.; Hiller, M.; Zitterbart, M.
2023. 2023 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, Germany, 16-18 October 2023, 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380897

Experimental validation of demand side response rates for frequency control
Casasola-Aignesberger, L.; Wiegel, F.; Waczowicz, S.; Hagenmeyer, V.; Martinez, S.
2023. 2023 8th IEEE Workshop on the Electronic Grid (eGRID), Karlsruhe, Germany, 16-18 October 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/eGrid58358.2023.10380814

MEMS LiDAR Sensor Simulation for Autonomous Driving: A Novel Framework Using Open-source Tools
Berens, F.; Elser, S.; Reischl, M.
2023. ISR Europe 2023: 56th International Symposium on Robotics, in cooperation with Fraunhofer IPA, Stuttgart, 26th-27th September 2023, VDE Verlag

A Fair and In-Depth Evaluation of Existing End-to-End Entity Linking Systems
Bast, H.; Hertel, M.; Prange, N.
2023. Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapur, 6th-10th December 2023, Hrsg.: Bouamor, Houda; Pino, Juan; Bali, Kalika, 6659–6672, Association for Computational Linguistics (ACL). doi:10.18653/v1/2023.emnlp-main.411

AI 2 Seg: A Method and Tool for AI-based Annotation Inspection of Biomedical Instance Segmentation Datasets
Schilling, M. P.; Klinger, L.; Schumacher, U.; Schmelzer, S.; López, M. B.; Nestler, B.; Reischl, M.
2023. 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Sydney, Australia, 24-27 July 2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EMBC40787.2023.10341074

On Evasion of Machine Learning-based Intrusion Detection in Smart Grids
Mumrez, A.; Sánchez, G.; Elbez, G.; Hagenmeyer, V.
2023. IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids. doi:10.1109/SmartGridComm57358.2023.10333966

Comparative Study on Smart Grid Security Testbeds Using MITRE ATT&CK Matrix
Mumrez, A.; Muhammad M. Roomi; Heng Chuan Tan; Daisuke Mashima; Elbez, G.; Hagenmeyer, V.
2023. 2023 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm57358.2023.10333902

Conceptual planning and implementation of an au- tomated workflow in scaled 3D printing with the aim of generating printable models from BIM data
Di, S.; Lourenzi, F.; Geiger, A.; Häfele, K.-H.; Lauble, S.
2023. Tagungsband des 34. Forum Bauinformatik 2023, Bochum, 6.-8. September 2023. Hrsg.: K. Sigalov, 209–216, Ruhr-Universität Bochum. doi:10.13154/294-10113

Practical Data Science Using the Shell
Schmidt, A.; Koubaa, M. A.
2023. Proceedings of the 20th International Conference Applied Computing (AC 2023), Funchal, Madeira, P, October 21-23, 2023

Non-linear, bivariate stochastic modelling of power-grid frequency applied to islands
Oberhofer, U.; Gorjao, L. R.; Yalcin, G. C.; Kamps, O.; Hagenmeyer, V.; Schäfer, B.
2023. 2023 IEEE Belgrade PowerTech, 1, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PowerTech55446.2023.10202986

AI-based automated active learning for discovery of hidden dynamic processes: A use case in light microscopy
Friederich, N.; Yamachui Sitcheu, A. J.; Neumann, O.; Eroglu-Kayıkçı, S.; Prizak, R.; Hilbert, L.; Mikut, R.
2023. Proceedings-33. Workshop Computational Intelligence: Berlin, 23.-24. November 2023, 31–51, KIT Scientific Publishing. doi:10.48550/arXiv.2310.04461

ZeitGeist: A Generic Tool Supporting the Dissemination of Time Series Data Following FAIR Principles
Schmidt, A.; Koubaa, M.; Schweikert, J.; Stucky, K.-U.; Süß, W.; Hagenmeyer, V.
2023. Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, 303–310, SciTePress. doi:10.5220/0012254300003598

Management Strategies for an EP device in an Energy Packet Grid
Weßbecher, M.; Marianczuk, J.; Wiegel, F.; An, S. X.; Schneider, K.; Schulz, D.; Zitterbart, M.; Hiller, M.; Hagenmeyer, V.
2023. Energy Informatics: First Energy Informatics Academy Conference, EI.A 2023, Campinas, Brazil, December 6–8, 2023, Proceedings. Ed.: B. Jørgensen, 240–256, Springer. doi:10.1007/978-3-031-48652-4_16

A Real-World District Community Platform as a Cyber-Physical-Social Infrastructure Systems in the Energy Domain
Galenzowski, J.; Waczowicz, S.; Meisenbacher, S.; Mikut, R.; Hagenmeyer, V.
2023. BuildSys ’23: Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 434–441, Association for Computing Machinery (ACM). doi:10.1145/3600100.3626347

A study on the effect of process parameters on feature resolution in 3D inkjet printing
Chen, K. J.-Y.
2023. WCMNM 2023 Proceedings, World Congress on Micro and Nano Manufacturing, Evanston, 18th - 21st September 2023

MLOps for Scarce Image Data: A Use Case in Microscopic Image Analysis
Yamachui Sitcheu, A. J.; Friederich, N.; Baeuerle, S.; Neumann, O.; Reischl, M.; Mikut, R.
2023. Proceedings 33. Workshop Computational Intelligence. Hrsg.: H. Schulte, 169–190, KIT Scientific Publishing

On Higher-Order Averaging and Flatness
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2023. 2023 9th International Conference on Control, Decision and Information Technologies (CoDIT), Rome, Italy, 03-06 July 2023, 1043–1048, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CoDIT58514.2023.10284494

Modelling and Design-for-Manufacturing of an Aerosol-on-Demand Jet-Printhead
Ungerer, M.; Benítez, J. L.; Zeltner, D.; Wenka, A.; Gengenbach, U.; Sieber, I.
2023. Simulation and Modeling Methodologies, Technologies and Applications. Ed.: G. Wagner, 1–21, Springer Nature Switzerland. doi:10.1007/978-3-031-43824-0_1

Design-for-manufacture of a dual-chamber nozzle for hydrodynamic focusing of the Aerosol-on-Demand jet-printhead
Ungerer, M.; Gengenbach, U.; Grewal, K. S.; Wenka, A.; Sieber, I.
2023. 2023 Symposium on Design, Test, Integration and Packaging of MEMS/MOEMS (DTIP), 5 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DTIP58682.2023.10267945

Tuning of discrete-time angular droop controllers
Jouini, T. K.; Sun, Z.; Hagenmeyer, V.
2023. 2023 IEEE Conference on Control Technology and Applications (CCTA), Bridgetown, Barbados, 16-18 August 2023, 741 – 745, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CCTA54093.2023.10252209

Graph-Based Time Token Recognition using Graph Neural Networks and Stanza Library
Doms, N.; Schlachter, T.; Hahn-Woernle, L.
2023. EnviroInfo : AI and Sustainability - Session III, Gesellschaft für Informatik (GI)

Dynamic Mapping for Evolutionary Algorithm Based Optimization of Energy Hub Gas Scheduling
Poppenborg, R.; Beisswanger, K.; Hotz, C.; Förderer, K.; Kolb, T.; Hagenmeyer, V.
2023. 2023 IEEE 11th International Conference on Smart Energy Grid Engineering (SEGE), 206–211, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE59172.2023.10274571

A Novel Method for Topology Preserving Static Network Reduction
Weber, M.; Çakmak, H. K.; Kühnapfel, U.; Hagenmeyer, V.
2023. 2023 IEEE 11th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 13-15 August 2023, 58–63, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE59172.2023.10274576

FAIR Data for Energy System Research – An Overview of NFDI4Energy Task Area 4
Wein, A.; Reinkensmeier, J.; Weidlich, A.; Lilliestam, J.; Hagenmeyer, V.; Richter, M.; Auer, S.; Nieße, A.; Lehnhoff, S.
2023. 1st Conference on Research Data Infrastructure (CoRDI) - Connecting Communities, Karlsruhe, 12th - 14th September 2023, 1–4, Karlsruher Institut für Technologie (KIT). doi:10.52825/CoRDI.v1i.364

The HMC Information Portal for Enhanced Metadata Collaboration in the Helmholtz FAIR Data Space
Kulla, L.; Bröder, J.; Curdt, C.; Kubin, M.; Kollai, H.; Lemster, C.; Nolden, M.; Schmieder, K.; Strupp, A.; Stucky, K.-U.; Söding, E.; Walter, K. P.; Witold, A.
2023. 1st Conference on Research Data Infrastructure (CoRDI) - Connecting Communities Karlsruhe (Germany), 12-14 September 2023. Ed.: Y. Sure-Vetter, CoRDI2023–17, Karlsruher Institut für Technologie (KIT). doi:10.52825/CoRDI.v1i.383

Enhancing Agility and Reconfigurability in Production: A Database-Driven Infrastructure to Support Additive Manufacturing with Collaborative Robotics
Mueller, T.; Scholz, S.; Salem, M.; Hagenmeyer, V.; Schmidt, A.
2023. Production Processes and Product Evolution in the Age of Disruption – Proceedings of the 9th Changeable, Agile, Reconfigurable and Virtual Production Conference (CARV2023) and the 11th World Mass Customization & Personalization Conference (MCPC2023), Bologna, Italy, June 2023, 255 – 263, Springer International Publishing. doi:10.1007/978-3-031-34821-1_28

Comparison of the Depth Accuracy of a Plenoptic Camera and a Stereo Camera System in Spatially Tracking Single Refuse-derived Fuel Particles in a Drop Shaft
Zhang, M.; Streier, R.; Vogelbacher, M.; Wirtz, S.; Scherer, V.; Matthes, J.
2023. Sensors and Electronic Instrumentation Advances. Ed.: S.Y. Yurish, 52–57, IFSA Publishing, S.L

Automated Style-Aware Selection of Annotated Pre-Training Databases in Biomedical Imaging
Molina-Moreno, M.; Schilling, M. P.; Reischl, M.; Mikut, R.
2023. 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 5 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISBI53787.2023.10230659

Automating day-ahead forecasting of photovoltaic power generation: Model design, monitoring, and adaption
Meisenbacher, S.; Martin, T.; Heidrich, B.; Mikut, R.; Hagenmeyer, V.
2023. ETG Congress 2023, Kassel, Germany, 25-26 May 2023, 83–90, VDE Verlag

Fast Whitespace Correction with Encoder-Only Transformers
Bast, H.; Hertel, M.; Walter, S.
2023. The 61st Annual Meeting of the Association for Computational Linguistics: System Demonstrations : ACL-DEMO 2023. Vol 3: Proceedings of the System Demonstrations, 389–399, Association for Computational Linguistics (ACL). doi:10.18653/v1/2023.acl-demo.37

Dissolved ozone sensing in water and blood based on commercial screen-printed and BDD electrodes
Petani, L.; Llupa, L.; Peng, Z.; Ogata, G.; Koker, L.; Gengenbach, U.; Einaga, Y.; Pylatiuk, C.
2023. IEEE Biomedical Circuits ans Systems Conference (BioCAS), Institute of Electrical and Electronics Engineers (IEEE)

A Real-Time PHIL Implementation of a Novel Nonlinear Distributed Control Strategy for a Multi-Terminal DC Microgrid
Ekin, Ö.; Perez, F.; Damm, G.; Hagenmeyer, V.
2023. 2023 IEEE Belgrade PowerTech, Belgrade, Serbia, 25-29 June 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PowerTech55446.2023.10202843

Dynamic Chromosome Interpretation in Evolutionary Algorithms for Distributed Energy Resources Scheduling
Poppenborg, R.; Phipps, K.; Khalloof, H.; Förderer, K.; Mikut, R.; Hagenmeyer, V.
2023. GECCO ’23 Companion: Companion Conference on Genetic and Evolutionary Computation Lisbon Portugal July 15 - 19, 2023. Ed.: S. Silva, 755–758, Association for Computing Machinery (ACM). doi:10.1145/3583133.3590666

From Stationary to Flexible Plant Operation: Extension of a Co-Current Rotary Dryer Model for Energy Demand Flexibility
Schaßberger, J.; Hagenmeyer, V.; Gröll, L.
2023. International Conference on Process Control 2023

Optimised inkjet-printing parameters and processing techniques for an exemplary structure of an oxygen sensor on a Polyimide substrate
Petani, L.; Schweizer, A.; Pylatiuk, C.; Stiller, P.; Gengenbach, U.; Ungerer, M.
2023. 2023 IEEE International Conference on Flexible and Printable Sensors and Systems (FLEPS), Boston, MA, USA, 09-12 July 2023, 1–4, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/FLEPS57599.2023.10220420

A Shapley value-based Distributed AC OPF Approach for Redispatch Congestion Cost Allocation
Bauer, R.; Dai, X.; Hagenmeyer, V.
2023. e-Energy ’23: Proceedings of the 14th ACM International Conference on Future Energy Systems, 109 – 113, Association for Computing Machinery (ACM). doi:10.1145/3575813.3576881

Position Analysis of the Atomiser Unit of an Aerosol-on-Demand Jet-Printhead by means of Computational Fluid Dynamics
Ungerer, M.; Walter, T.; Sieber, I.
2023. Proceedings of the 13th International Conference on Simulation and Modeling Methodologies, Technologies and Applications - SIMULTECH Volume 1, 126–133, SciTePress. doi:10.5220/0012131000003546

The Impact of Local Energy Market Participants’ Decisions on Efficient Energy Usage: Design of a Multi-Agent System
Speck, C.; Bluhm, S.; Weinhardt, C.; Zwickel, P.; Hagenmeyer, V.
2023. 2023 19th International Conference on the European Energy Market (EEM), Lappeenranta, Finland, 06-08 June 2023, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM58374.2023.10161771

An Efficient Greedy Algorithm for Real-World Large-Scale Electric Vehicle Charging
Hegele, M.; Metzler, P.; Beichter, S.; Wiegel, F.; Hagenmeyer, V.
2023. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 415–426, Association for Computing Machinery (ACM). doi:10.1145/3575813.3597349

A new Data-Driven Approach for Comparative Assessment of Baseline Load Profiles Supporting the Planning of Future Charging Infrastructure
Galenzowski, J.; Waczowicz, S.; Hagenmeyer, V.
2023. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 8–20, Association for Computing Machinery (ACM). doi:10.1145/3599733.3600245

Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence
Pütz, S.; Kruse, J.; Witthaut, D.; Hagenmeyer, V.; Schäfer, B.
2023. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 26–31, Association for Computing Machinery (ACM). doi:10.1145/3599733.3600247

The Impact of Forecast Characteristics on the Forecast Value for the Dispatchable Feeder
Werling, D.; Beichter, M.; Heidrich, B.; Phipps, K.; Mikut, R.; Hagenmeyer, V.
2023. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 59–71, Association for Computing Machinery (ACM). doi:10.1145/3599733.3600251

Loss-Customised Probabilistic Energy Time Series Forecasts Using Automated Hyperparameter Optimisation
Phipps, K.; Meisenbacher, S.; Heidrich, B.; Turowski, M.; Mikut, R.; Hagenmeyer, V.
2023. Proceedings of the 14th ACM International Conference on Future Energy Systems, 271–286, Association for Computing Machinery (ACM). doi:10.1145/3575813.3595204

Direct Window-to-Wall Ratio Prediction Using Deep Learning Approaches
Zhuo, X.; Tian, J.; Häfele, K.-H.
2023. 2023 Joint Urban Remote Sensing Event (JURSE), 1–4, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/JURSE57346.2023.10144162

AutoPV: Automated photovoltaic forecasts with limited information using an ensemble of pre-trained models
Meisenbacher, S.; Heidrich, B.; Martin, T.; Mikut, R.; Hagenmeyer, V.
2023. Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy 2023), 386–414, Association for Computing Machinery (ACM). doi:10.1145/3575813.3597348

Distributed Co-Simulation of Multimodal Energy Systems using eASiMOV : Tutorial 5
Süß, A.-C.; Kovacevic, J.; Cakmak, H.; Hagenmeyer, V.
2023. 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES), Institute of Electrical and Electronics Engineers (IEEE)

PyAPI-RTS: A Python-API for RSCAD Modeling
Weber, M.; Enzinger, J.; Çakmak, H. K.; Kühnapfel, U.; Hagenmeyer, V.
2023. 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES), Hrsg.: IEEE, International Workshop on Open Source Modelling and Simulation of Energy Systems (OSMSES 2023), Aachen, Deutschland, 27.03.2023–29.03.2023, 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES58477.2023.10089671

Introducing PROOF - A PROcess Orchestration Framework for the Automation of Computational Scientific Workflows and Co-Simulations
Liu, J.; Chlosta, M.; Schaber, N.; Sidler, J.; Lutz, R.; Schlachter, T.; Hagenmeyer, V.
2023. 2023 Open Source Modelling and Simulation of Energy Systems (OSMSES), Hrsg.: IEEE, International Workshop on Open Source Modelling and Simulation of Energy Systems (OSMSES 2023) Aachen, Deutschland, 27.03.2023–29.03.2023, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES58477.2023.10089680

Simulation in Additive Manufacturing and Its Implications for Sustainable Manufacturing in the Era of Industry 4.0
Charles, A.; Bayat, M.; Elkaseer, A.; Scholz, S.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing (SDM 2022). Ed.: S. Scholz, 370–377, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_36

Multi-parameter Analysis for High-Precision Inkjet Printing
Elkaseer, A.; Kuchta, M.; Rees, A.; Scholz, S. G.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing (SDM 2022). Ed.: S. Scholz, 378–387, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_37

Introduction and Evaluation of a Project Management Software Tool in the Context of the Administration of Science and Research Projects
Lauth, E.; Scholz, S. G.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing (SDM 2022). Ed.: S. Scholz, 11–20, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_2

Impact of Additive Manufacturing on Supply Chains
Lauth, E.; Scholz, S. G.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing (SDM 2022). Ed.: S. Scholz, 1–10, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_1

Digital, Scalable Manufacturing - A Sustainable Production Scenario Using Collaborative Robotics and Additive Manufacturing
Müller, T.; Schmidt, A.; Scholz, S.; Hagenmeyer, V.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing (SDM 2022). Ed.: S. Scholz, 262–271, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_25

Investigation of a simplified photometer design for the measurement of ozone gas concentration
Petani, L.; Barth, R.; Wührl, L.; Sieber, I.; Koker, L.; Reischl, M.; Gengenbach, U.; Pylatiuk, C.
2023. 2022 IEEE-EMBS Conference on Biomedical Engineering and Sciences (IECBES), 94–99, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IECBES54088.2022.10079356

Assessing the combination of differential flatness and deterministic automata for controllable hybrid systems
Zahn, F.; Kleinert, T.; Hagenmeyer, V.
2023. 2022 IEEE 61st Conference on Decision and Control (CDC), 2612–2619, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC51059.2022.9993043

Multi-Day Stochastic Scheduling of Electric Vehicle Charging for Reliability and Convenience
Schwenk, K.; Hagenmeyer, V.; Mikut, R.
2023. IEEE Vehicle Power and Propulsion Conference (VPPC), Merced, California, USA, 1st - 4th November 2022, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/VPPC55846.2022.10003402

Precise Energy Consumption Measurements of Heterogeneous Artificial Intelligence Workloads
Caspart, R.; Ziegler, S.; Weyrauch, A.; Obermaier, H.; Raffeiner, S.; Schuhmacher, L. P.; Scholtyssek, J.; Trofimova, D.; Nolden, M.; Reinartz, I.; Isensee, F.; Götz, M.; Debus, C.
2023. High Performance Computing. ISC High Performance 2022 International Workshops – Hamburg, Germany, May 29 – June 2, 2022, Revised Selected Papers. Ed.: H. Anzt, 108–121, Springer International Publishing. doi:10.1007/978-3-031-23220-6_8

Development of a Database for the Management and Use of Available Resources in the Field of Sustainable Nanomanufacturing
Marquardt, C.; Scholz, S. G.; Nau, K.; Schmidt, A.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing, SDM 2022, 14th - 16th September 2022. Ed.: S. Scholz, 232–241, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_22

An Approach for Sustainable Knowledge Management and Policy Upstreaming for Industry4.0 in Central Europe
Marquardt, C.; Charles, A. P.; Scholz, S. G.
2023. Sustainable Design and Manufacturing – Proceedings of the 9th International Conference on Sustainable Design and Manufacturing, SDM 2022, 14th - 16th September 2022. Ed.: S. Scholz, 242–251, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_23

Knowledge Base Materials Sustainable Science Communication on Advanced Materials
Nau, K.; Espinoza, S.; Krug, H. F.; Marquardt, C.; Mattern, A.; Möller, N.; Steinbach, C.; Kühnel, D.
2023. Sustainable Design and Manufacturing. Ed.: S. G. Scholz, 33–42, Springer Nature Singapore. doi:10.1007/978-981-19-9205-6_4

Umweltinformationen digital 4.0 - Analyse moderner Technologien für die Erfassung, Haltung und Weitergabe von Umweltdaten
Hahn-Woernle, L.; Schillinger, W.; Schlachter, T.; Doms, N.; Trefzger, M.; Schlegel, T.; Wolf, A.; Preiß, A.
2023. Umweltinformationssysteme – Vielfalt, Offenheit, Komplexität : Tagungsband des 29. Workshops “Umweltinformationssysteme (UIS 2022)“ des Arbeitskreises „Umweltinformationssysteme“ der Fachgruppe „Informatik im Umweltschutz‘‘ der Gesellschaft für Informatik (GI). Hrsg.: F. Fuchs-Kittowski, Springer Vieweg

Abstractband DOG 2023
Deutsche Ophthalmologische Gesellschaft e.V. (Ed.)
2023. Springer Medizin. doi:10.1007/s00347-023-01901-w

Proceedings - 33. Workshop Computational Intelligence: Berlin, 23.-24. November 2023
Schulte, H.; Hoffmann, F.; Mikut, R. (Eds.)
2023. doi:10.5445/KSP/1000162754

CFC – Carbon Fibre Cycle Carbonfasern im Kreislauf – Freisetzungsverhalten und Toxizität bei thermischer und mechanischer Behandlung
Baumann, W.; Bäger, D.; Deußen, O.; Diabaté, S.; Ellermann, N.; Emmerich, R.; Friesen, A.; Fritsch-Decker, S.; Gehrmann, H. J.; Gries, T.; Große, A.; Guth, J.; Hartwig, A.; Hauser, M.; Hofmann, M.; Hufnagel, M.; Kehren, D.; Krug, H. F.; Kühnel, D.; Leis, J.; Mahl, J.; Marquardt, C.; Mattern, A.; Merz, D.; Möller, N.; Nau, K.; Naumann, R.; Plitzko, S.; Schlögel, K.; Stapf, D.; Steinbach, C.; Weiss, C.; Wexler, M.
2023

A large and diverse brain organoid dataset of 1,400 cross-laboratory images of 64 trackable brain organoids from four different clones
Schröter, J.; Deininger, L.; Richter, P.; Syrbe, S.; Lupse, B.; Mikut, R.; Jung-Klawitter, S.
2023. doi:10.5281/zenodo.10301912

On Evasion of Machine Learning-based Intrusion Detection in Smart Grids
Mumrez, A.; Sánchez, G.; Elbez, G.; Hagenmeyer, V.
2023, October 31

Dataset for the Segmentation of Industrial Burner Flames
Landgraf, S.; Hillemann, M.; Ulrich, M.; Aberle, M.; Jung, V.
2023, June 20. doi:10.5445/IR/1000159497

sktime - python toolbox for time series: new features 2023 – advanced pipelines, probabilistic forecasting, parallelism support, composable classifiers and distances, reproducibility features
Kiraly, F.; Ray, A.; Heidrich, B.
2023

Introduction to eASiMOV-eCoSim
Kovacevic, J.; Süß, A.-C.; Çakmak, H. K.; Hagenmeyer, V.
2023. doi:10.5445/IR/1000159679

Large Volume Reconstruction of Pyrolyzed Origami Cellulose Structure by Automated Section Acquisition for Array Tomography
Hoffmann, J.; Huang, L.
2023. doi:10.5445/IR/1000154756

Demonstration video of the automated section acquisition for Array Tomography
Hoffmann, J.; Huang, L.
2023. doi:10.5445/IR/1000154722

Energiesysteme zukunftssicher gestalten: Resilienz & Nachhaltigkeit & Partizipation als Treiber für technologische und gesellschaftliche Innovationen
Hanselka, H.; Ottenburger, S. S.; Raskob, W.; Bao, K.; Rösch, C.
2022. Resilienz – Innovationen – Wachstum: Energie für die postpandemische Zeit, 42–54, Forum für Zukunftsenergien e.V

Scale aware modeling and monitoring of the urban energy chain. PhD dissertation
Nichersu, A.
2022, August 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000149384

A Smart Charging Assistant for Electric Vehicles Considering Battery Degradation, Power Grid and User Constraints. PhD dissertation
Schwenk, K.
2022, July 7. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000148141

Simulation optomechanischer Wirkzusammenhänge am Beispiel eines Head-Up-Displays und deren experimentelle Verifizierung. PhD dissertation
Markisch, S.
2022, June 9. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000147722

On the Detection of Cyber-Attacks in the Communication Network of IEC 61850 Electrical Substations. PhD dissertation
Elbez, G.
2022, May 30. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000146668

Distributed Optimization with Application to Power Systems and Control. PhD dissertation
Engelmann, A.
2022. KIT Scientific Publishing. doi:10.5445/KSP/1000144792

An adaptive filtering algorithm in pulse-Doppler radar for counteracting range-velocity jamming
Abdalla, A.; Ramadan, M.; Liao, Y.; Zhou, S.
2022. International Journal of Electronics, 109 (10), 1695–1713. doi:10.1080/00207217.2021.2001850

Some Notes on Two Tests for Stability in Lossy Power Systems
Gröll, L.; Kastner, A.; Scholl, T. H.; Hagenmeyer, V.
2022. IFAC-PapersOnLine, 55 (40), 247–252. doi:10.1016/j.ifacol.2023.01.080

Robotic systems for decontamination in hazardous environments : To boldly go where many still work today
Petereit, J.; Bretthauer, G.; Beyerer, J.
2022. at - Automatisierungstechnik, 70 (10), 823–825. doi:10.1515/auto-2022-0121

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN
Zhai, J.; Dai, X.; Jiang, Y.; Xue, Y.; Hagenmeyer, V.; Jones, C. N.; Zhang, X.-P.
2022. IEEE Transactions on Power Systems, 37 (6), 4861–4873. doi:10.1109/TPWRS.2022.3155866

Abstractband DOG 2022; Utilizing static corneal landmarks to assess dynamic corneal nerve changes by in vivo large-area confocal microscopy
Bohn, S.; Stache, N.; Sterenczak, K. A.; Sperlich, K.; Allgeier, S.; Köhler, B.; Mikut, R.; Bartschat, A.; Reichert, K.-M.; Guthoff, R., F.; Stachs, O.
2022. Die Ophthalmologie, 119 (S3), 157–344. doi:10.1007/s00347-022-01723-2

Initial analysis of the impact of the Ukrainian power grid synchronization with Continental Europe
Böttcher, P. C.; Rydin Gorjão, L.; Beck, C.; Jumar, R.; Maass, H.; Hagenmeyer, V.; Witthaut, D.; Schäfer, B.
2022. Energy Advances, 2 (1), 91–97. doi:10.1039/D2YA00150K

microbeSEG: A deep learning software tool with OMERO data management for efficient and accurate cell segmentation
Scherr, T.; Seiffarth, J.; Wollenhaupt, B.; Neumann, O.; Schilling, M. P.; Kohlheyer, D.; Scharr, H.; Nöh, K.; Mikut, R.
2022. (A. Imran, Ed.) PLOS ONE, 17 (11), Art.-Nr.: e0277601. doi:10.1371/journal.pone.0277601

Hardware-in-the-loop platforms for the automation and control of future energy systems
Bretschneider, P.; Mikut, R.; Hagenmeyer, V.
2022. at - Automatisierungstechnik, 70 (12), 1031–1033. doi:10.1515/auto-2022-0145

An adapter-based architecture for evaluating candidate solutions in energy system scheduling
Chlosta, M.; Liu, J.; Poppenborg, R.; Lutz, R.; Förderer, K.; Schlachter, T.; Hagenmeyer, V.
2022. Energy Informatics, 5 (S4), 56. doi:10.1186/s42162-022-00246-z

A comparison of clustering methods for the spatial reduction of renewable electricity optimisation models of Europe
Frysztacki, M. M.; Recht, G.; Brown, T.
2022. Energy Informatics, 5 (1), Art.-Nr.: 4. doi:10.1186/s42162-022-00187-7

Two- and Three-Dimensional Benchmarks for Particle Detection from an Industrial Rotary Kiln Combustion Chamber Based on Light-Field-Camera Recording
Vogelbacher, M.; Zhang, M.; Aleksandrov, K.; Gehrmann, H.-J.; Matthes, J.
2022. Data, 7 (12), 179. doi:10.3390/data7120179

Editorial: Methods and protocols in nanotoxicology
Krug, H. F.; Nau, K.
2022. Frontiers in Toxicology, 4, Art.Nr. 1093765. doi:10.3389/ftox.2022.1093765

Smart Energy System Control Laboratory : a fully-automated and user-oriented research infrastructure for controlling and operating smart energy systems = Smart Energy System Control Laboratory : hochgradig automatisierte und nutzerorientierte Forschungsinfrastruktur zur Steuerung und zum Betrieb intelligenter Energiesysteme
Wiegel, F.; Wachter, J.; Kyesswa, M.; Mikut, R.; Waczowicz, S.; Hagenmeyer, V.
2022. at - Automatisierungstechnik, 70 (12), 1116–1133. doi:10.1515/auto-2022-0018

Characterization of the pace-and-drive capacity of the human sinoatrial node: A 3D in silico study
Amsaleg, A.; Sánchez, J.; Mikut, R.; Loewe, A.
2022. Biophysical Journal, 121 (22), 4247–4259. doi:10.1016/j.bpj.2022.10.020

Utilizing static corneal landmarks to assess dynamic corneal nerve changes by in vivo large-area confocal microscopy
Bohn, S.; Stache, N.; Sterenczak, K. A.; Sperlich, K.; Allgeier, S.; Köhler, B.; Mikut, R.; Bartschat, A.; Reichert, K.-M.; Guthoff, R. F.; Stachs, O.
2022. Der Ophthalmologe, 119 (Suppl 3), 170

Material jetting for advanced applications: A state-of-the-art review, gaps and future directions
Elkaseer, A.; Chen, K. J.; Janhsen, J. C.; Refle, O.; Hagenmeyer, V.; Scholz, S. G.
2022. Additive Manufacturing, 60 (Part A), Art.-Nr.: 103270. doi:10.1016/j.addma.2022.103270

3D Refuse-derived Fuel Particle Tracking-by-Detection Using a Plenoptic Camera System
Zhang, M.; Vogelbacher, M.; Hagenmeyer, V.; Aleksandrov, K.; Gehrmann, H.-J.; Matthes, J.
2022. IEEE Transactions on Instrumentation and Measurement, 71, Art.Nr. 5024815. doi:10.1109/TIM.2022.3217858

A Highspeed‐Camera Based Measurement System for the High‐Pressure Entrained‐Flow Gasification
Matthes, J.; Kollmer, M.; Eberhard, M.; Hagenmeyer, V.; Kolb, T.
2022. Chemical Engineering & Technology, 45 (12), 2313–2322. doi:10.1002/ceat.202200434

Transformation-optics modeling of 3D-printed freeform waveguides
Nesic, A.; Blaicher, M.; Orlandini, E.; Olariu, T.; Paszkiewicz, M.; Negredo, F.; Kraft, P.; Sukhova, M.; Hofmann, A.; Dörfler, W.; Rockstuhl, C.; Freude, W.; Koos, C.
2022. Optics Express, 30 (21), 38856–38879. doi:10.1364/OE.452243

Modularer Baukasten für die Erstellung anwendungsspezifischer Greiffinger: Greiferfinger für eine schnelle Rekonfiguration
Friedmann, M.; Schabel, S.; Gerber, J.; Döhring, A.; Meschter, L.; Fleischer, J.; May, M.
2022. wt Werkstattstechnik online, 112 (09), 629–634. doi:10.37544/1436-4980-2022-09-101

Mosaic vs. Single Image Analysis with Confocal Microscopy of the Corneal Nerve Plexus for Diagnosis of Early Diabetic Peripheral Neuropathy
Matuszewska-Iwanicka, A.; Stratmann, B.; Stachs, O.; Allgeier, S.; Bartschat, A.; Winter, K.; Guthoff, R.; Tschoepe, D.; Hettlich, H.-J.
2022. Ophthalmology and Therapy, 11 (6), 2211–2223. doi:10.1007/s40123-022-00574-z

Quantitative downhill skiing technique analysis according to ski instruction curricula: A proof-of-concept study applying principal component analysis on wearable sensor data
Debertin, D.; Wachholz, F.; Mikut, R.; Federolf, P.
2022. Frontiers in Bioengineering and Biotechnology, 10, Art.Nr. 1003619. doi:10.3389/fbioe.2022.1003619

Realizing FAIR Digital Objects for the German Helmholtz Association of Research Centres
Jejkal, T.; Pfeil, A.; Schweikert, J.; Pirogov, A.; Barranco, P.; Krebs, F.; Koch, C.; Guenther, G.; Curdt, C.; Weinelt, M.
2022. Research Ideas and Outcomes, 8, Art.Nr. e94758. doi:10.3897/rio.8.e94758

Implementation of a Photovoltaic System Model Using FAIR Digital Objects
Schweikert, J.; Stucky, K.-U.; Koubaa, M. A.; Süß, W.; Hagenmeyer, V.
2022. Research Ideas and Outcomes, 8, Art.-nr.: e93929. doi:10.3897/rio.8.e93929

Understanding Braess’ Paradox in power grids
Schäfer, B.; Pesch, T.; Manik, D.; Gollenstede, J.; Lin, G.; Beck, H.-P.; Witthaut, D.; Timme, M.
2022. Nature Communications, 13 (1), Art.-Nr.: 5396. doi:10.1038/s41467-022-32917-6

Rapid Scalable Distributed Power Flow with Open-Source Implementation
Dai, X.; Cai, Y.; Jiang, Y.; Hagenmeyer, V.
2022. IFAC-PapersOnLine, 55 (13), 145–150. doi:10.1016/j.ifacol.2022.07.250

Gas-tight means zero defects - design considerations for thin-walled fluidic devices with overhangs by laser powder bed fusion
Grinschek, F.; Charles, A.; Elkaseer, A.; Klahn, C.; Scholz, S. G.; Dittmeyer, R.
2022. Materials & Design, 223, 111174. doi:10.1016/j.matdes.2022.111174

Inferring Topology of Networks With Hidden Dynamic Variables
Schmidt, R.; Haehne, H.; Hillmann, L.; Casadiego, J.; Witthaut, D.; Schafer, B.; Timme, M.
2022. IEEE Access, 10, 76682–76692. doi:10.1109/ACCESS.2022.3191665

Non-Invasive Data Acquisition and IoT Solution for Human Vital Signs Monitoring: Applications, Limitations and Future Prospects
Salem, M.; Elkaseer, A.; El-Maddah, I. A. M.; Youssef, K. Y.; Scholz, S. G.; Mohamed, H. K.
2022. Sensors, 22 (17), Art.Nr. 6625. doi:10.3390/s22176625

Automated Zebrafish Phenotype Pattern Recognition: 6 Years Ago, and Now
Schutera, M.; Rettenberger, L.; Reischl, M.
2022. Zebrafish, 19 (6), 213–217. doi:10.1089/zeb.2022.0027

Boost short-term load forecasts with synthetic data from transferred latent space information
Heidrich, B.; Mannsperger, L.; Turowski, M.; Phipps, K.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2022. Energy Informatics, 5 (S1), Article no: 20. doi:10.1186/s42162-022-00214-7

Net load forecasting using different aggregation levels
Beichter, M.; Phipps, K.; Frysztacki, M. M.; Mikut, R.; Hagenmeyer, V.; Ludwig, N.
2022. Energy Informatics, 5 (S1), Article no: 19. doi:10.1186/s42162-022-00213-8

EmbedTrack—Simultaneous Cell Segmentation and Tracking Through Learning Offsets and Clustering Bandwidths
Löffler, K.; Mikut, R.
2022. IEEE Access, 10, 77147–77157. doi:10.1109/ACCESS.2022.3192880

Normics: Proteomic Normalization by Variance and Data-Inherent Correlation Structure
Dressler, F. F.; Brägelmann, J.; Reischl, M.; Perner, S.
2022. Molecular & Cellular Proteomics, 21 (9), Article no: 100269. doi:10.1016/j.mcpro.2022.100269

Prediction of Fluorescent Ki67 Staining in 3D Tumor Spheroids
Bruch, R.; Vitacolonna, M.; Rudolf, R.; Reischl, M.
2022. Current Directions in Biomedical Engineering, 8 (2), 305–308. doi:10.1515/cdbme-2022-1078

Annotation Efforts in Image Segmentation can be Reduced by Neural Network Bootstrapping
Rettenberger, L.; Schilling, M.; Reischl, M.
2022. Current Directions in Biomedical Engineering, 8 (2), 329–332. doi:10.1515/cdbme-2022-1084

Impact of Annotation Noise on Histopathology Nucleus Segmentation
Schilling, M. P.; Ahuja, N.; Rettenberger, L.; Scherr, T.; Reischl, M.
2022. Current Directions in Biomedical Engineering, 8 (2), 197–200. doi:10.1515/cdbme-2022-1051

KaIDA: a modular tool for assisting image annotation in deep learning
Schilling, M. P.; Schmelzer, S.; Klinger, L.; Reischl, M.
2022. Journal of Integrative Bioinformatics, 19 (4), Art.-Nr.: 20220018. doi:10.1515/jib-2022-0018

Data-driven load profiles and the dynamics of residential electricity consumption
Anvari, M.; Proedrou, E.; Schäfer, B.; Beck, C.; Kantz, H.; Timme, M.
2022. Nature Communications, 13 (1), Art.-Nr.: 4593. doi:10.1038/s41467-022-31942-9

Effect of Process Parameters on the Performance of Drop-On-Demand 3D Inkjet Printing: Geometrical-Based Modeling and Experimental Validation
Elkaseer, A.; Schneider, S.; Deng, Y.; Scholz, S. G.
2022. Polymers, 14 (13), Art.-Nr.: 2557. doi:10.3390/polym14132557

Droplet Microarray Based Screening Identifies Proteins for Maintaining Pluripotency of hiPSCs
Liu, Y.; Bertels, S.; Reischl, M.; Peravali, R.; Bastmeyer, M.; Popova, A. A.; Levkin, P. A.
2022. Advanced Healthcare Materials, 11 (18), Art.-Nr.: 2200718. doi:10.1002/adhm.202200718

Review of automated time series forecasting pipelines
Meisenbacher, S.; Turowski, M.; Phipps, K.; Rätz, M.; Müller, D.; Hagenmeyer, V.; Mikut, R.
2022. WIREs Data Mining and Knowledge Discovery, 12 (6), Art.Nr. e1475. doi:10.1002/widm.1475

Entwicklung und Evaluation eines Simulators für die endoskopische Nasennebenhöhlenoperation
Pößneck, A.; Ludwig, A. A.; Burgert, O.; Nowatius, E.; Maaß, H.; Çakmak, H.; Dietz, A.
2022. Laryngo-Rhino-Otologie, 101 (10), 805–813. doi:10.1055/a-1841-6328

A Mode-Based Averaged Power Converter Model for Large Transients
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2022. IFAC-PapersOnLine, 10th Vienna International Conference on Mathematical Modelling MATHMOD 2022, Vienna Austria, 27–29 July 2022, Ed.: A. Kugi, 55 (20), 367–372. doi:10.1016/j.ifacol.2022.09.122

Validation Methods for Energy Time Series Scenarios From Deep Generative Models
Cramer, E.; Gorjao, L. R.; Mitsos, A.; Schafer, B.; Witthaut, D.; Dahmen, M.
2022. IEEE Access, 10, 8194–8207. doi:10.1109/ACCESS.2022.3141875

Secondary frequency control stabilising voltage dynamics
Tchuisseu, E. B. T.; Dongmo, E.-D.; Procházka, P.; Woafo, P.; Colet, P.; Schäfer, B.
2022. European Journal of Applied Mathematics, 34 (3), 467–483. doi:10.1017/S095679252100036X

Phase and Amplitude Synchronization in Power-Grid Frequency Fluctuations in the Nordic Grid
Rydin Gorjao, L.; Vanfretti, L.; Witthaut, D.; Beck, C.; Schäfer, B.
2022. IEEE Access, 10, 18065–18073. doi:10.1109/ACCESS.2022.3150338

Spatial heterogeneity of air pollution statistics in Europe
He, H.; Schäfer, B.; Beck, C.
2022. Scientific Reports, 12 (1), Artikel-Nr.: 12215. doi:10.1038/s41598-022-16109-2

Machine learning approach towards explaining water quality dynamics in an urbanised river
Schäfer, B.; Beck, C.; Rhys, H.; Soteriou, H.; Jennings, P.; Beechey, A.; Heppell, C. M.
2022. Scientific Reports, 12 (1), Art.-Nr.: 12346. doi:10.1038/s41598-022-16342-9

Secondary control activation analysed and predicted with explainable AI
Kruse, J.; Schäfer, B.; Witthaut, D.
2022. Electric Power Systems Research, 212, Art.-Nr.: 108489. doi:10.1016/j.epsr.2022.108489

Droplet Microarray as a Powerful Platform for Seeking New Antibiotics Against Multidrug‐Resistant Bacteria
Lei, W.; Deckers, A.; Luchena, C.; Popova, A.; Reischl, M.; Jung, N.; Bräse, S.; Schwartz, T.; Krimmelbein, I. K.; Tietze, L. F.; Levkin, P. A.
2022. Advanced Biology, 6 (12), Art.-Nr.: 2200166. doi:10.1002/adbi.202200166

In silico identification of two peptides with antibacterial activity against multidrug-resistant Staphylococcus aureus
Oyama, L. B.; Olleik, H.; Teixeira, A. C. N.; Guidini, M. M.; Pickup, J. A.; Hui, B. Y. P.; Vidal, N.; Cookson, A. R.; Vallin, H.; Wilkinson, T.; Bazzolli, D. M. S.; Richards, J.; Wootton, M.; Mikut, R.; Hilpert, K.; Maresca, M.; Perrier, J.; Hess, M.; Mantovani, H. C.; Fernandez-Fuentes, N.; Creevey, C. J.; Huws, S. A.
2022. npj Biofilms and Microbiomes, 8 (1), Artikel-Nr.: 58. doi:10.1038/s41522-022-00320-0

Herrn Prof. Dr.-Ing. Frank Allgöwer zum 60. Geburtstag
Bretthauer, G.
2022. at - Automatisierungstechnik, 70 (6), 599–600. doi:10.1515/auto-2022-0067

Prof. Dr.-Ing. habil. Jan Lunze zum 70. Geburtstag
Bretthauer, G.
2022. at - Automatisierungstechnik, 70 (1), 102–104. doi:10.1515/auto-2021-0173

Part Tailoring in Metal-Additive Manufacturing: A Step towards Functionally Graded Customized Stainless-Steel Components Using Laser Powder Bed Fusion
Elkaseer, A.; Charles, A.; Schneider, S.; Scholz, S. G.
2022. Applied Sciences, 12 (12), Art.Nr. 6193. doi:10.3390/app12126193

Assessment of dynamic corneal nerve changes using static landmarks by in vivo large-area confocal microscopy—a longitudinal proof-of-concept study
Stache, N.; Sterenczak, K. A.; Sperlich, K.; Marfurt, C. F.; Allgeier, S.; Köhler, B.; Mikut, R.; Bartschat, A.; Reichert, K.-M.; Guthoff, R. F.; Stachs, A.; Stachs, O.; Bohn, S.
2022. Quantitative Imaging in Medicine and Surgery, 12 (10), 4734–4746. doi:10.21037/qims-22-15

Speed of technological transformations required in Europe to achieve different climate goals
Victoria, M.; Zeyen, E.; Brown, T.
2022. Joule, 6 (5), 1066–1086. doi:10.1016/j.joule.2022.04.016

Herrn Prof. Henning Tolle zum 90. Geburtstag
Adamy, J.; Bretthauer, G.
2022. at - Automatisierungstechnik, 70 (5), 498–500. doi:10.1515/auto-2022-0055

Wandlungsfähige Produktion für die Kreislaufwirtschaft
Beyerer, J.; Bretthauer, G.; Hofmann, C.; Lanza, G.
2022. at - Automatisierungstechnik, 70 (6), 501–503. doi:10.1515/auto-2022-0063

Prof. Dr.-Ing. Jürgen Adamy zum 60. Geburtstag
Bretthauer, G.; Willert, V.
2022. at - Automatisierungstechnik, 70 (3), 312–314. doi:10.1515/auto-2022-0017

A guideline to document occupant behavior models for advanced building controls
Dong, B.; Markovic, R.; Carlucci, S.; Liu, Y.; Wagner, A.; Liguori, A.; van Treeck, C.; Oleynikov, D.; Azar, E.; Fajilla, G.; Drgoňa, J.; Kim, J.; Vellei, M.; De Simone, M.; Shamsaiee, M.; Bavaresco, M.; Favero, M.; Kjaergaard, M.; Osman, M.; Frahm, M.; Dabirian, S.; Yan, D.; Kang, X.
2022. Building and Environment, 219, Art.-Nr.: 109195. doi:10.1016/j.buildenv.2022.109195

Multiobjective Optimization of Laser Polishing of Additively Manufactured Ti-6Al-4V Parts for Minimum Surface Roughness and Heat-Affected Zone
Solheid, J. S.; Elkaseer, A.; Wunsch, T.; Scholz, S.; Seifert, H. J.; Pfleging, W.
2022. Materials, 15 (9), Art.Nr. 3323. doi:10.3390/ma15093323

Binary Exploitation in Industrial Control Systems: Past, Present and Future
Liu, Q.; Bao, K.; Hagenmeyer, V.
2022. IEEE Access, 10, 48242–48273. doi:10.1109/ACCESS.2022.3171922

A Holistic Consideration of Megawatt Electrolysis as a Key Component of Sector Coupling
Emonts, B.; Müller, M.; Hehemann, M.; Janßen, H.; Keller, R.; Stähler, M.; Stähler, A.; Hagenmeyer, V.; Dittmeyer, R.; Pfeifer, P.; Waczowicz, S.; Rubin, M.; Munzke, N.; Kasselmann, S.
2022. Energies, 15 (10), 3656. doi:10.3390/en15103656

Material matters: predicting the core hardness variance in industrialized case hardening of 18CrNi8 [Vorhersage der Kernhärtenvarianz von industriell einsatzgehärtetem 18CrNi8]
Lingelbach, Y.; Waldenmaier, T.; Hagymasi, L.; Mikut, R.; Schulze, V.
2022. Materialwissenschaft und Werkstofftechnik, 53 (5), 576–589. doi:10.1002/mawe.202100249

In vivo monitoring of corneal dendritic cells in the subbasal nerve plexus during Trastuzumab and Paclitaxel breast cancer therapy - a one-year follow-up
Bohn, S.; Stache, N.; Sperlich, K.; Allgeier, S.; Köhler, B.; Bartschat, A.; Do, H.-V.; George, C.; Guthoff, R. F.; Stachs, A.; Stachs, O.; Sterenczak, K. A.
2022. Diagnostics, 12 (5), 1180. doi:10.3390/diagnostics12051180

Assessments of linear power flow and transmission loss approximations in coordinated capacity expansion problems
Neumann, F.; Hagenmeyer, V.; Brown, T.
2022. Applied Energy, 314, Art.-Nr.: 118859. doi:10.1016/j.apenergy.2022.118859

Evaluating ensemble post‐processing for wind power forecasts
Phipps, K.; Lerch, S.; Andersson, M.; Mikut, R.; Hagenmeyer, V.; Ludwig, N.
2022. Wind Energy, 25 (8), 1379–1405. doi:10.1002/we.2736

A framework for participation of prosumers in peer-to-peer energy trading and flexibility markets
Khorasany, M.; Shokri Gazafroudi, A.; Razzaghi, R.; Morstyn, T.; Shafie-khah, M.
2022. Applied Energy, 314, Art.-Nr.: 118907. doi:10.1016/j.apenergy.2022.118907

Design and experimental setup of a new concept of an aerosol-on-demand print head
Sieber, I.; Zeltner, D.; Ungerer, M.; Wenka, A.; Walter, T.; Gengenbach, U.
2022. Aerosol Science and Technology, 56 (4), 355–366. doi:10.1080/02786826.2021.2022094

ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles
Quintana, M.; Stoeckmann, T.; Park, J. Y.; Turowski, M.; Hagenmeyer, V.; Miller, C.
2022. Energy and Buildings, 265, Art.-Nr.: 112096. doi:10.1016/j.enbuild.2022.112096

An Automated Room Temperature Flip-Chip Mounting Process for Hybrid Printed Electronics
Chen, Z.; Gengenbach, U.; Liu, X.; Scholz, A.; Zimmermann, L.; Aghassi-Hagmann, J.; Koker, L.
2022. Micromachines, 13 (4), 583. doi:10.3390/mi13040583

A Closer Look at Precision Hard Turning of AISI4340: Multi-Objective Optimization for Simultaneous Low Surface Roughness and High Productivity
Abbas, A. T.; Al-Abduljabbar, A. A.; Alnaser, I. A.; Aly, M. F.; Abdelgaliel, I. H.; Elkaseer, A.
2022. Materials, 15 (6), Art.-Nr.: 2106. doi:10.3390/ma15062106

Energy informatics – key elements for tomorrow’s energy system
Schmeck, H.; Monti, A.; Hagenmeyer, V.
2022. Communications of the ACM, 65 (4), 58–63. doi:10.1145/3511666

Improving process monitoring of ultrasonic metal welding using classical machine learning methods and process-informed time series evaluation
Schwarz, E. B.; Bleier, F.; Guenter, F.; Mikut, R.; Bergmann, J. P.
2022. Journal of Manufacturing Processes, 77, 54–62. doi:10.1016/j.jmapro.2022.02.057

A Comparison of Energy-Efficient Seizure Detectors for Implantable Neurostimulation Devices
Manzouri, F.; Zöllin, M.; Schillinger, S.; Dümpelmann, M.; Mikut, R.; Woias, P.; Comella, L. M.; Schulze-Bonhage, A.
2022. Frontiers in Neurology, 12, Article: 703797. doi:10.3389/fneur.2021.703797

“Cells‐to‐cDNA on Chip”: Phenotypic assessment and gene expression analysis from live cells in nanoliter volumes using droplet microarrays
Chakraborty, S.; Luchena, C.; Elton, J. J.; Schilling, M. P.; Reischl, M.; Roux, M.; Levkin, P. A.; Popova, A. A.
2022. Advanced Healthcare Materials, 11 (12), Art.-Nr.: 2102493. doi:10.1002/adhm.202102493

Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding
Zhou, B.; Pychynski, T.; Reischl, M.; Kharlamov, E.; Mikut, R.
2022. Journal of Intelligent Manufacturing, 33, 1139–1163. doi:10.1007/s10845-021-01892-y

Methods for the frugal labeler: Multi-class semantic segmentation on heterogeneous labels
Schutera, M.; Rettenberger, L.; Pylatiuk, C.; Reischl, M.
2022. PLoS ONE, 17 (2), Art.-Nr.: e0263656. doi:10.1371/journal.pone.0263656

Simple assessment of viability in 2D and 3D cell microarrays using single step digital imaging
Popova, A. A.; Reischl, M.; Kazenmaier, D.; Cui, H.; Amberger, T.; Levkin, P. A.
2022. SLAS technology, 27 (1), 44–53. doi:10.1016/j.slast.2021.10.017

Real-time large-area imaging of the corneal subbasal nerve plexus
Allgeier, S.; Bartschat, A.; Bohn, S.; Guthoff, R. F.; Hagenmeyer, V.; Kornelius, L.; Mikut, R.; Reichert, K.-M.; Sperlich, K.; Stache, N.; Stachs, O.; Köhler, B.
2022. Scientific reports, 12, Article no: 2481. doi:10.1038/s41598-022-05983-5

Automated Annotator Variability Inspection for Biomedical Image Segmentation
Schilling, M. P.; Scherr, T.; Munke, F. R.; Neumann, O.; Schutera, M.; Mikut, R.; Reischl, M.
2022. IEEE access, 10, 2753–2765. doi:10.1109/ACCESS.2022.3140378

Genetic Algorithm for the Optimal LiDAR Sensor Configuration on a Vehicle
Berens, F.; Elser, S.; Reischl, M.
2022. IEEE sensors journal, 22 (3), 2735–2743. doi:10.1109/JSEN.2021.3136362

Elucidation of dross formation in laser powder bed fusion at down-facing surfaces : Phenomenon-oriented multiphysics simulation and experimental validation
Charles, A.; Bayat, M.; Elkaseer, A.; Thijs, L.; Hattel, J. H.; Scholz, S.
2022. Additive manufacturing, 50, Article no: 102551. doi:10.1016/j.addma.2021.102551

High-Throughput Data Acquisition Platform for Multi-Larvae Touch-Response Behavior Screening of Zebrafish
Wang, Y.; Kanagaraj, N. K.; Pylatiuk, C.; Mikut, R.; Peravali, R.; Reischl, M.
2022. IEEE Robotics and automation letters, 7 (2), 858–865. doi:10.1109/LRA.2021.3134281

DiversityScanner: Robotic handling of small invertebrates with machine learning methods
Wührl, L.; Pylatiuk, C.; Giersch, M.; Lapp, F.; Rintelen, T.; Balke, M.; Schmidt, S.; Cerretti, P.; Meier, R.
2022. Molecular ecology resources, 22 (4), 1626–1638. doi:10.1111/1755-0998.13567

Information modelling for urban building energy simulation : A taxonomic review
Malhotra, A.; Bischof, J.; Nichersu, A.; Häfele, K.-H.; Exenberger, J.; Sood, D.; Allan, J.; Frisch, J.; Treeck, C. van; O’Donnell, J.; Schweiger, G.
2022. Building and Environment, 208, Article no: 108552. doi:10.1016/j.buildenv.2021.108552

Distributed Control of Charging for Electric Vehicle Fleets Under Dynamic Transformer Ratings
Botkin-Levy, M.; Engelmann, A.; Muhlpfordt, T.; Faulwasser, T.; Almassalkhi, M. R.
2022. IEEE Transactions on Control Systems Technology, 30 (4), 1578–1594. doi:10.1109/TCST.2021.3120494

Topology-based approximations for contingency constraints in power transmission networks
Shokri Gazafroudi, A.; Neumann, F.; Brown, T.
2022. International journal of electrical power & energy systems, 137, Art.-Nr.: 107702. doi:10.1016/j.ijepes.2021.107702

Equilibrium droplet shapes on chemically patterned surfaces: theoretical calculation, phase-field simulation, and experiments
Wu, Y.; Kuzina, M.; Wang, F.; Reischl, M.; Selzer, M.; Nestler, B.; Levkin, P. A.
2022. Journal of Colloid and Interface Science, 606, 1077–1086. doi:10.1016/j.jcis.2021.08.029

Development of an Experimental Setup for Real-Time In-Line Dissolved Ozone Measurement for Medical Therapy
Petani, L.; Wührl, L.; Koker, L.; Reischl, M.; Renz, J.; Gengenbach, U.; Pylatiuk, C.
2022. Ozone science & engineering, 44 (5), 499–509. doi:10.1080/01919512.2021.1932412

Integrated concept of local heat transition using geothermal heat production, aquifer storage and optimization of distribution network
Zwickel, P.; Bauer, F.; Schätzler, K.; Steiner, U.; Waczowicz, S.; Hagenmeyer, V.; Schill, E.
2022. European Geothermal Congress 2022 : Berlin, Germany, 17-21 October 2022 : proceedings, European Geothermal Energy Council (EGEC)

A Look-ahead Towards 6G Security (Abstract)
Ramadan, M.; Raza, S.
2022. 2022 International Conference on Cyberworlds (CW), 259–260, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CW55638.2022.00058

Broadband Jamming Suppression at Subarray Level for Frequency Diverse Array Antenna
Ramadan, M.; Raza, S.
2022. 2022 16th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), 231–237, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SITIS57111.2022.00049

Simulation of Synthetically Degraded Tracking Data to Benchmark MOT Metrics
Hartmann, M.; Löffler, K.; Mikut, R.
2022. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. Ed.: H. Schulte, 163–180, KIT Scientific Publishing

EasyMLServe: Easy Deployment of REST Machine Learning Services
Neumann, O.; Schilling, M.; Reischl, M.; Mikut, R.
2022. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 11–30, KIT Scientific Publishing

Evaluation of Transformer Architectures for Electrical Load Time-Series Forecasting
Hertel, M.; Ott, S.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.; Neumann, O.
2022. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. Hrsg.: H. Schulte, F. Hoffmann; R. Mikut, 93–110, KIT Scientific Publishing

Multi-stage Inspection of Laser Welding Defects using Machine Learning
Dold, P. M.; Bleier, F.; Boley, M.; Mikut, R.
2022. Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 31–52, KIT Scientific Publishing

Comparison of Experiment Tracking Frameworks in Machine Learning Environments
Budras, T.; Blanck, M.; Berger, T.; Schmidt, A.
2022. 14th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2022), Venice, I, May 22-26, 2022. Ed.: M. Crowe, International Academy, Research, and Industry Association (IARIA)

On the Assessment of the Effect of Multiple Process Parameters on the Precision of 3D Inkjet Printing
Elkaseer, A.; Kuchta, M.; Scholz, S. G.
2022. Proceedings of the World Congress on Micro and Nano Manufacturing, 19-22 September 2022, Leuven, Belgium. Ed.: S. Castagne, 126–131, Research Publishing. doi:10.3850/978-981-18-5180-3_RP26-0069

Comparison of Four-Switch Buck-Boost and Dual Active Bridge Converter for DC Microgrid Applications
Ekin, Ö.; Arena, G.; Waczowicz, S.; Hagenmeyer, V.; Carne, G.
2022. 2022 IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PEDG54999.2022.9923074

About Lightweight Code Generation
Schmidt, A.
2022. Web Engineering : 22nd International Conference, ICWE 2022, Bari, Italy, July 5–8, 2022. Ed.: T. Di Noia, 497–500, Springer International Publishing. doi:10.1007/978-3-031-09917-5_43

An Optimization-based Approach for Automated Generation of Residential Low-Voltage Grid Models Using Open Data and Open Source Software
Cakmak, H. K.; Janecke, L.; Weber, M.; Hagenmeyer, V.
2022. 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe54678.2022.9960483

Demand Response in Smart Districts: Model Predictive Control of Building Cooling
Zwickel, P.; Frahm, M.; Galenzowski, J.; Hafele, K.-H.; Maass, H.; Waczowicz, S.; Hagenmeyer, V.
2022. 2022 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe54678.2022.9960608

A Computational Workflow for Interdisciplinary Deep Learning Projects utilizing bwHPC Infrastructure
Schilling, M.; Neumann, O.; Scherr, T.; Cui, H.; Popova, A. A.; Levkin, P. A.; Götz, M.; Reischl, M.
2022. Proceedings of the 7th bwHPC Symposium, 69–74, Kommunikations- und Informationszentrum (kiz). doi:10.18725/OPARU-46069

Dynamic Optimization of Energy Hubs with Evolutionary Algorithms Using Adaptive Time Segments and Varying Resolution
Poppenborg, R.; Khalloof, H.; Chlosta, M.; Hofferberth, T.; Düpmeier, C.; Hagenmeyer, V.
2022. Intelligent Data Engineering and Automated Learning – IDEAL 2022 : 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022, Proceedings. Ed.: H. Yin, 513–524, Springer International Publishing. doi:10.1007/978-3-031-21753-1_50

Early Detection of GOOSE Denial of Service (DoS) Attacks in IEC 61850 Substations
Elbez, G.; Nahrstedt, K.; Hagenmeyer, V.
2022. IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids 2022. doi:10.1109/SmartGridComm52983.2022.9961042

Comparing human and algorithmic anomaly detection for HVAC systems applications
Borrison, R.; Syndicus, M.; Orth, A.; Markovic, R.; Dix, M.; Liguori, A.; Berning, M.; Wagner, A.; Van Treeck, C.
2022. Conference Proceedings: 2022 IEEE Eighth International Conference on Big Data Computing Service and Applications (BigDataService), 155–160, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BigDataService55688.2022.00032

Exploiting Multiple EEG Data Domains with Adversarial Learning
Bethge, D.; Hallgarten, P.; Ozdenizci, O.; Mikut, R.; Schmidt, A.; Grosse-Puppendahl, T.
2022. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 3154–3158, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EMBC48229.2022.9871743

Multi-Zone Grey-Box Thermal Building Identification with Real Occupants
Frahm, M.; Meisenbacher, S.; Klumpp, E.; Mikut, R.; Matthes, J.; Hagenmeyer, V.
2022. Proceedings of the 9th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, BuildSys 2022, Boston, MA, USA, 09.11.2022-10.11.2022. Ed.: J. Ortiz, 484–487, Association for Computing Machinery (ACM). doi:10.1145/3563357.3567403

Hardware Realization of Participants in an Energy Packet-based Power Grid
Schulz, D.; Schneider, K.; Weßbecher, M.; Hagenmeyer, V.; Zitterbart, M.; Hiller, M.
2022. IEEE 13th International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PEDG54999.2022.9923290

Fast Grid State Estimation for Power Networks: An Ensemble Machine Learning Approach
Shahoud, S.; Khalloof, H.; Khalouf, R.; Düpmeier, C.; Cakmak, H. K.; Forderer, K.; Hagenmeyer, V.
2022. 2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE), 12–18, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE55279.2022.9889763

Data Fusion and State Estimation Using Belief Propagation in Gas Distribution Networks
Demirel, G.; Jongh, S. de; Müller, F.; Leibfried, T.
2022. 57th International Universities Power Engineering Conference, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/UPEC55022.2022.9917770

A Photovoltaic System Model Integration FAIR Digital Objects and Ontologies
Schweikert, J.; Stucky, U.; Süß, W.; Hagenmeyer, V.
2022. 2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE), Oshawa, ON, Canada, 10-12 August 2022, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE55279.2022.9889768

Energy Hub Gas: A Modular Setup for the Evaluation of Local Flexibility and Renewable Energy Carriers Provision
Poppenborg, R.; Chlosta, M.; Ruf, J.; Hotz, C.; Düpmeier, C.; Kolb, T.; Hagenmeyer, V.
2022. 2022 IEEE 10th International Conference on Smart Energy Grid Engineering (SEGE), 33–41, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE55279.2022.9889751

Experimental Setup for Evaluation of Medical Ozone Gas Sensors
Petani, L.; Wickersheim, D.; Koker, L.; Reischl, M.; Gengenbach, U.; Pylatiuk, C.
2022. 2022 IEEE Sensors Applications Symposium (SAS), 1st - 3rd August 2022, Sundsvall, Sweden, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SAS54819.2022.9881340

Development and Validation of Grey-Box Multi-Zone Thermal Building Models
Frahm, M.; Klumpp, E.; Meisenbacher, S.; Matthes, J.; Mikut, R.; Hagenmeyer, V.
2022. Proceedings of BauSim Conference 2022 : 9th Conference of IBPSA-Germany and Austria, 20-22 September 2022, Bauhaus Universität Weimar. C. Völker, 346–351, International Building Performance Simulation Association (IBPSA). doi:10.26868/29761662.2022.22

Ratio-based features for bridge damage detection based on displacement influence line and curvature influence line
Döring, A.; Vogelbacher, M.; Schneider, O.; Müller, J.; Hinz, S.; Matthes, J.
2022. Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability, CRC Press

Boost short-term load forecasts with synthetic data from transferred latent space information
Heidrich, B.; Mannsperger, L.; Turowski, M.; Phipps, K.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2022. DACH+ Conference on Energy Informatics German Federal Ministry for Economic Affairs and Energy

Domain-Invariant Representation Learning from EEG with Private Encoders
Bethge, D.; Hallgarten, P.; Grosse-Puppendahl, T.; Kari, M.; Mikut, R.; Schmidt, A.; Ozdenizci, O.
2022. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 23-27 May 2022, 1236–1240, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICASSP43922.2022.9747398

BCFViewer – BIM Collaboration Format tool development
Lourenzi, F.; Geiger, A.
2022. Proceedings of 33. ForumBauinformatik, 07. – 09. September 2022, Technische Universität München. Hrsg.: M. Slepicka, 343 – 350

Integration of Monitoring Data into a Virtual 3D Campus Model
Häfele, K.-H.; Geiger, A.; Kaiser, F.-J.; Hagenmeyer, V.
2022. Proceedings of BauSim Conference 2022: 9th Conference of IBPSA-Germany and Austria, International Building Performance Simulation Association (IBPSA). doi:10.26868/29761662.2022.32

Usage Profile Enrichment of CityGML Models for Urban Building Energy Modeling
Geiger, A.; Nichersu, A.; Häfele, K.-H.; Hagenmeyer, V.
2022. Proceedings of BauSim Conference 2022: 9th Conference of IBPSA-Germany and Austria, International Building Performance Simulation Association (IBPSA). doi:10.26868/29761662.2022.28

Automated floorplan generation using mathematical optimization
Zhong, Y.; Geiger, A.
2022. 14th European Conference on Product and Process Modelling, Norwegian University of Science and Technology (NTNU)

Ciscnet - a Single-Branch Cell Nucleus Instance Segmentation and Classification Network
Böhland, M.; Neumann, O.; Schilling, M. P.; Reischl, M.; Mikut, R.; Loffler, K.; Scherr, T.
2022. 2022 IEEE International Symposium on Biomedical Imaging Challenges (ISBIC), 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISBIC56247.2022.9854734

Facilitating the hybridization of parallel evolutionary algorithms in cluster computing environments
Khalloof, H.; Ciftci, S.; Shahoud, S.; Duepmeier, C.; Foerderer, K.; Hagenmeyer, V.
2022. GECCO ’22: Proceedings of the Genetic and Evolutionary Computation Conference Companion. Ed.: J. E. Fieldsend, 2001–2008, Association for Computing Machinery (ACM). doi:10.1145/3520304.3533997

High-resolution real-world electricity data from three microgrids in the global south
Luh, M.; Phipps, K.; Britto, A.; Wolf, M.; Lutz, M.; Kraft, J.
2022. e-Energy ’22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, 496–514, Association for Computing Machinery (ACM). doi:10.1145/3538637.3539763

Modelling power systems as flat hybrid automata for controlled line switching
Zahn, F.; Hagenmeyer, V.
2022. e-Energy ’22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, 302–306, Association for Computing Machinery (ACM). doi:10.1145/3538637.3538859

Modelling and Simulation of an Aerosol-on-Demand Print Head with Computational Fluid Dynamics
Ungerer, M.; Zeltner, D.; Wenka, A.; Gengenbach, U.; Sieber, I.
2022. Proceedings of the 12th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2022), July 14-16, 2022, in Lisbon, Portugal. Ed.: Gerd Wagner, 44–51, SciTePress. doi:10.5220/0011258100003274

Towards line-restricted dispatchable feeders using probabilistic forecasts for PV-dominated low-voltage distribution grids
Werling, D.; Heidrich, B.; Çakmak, H. K.; Hagenmeyer, V.
2022. e-Energy ’22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022- 1 July 2022. Ed.: S. Lehnhoff, 395–400, Association for Computing Machinery (ACM). doi:10.1145/3538637.3538868

Analytical uncertainty propagation and storage usage in a high RES Turkish transmission grid scenario
Bauer, R.; Mühlpfordt, T.; Ludwig, N.; Hagenmeyer, V.
2022. e-Energy ’22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022- 1 July 2022. Ed.: S. Lehnhoff, 489–495, Association for Computing Machinery (ACM). doi:10.1145/3538637.3539762

Enhancing anomaly detection methods for energy time series using latent space data representations
Turowski, M.; Heidrich, B.; Phipps, K.; Schmieder, K.; Neumann, O.; Mikut, R.; Hagenmeyer, V.
2022. e-Energy ’22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022- 1 July 2022. Ed.: S. Lehnhoff, 208–227, Association for Computing Machinery (ACM). doi:10.1145/3538637.3538851

Modeling and Generating Synthetic Anomalies for Energy and Power Time Series
Turowski, M.; Weber, M.; Neumann, O.; Heidrich, B.; Phipps, K.; Çakmak, H. K.; Mikut, R.; Hagenmeyer, V.
2022. e-Energy ’22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022- 1 July 2022. Ed.: S. Lehnhoff, 471–484, Association for Computing Machinery (ACM). doi:10.1145/3538637.3539760

Adaptively coping with concept drifts in energy time series forecasting using profiles
Heidrich, B.; Ludwig, N.; Turowski, M.; Mikut, R.; Hagenmeyer, V.
2022. e-Energy ’22: The Thirteenth ACM International Conference on Future Energy Systems, Virtual Event, 28 June 2022- 1 July 2022. Ed.: S. Lehnhoff, 459–470, Association for Computing Machinery (ACM). doi:10.1145/3538637.3539759

Occupant-oriented economic model predictive control for demand response in buildings
Frahm, M.; Zwickel, P.; Wachter, J.; Langner, F.; Strauch, P.; Matthes, J.; Hagenmeyer, V.
2022. e-Energy ’22: Proceedings of the Thirteenth ACM International Conference on Future Energy Systems, 354–360, Association for Computing Machinery (ACM). doi:10.1145/3538637.3538864

VILLASnode-based Co-simulation of Local Energy Communities
Carta, D.; Weber, M.; Glucker, P.; Pesch, T.; Hagenmeyer, V.; Benigni, A.; Kuhnapfel, U.
2022. 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES): April 4–5, 2022, Aachen, Germany, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES54027.2022.9768933

Oscillating Combustion for NOₓ-Reduction in Pulverized Fuel Boilers
Jolibois, N.; Gehrmann, H. J.; Aleksandrov, K.; Hauser, M.; Stapf, D.; Seifert, H.; Waibel, P.; Vogelbacher, M.; Matthes, J.
2022. 13th European Conference on Industrial Furnances and Boilers (INFUB-13), Centro de Energia e Tecnologia (CENERTEC)

Using Open Data for Modeling and Simulation of the All Electrical Society in eASiMOV
Çakmak, H. K.; Hagenmeyer, V.
2022. 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES), 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES54027.2022.9769145

How to Derive and Implement a Minimalistic RC Model from Thermodynamics for the Control of Thermal Parameters for Assuring Thermal Comfort in Buildings
Frahm, M.; Langner, F.; Zwickel, P.; Matthes, J.; Mikut, R.; Hagenmeyer, V.
2022. 2022 Open Source Modelling and Simulation of Energy Systems (OSMSES), 6 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/OSMSES54027.2022.9769134

Determination of the aerodynamic properties of refuse derived fuel by computer vision
Streier, R.; Wirtz, S.; Aleksandrov, K.; Gehrmann, H. J.; Stapf, D.; Zhang, M.; Vogelbacher, M.; Matthes, J.; Scherer, V.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilers

Deep learning-based segmentation of overlapping flames in industrial combustion chambers
Vogelbacher, M.; Waibel, P.; Großkopf, J.; Kollmer, M.; Matthes, J.
2022. Proceedings of the13th European Conference on Industrial Furnaces and Boilers

Analysis of spatial flight properties of refuse-derived fuel particles based on a light-field camera system
Zhang, M.; Vogelbacher, M.; Aleksandrov, K.; Gehrmann, H. J.; Stapf, D.; Streier, R.; Wirtz, S.; Scherer, V.; Matthes, J.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilers

A camera-based flame stability controller for non-oscillating and forced-oscillating combustion
Matthes, J.; Waibel, P.; Vogelbacher, M.; Keller, H. B.; Gehrmann, H. J.; Stapf, D.
2022. Proceedings of the 13th European Conference on Industrial Furnaces and Boilers

Experimental Evaluation and Systematic-Error Reduction of Frequency Estimation Using the Zero-Crossing Technique for Dynamic Power Grids
Förstner, E.; JUmar, R.; Tanrikulu, O. D.; Maaß, H.; Kühnapfel, U.; Hagenmeyer, V.
2022. The 2022 International Conference on Smart Grid Synchronized Measurements and Analytics – SGSMA, Split, Croatia, May 24h - 26th 2022, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SGSMA51733.2022.9806021

Methods and Prospects of Machine Learning applied to Challenges in Crystallography
Reischl, M.; Schützke, J.
2022. DGK München

Microservice-Based Architecture for the Integration of Data Backends and Dashboard Applications in the Energy and Environment Domains
Sidler, J.; Braun, E.; Schmitt, C.; Schlachter, T.; Hagenmeyer, V.
2022. Advances and New Trends in Environmental Informatics. Ed.: V. Wohlgemuth, 37–48, Springer International Publishing. doi:10.1007/978-3-030-88063-7

Features Detection-Based Computer Vision of Transparent 3D Inkjet Printed Parts
Elkaseer, A.; Scholz, A.; Scholz, S. G.
2022. Proceedings of the Future Technologies Conference (FTC) 2021, Volume 2. Ed.: K. Arai, 218–231, Springer International Publishing. doi:10.1007/978-3-030-89880-9_17

Development of Correction Factors for FDM 3D Printers: Experimental Investigation and ANN Modelling
Müller, T.; Elkaseer, A.; Wadlinger, J.; Salem, M.; Scholz, S. G.
2022. Sustainable Design and Manufacturing : Proceedings of the 8th International Conference on Sustainable Design and Manufacturing (KES-SDM 2021) . Ed.: S. Scholz, 314–326, Springer Singapur. doi:10.1007/978-981-16-6128-0_30

Human Activity Recognition Using K-Nearest Neighbor Machine Learning Algorithm
Mohsen, S.; Elkaseer, A.; Scholz, S. G.
2022. Sustainable Design and Manufacturing – Proceedings of the 8th International Conference on Sustainable Design and Manufacturing (KES-SDM 2021). Ed.: S. Scholz, 304–313, Springer Singapur. doi:10.1007/978-981-16-6128-0_29

Additive Manufacturing in the Automotive Industry and the Potential for Driving the Green and Electric Transition
Charles, A.; Hofer, A.; Elkaseer, A.; Scholz, S. G.
2022. Sustainable Design and Manufacturing: Proceedings of the 8th International Conference on Sustainable Design and Manufacturing (KES-SDM 2021) . Ed.: S. G. Scholz, 339–346, Springer Singapur. doi:10.1007/978-981-16-6128-0_32

14th International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2022), Venice, I, May 22-26, 2022. Proceedings
Crowe, M.; Laux, F.; Schmidt, A. (Eds.)
2022. International Academy Research and Industry Association (IARIA)

Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022
Schulte, H.; Hoffmann, F.; Mikut, R. (Eds.)
2022. doi:10.5445/KSP/1000151141

Sustainable Design and Manufacturing – Proceedings of the 8th International Conference on Sustainable Design and Manufacturing (KES-SDM 2021)
Scholz, S. G.; Howlett, R. J.; Setchi, R. (Eds.)
2022. Springer Singapur. doi:10.1007/978-981-16-6128-0

Euler-Bernoulli beam for Matlab
Döring, A.
2022. doi:10.5281/ZENODO.6675691

Stepped-Euler-Bernoulli-Beam for Matlab
Döring, A.
2022. doi:10.5281/ZENODO.6675982

Entomoscope - Plug-In
Wührl, L.
2022, November 28

Entomoscope - Standalone
Wührl, L.; Pylatiuk, C.
2022, October 28

HMC Community Survey 2021
Arndt, W.; Gerlich, S. C.; Hofmann, V.; Kubin, M.; Kulla, L.; Lemster, C.; Mannix, O.; Nolden, M.; Rink, K.; Schweikert, J.; Shankar, S.; Söding, E.; Steinmeier, L.; Suess, W.
2022. doi:10.7802/2433

Predicting the power grid frequency of European islands
Lund Onsaker, T.; Nygård, H. S.; Gomila, D.; Colet, P.; Mikut, R.; Jumar, R.; Kühnapfel, U.; Maass, H.; Hagenmeyer, V.; Witthaut, D.; Schäfer, B.
2022, September 27. doi:10.48550/arXiv.2209.15414

Data for - Tracking one in a million: Performance of automated tracking on a large-scale microbial data set (1.0.0) [Data set]
Seiffarth, J.; Blöbaum, L.; Löffler, K.; Scherr, T.; Grünberger, A.; Scharr, H.; Mikut R.; Nöh, K.
2022, October 28. doi:10.5281/zenodo.7260137

microbeSEG dataset (1.0) [Data set]
Scherr, T.; Seiffarth, J.; Wollenhaupt, B.; Neumann, O.; Schilling, M.; Kohlheyer, D.; Scharr, H.; Mikut, R.; Nöh, K.
2022, April 28. doi:10.5281/zenodo.6497715

Use Cases in HMC - from Generation to Reuse of Data
Günther, G.; Schweikert, J.; Mannix, O.; Süß, W.
2022, October 6. doi:10.5281/zenodo.7157694

Use Cases and Tools in HMC Hub Energy
Süß, W.; Stucky, K. U.; Schweikert, J.; Koubaa, M. A.; Ballani, F.; Steinmeier, L.
2022, October 10. doi:10.5281/zenodo.7180896

HMC Community Survey: A Survey on research data management practices among researchers in the Helmhotz-Association
Gerlich, S.; Hofmann, V.; Kubin, M.; Lemster, C.; Mannix, O.; Rink, K.; Schweikert, J.; Shankar, S.; Söding, E.; Steinmeier, L.; Süß, W.
2022. doi:10.7803/2433

High-Resolution Real-World Electricity Data from Three Microgrids in the Global South
Luh, M.; Phipps, K.; Britto, A.; Wolf, M.; Lutz, M.; Kraft, J.
2022, May 23. doi:10.5445/IR/1000143466

New Work - Erfahrungen der Piloten - PIlotprojekt von IAI
Zahn, F.
2022. (I. Hartmann-Dietsch & M. Landgraf, Eds.)

Local market models
Gazafroudi, A. S.; Khajeh, H.; Shafie-khah, M.; Laaksonen, H.; Corchado, J. M.
2021. Local Electricity Markets. Ed.: T. Pinto, 79–90, Academic Press. doi:10.1016/B978-0-12-820074-2.00010-1

Automatisierte Grundrisserzeugung in der Entwurfsphase
Geiger, A.; Zhong, Y.
2021. BIM und KI in Wissenschaft & Unternehmenspraxis. Hrsg.: K. Teizer

Dynamic Model Based Detection of Cyberattacks in Industrial Facilities
Reibelt, K.; Keller, H. B.; Hagenmeyer, V.; Matthes, J.
2021. 31st European Symposium on Computer Aided Process Engineering: ESCAPE-31. Ed.: M. Türkay, 1339–1344, Elsevier. doi:10.1016/B978-0-323-88506-5.50206-0

Modeling and Simulation of Sector-Coupled Energy Networks: A Gas-Power Benchmark
Fokken, E.; Mühlpfordt, T.; Faulwasser, T.; Göttlich, S.; Kolb, O.
2021. Mathematical Modeling, Simulation and Optimization for Power Engineering and Management. Ed.: S. Göttlich, 263–284, Springer International Publishing. doi:10.1007/978-3-030-62732-4_12

Informatik 2020 - Bericht der Session zum Thema Software Engineering
Becker, S.; Keller, H.
2021. Informatik 2020. Hrsg.: R.H. Reussner, A. Koziolek, 35–37, Gesellschaft für Informatik (GI)

Heterogeneous Dual-Frequency IoT Network for Vital Data Acquisition
Salem, M.; El-Maddah, I.; Youssef, K.; Elkaseer, A.; Scholz, S.; Mohamed, H.
2021. Sustainable Design and Manufacturing 2020. Ed.: S. Scholz, 333–343, Springer Nature. doi:10.1007/978-981-15-8131-1_30

Sustainable Design and Manufacturing 2020 - Proceedings of the 7th International Conference on Sustainable Design and Manufacturing (KES-SDM 2020)
Scholz, S. G.; Howlett, R. J.; Setchi, R. (Eds.)
2021. Springer Singapur. doi:10.1007/978-981-15-8131-1

Modeling and Control of the Falling Film Evaporator Process. PhD dissertation
Hofmann, J.
2021, December 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000141284

Computational and Near-Optimal Trade-Offs in Renewable Electricity System Modelling. PhD dissertation
Neumann, F.
2021, September 13. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000137267

Engineering of Reliable and Secure Software via Customizable Integrated Compilation Systems. PhD dissertation
Scherer, O.
2021, June 28. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000134165

Machine Learning Methods for Product Quality Monitoring in Electric Resistance Welding. PhD dissertation
Zhou, B.
2021, May 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000132412

Machine learning-based automated segmentation with a feedback loop for 3D synchrotron micro-CT. PhD dissertation
Shkarin, R.
2021, February 18. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000129244

A Parallel Hybrid Method for Fast Analysis of Power System Dynamics. PhD dissertation
Kyesswa, M.
2021, January 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000128495

Distributed Optimization with Application to Power Systems and Control. PhD dissertation
Engelmann, A.
2021, January 11. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000127849/v2

Structure Exploitation in Mixed-Integer Optimization with Applications to Energy Systems. PhD dissertation
Murray, A.
2021, January 27. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000125528

Development of an automated milling system for the decontamination of the wall surface in a nuclear power plant
Li, C.; Kazemi, S.; Gentes, S.
2021. Safety of Nuclear Waste Disposal, 1, 23–24. doi:10.5194/sand-1-23-2021

Equality test with an anonymous authorization in cloud computing
Abdalla, H.; Xiong, H.; Wahaballa, A.; Ramadan, M.; Qin, Z.
2021. Wireless Networks, 27 (2), 1063–1076. doi:10.1007/s11276-020-02462-5

Wertstromkinematik – Produktionssysteme neu gedacht: Interdisziplinäres Forscherteam arbeitet an der Produktionstechnik der Zukunft (Teil 2)
Kimmig, A.; Schöck, M.; Mühlbeier, E.; Oexle, F.; Fleischer, J.; Bönsch, J.; Ovtcharova, J.; Hahn, J.; Grunwald, A.; Albers, A.; Rapp, S.; Hagenmeyer, V.; Scholz, S. G.; Schmidt, A.; Müller, T.; Becker, J.; Schade, F.; Beyerer, J.; Rehak, J.; Zwick, T.; Pauli, M.; Nuß, B.; Lanza, G.; Schild, L.; Overbeck, L.
2021. Zeitschrift für wirtschaftlichen Fabrikbetrieb, 116 (12), 935–939. doi:10.1515/zwf-2021-0207

Iterative Game Approach for Modeling the Behavior of Agents in a Competitive Flexibility Trading
Ebrahimi, M.; Gazafroudi, A. S.; Ebrahimi, M.; Laaksonen, H.; Shafie-Khah, M.; Catalao, J. P. S.
2021. IEEE access, 9, 165227–165238. doi:10.1109/ACCESS.2021.3134937

A generic flexible and scalable framework for hierarchical parallelization of population-based metaheuristics
Khalloof, H.; Mohammad, M.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2021. Internet of Things, 16, Art.-Nr. 100433. doi:10.1016/j.iot.2021.100433

Automated generation of models for demand side flexibility using machine learning – an overview
Förderer, K.; Hagenmeyer, V.; Schmeck, H.
2021. ACM SIGEnergy Energy Informatics Review, 1 (1), 107–120. doi:10.1145/3508467.3508477

Grid Screener: A Tool for Automated High-throughput Screening on Biochemical and Biological Analysis Platforms
Schilling, M. P.; Schmelzer, S.; Gómez, J. E. U.; Popova, A. A.; Levkin, P. A.; Reischl, M.
2021. IEEE access, 9, 166027–166038. doi:10.1109/ACCESS.2021.3135709

Rational Designed Hybrid Peptides Show up to a 6-Fold Increase in Antimicrobial Activity and Demonstrate Different Ultrastructural Changes as the Parental Peptides Measured by BioSAXS
Hilpert, K.; Gani, J.; Rumancev, C.; Simpson, N.; Lopez-Perez, P. M.; Garamus, V. M.; Gundlach, A. R. von; Markov, P.; Scocchi, M.; Mikut, R.; Rosenhahn, A.
2021. Frontiers in pharmacology, 12, Article no: 769739. doi:10.3389/fphar.2021.769739

Wide-field mosaics of the corneal subbasal nerve plexus in Parkinson’s disease using in vivo confocal microscopy
Badian, R. A.; Allgeier, S.; Scarpa, F.; Andréasson, M.; Bartschat, A.; Mikut, R.; Colonna, A.; Bellisario, M.; Utheim, T. P.; Köhler, B.; Svenningsson, P.; Lagali, N.
2021. Scientific data, 8 (1), Article no: 306. doi:10.1038/s41597-021-01087-3

Fundamental investigation into tool wear and surface quality in high-speed machining of Ti6Al4V alloy
Abbas, A. T.; Al Bahkali, E. A.; Alqahtani, S. M.; Abdelnasser, E.; Naeim, N.; Elkaseer, A.
2021. Materials, 14 (23), 7128. doi:10.3390/ma14237128

Pilotstudie zur Evaluation einer medizinisch-beruflich orientierten Rehabilitation für Pflegekräfte
Wittmann, C.; Papst, L.; Reischl, M.; Welsch, K.; Käfer, M.; Köllner, V.
2021. Zeitschrift für psychosomatische Medizin und Psychotherapie, 68 (2), 128–140. doi:10.13109/zptm.2021.67.oa13

Machine learning methods for automated classification of tumors with papillary thyroid carcinoma-like nuclei : A quantitative analysis
Böhland, M.; Tharun, L.; Scherr, T.; Mikut, R.; Hagenmeyer, V.; Thompson, L. D. R.; Perner, S.; Reischl, M.
2021. PLOS ONE, 16 (9), e0257635. doi:10.1371/journal.pone.0257635

An extended Meta Learning Approach for Automating Model Selection in Big Data Environments using Microservice and Container Virtualizationz Technologies
Shahoud, S.; Winter, M.; Khalloof, H.; Duepmeier, C.; Hagenmeyer, V.
2021. Internet of Things (Netherlands), 16, Art.Nr. 100432. doi:10.1016/j.iot.2021.100432

Industry 4.0-Oriented Deep Learning Models for Human Activity Recognition
Mohsen, S.; Elkaseer, A.; Scholz, S. G.
2021. IEEE Access, 9, 150508–150521. doi:10.1109/ACCESS.2021.3125733

ALADIN-α—An open-source MATLAB toolbox for distributed non-convex optimization
Engelmann, A.; Jiang, Y.; Benner, H.; Ou, R.; Houska, B.; Faulwasser, T.
2021. Optimal Control Applications and Methods, 43 (1), 4–22. doi:10.1002/oca.2811

Peer-to-Peer Electricity Market based on Local Supervision
Khajeh, H.; Gazafroudi, A. S.; Laaksonen, H.; Shafie-Khah, M.; Siano, P.; Catalão, J. P. S.
2021. IEEE access, 9, 156647–156662. doi:10.1109/ACCESS.2021.3129050

Prof. Dr.-Ing. habil. Jürgen Beyerer zum 60. Geburtstag
Bretthauer, G.
2021. Automatisierungstechnik, 69 (10), 919–920. doi:10.1515/auto-2021-2050

Classification of Bundle Branch Blocks with QRS Templates Extracted from 12-lead ECGs
Welle, H.; Nagel, C.; Loewe, A.; Mikut, R.; Dössel, O.
2021. Biomedical engineering, 66 (s1), S228–S233. doi:10.1515/bmt-2021-6033

Influence of contact cap design on large-area imaging of the subbasal nerve plexus
Bohn, S.; Sperlich, K.; Allgeier, S.; Bartschat, A.; Reichert, K.-M.; Kornelius, L.; Mikut, R.; Köhler, B.; Stachs, O.
2021. Biomedical engineering, 66 (s1), S124. doi:10.1515/bmt-2021-6018

A software framework for real-time image mosaicking of the corneal subbasal nerve plexus
Köhler, B.; Kornelius, L.; Bartschat, A.; Bohn, S.; Mikut, R.; Reichert, K.-M.; Sperlich, K.; Stachs, O.; Allgeier, S.
2021. Biomedical engineering, 66 (s1), S121

Systematic assessment of the biocompatibility of materials for inkjet-printed ozone sensors for medical therapy
Petani, L.; Wehrheim, V.; Koker, L.; Reischl, M.; Ungerer, M.; Gengenbach, U.; Pylatiuk, C.
2021. Flexible and printed electronics, 6 (4), Art.-Nr.: 043003. doi:10.1088/2058-8585/ac32ab

FAIR Metadata Standards for Low Carbon Energy Research—A Review of Practices and How to Advance
Wierling, A.; Schwanitz, V. J.; Altinci, S.; Bałazińska, M.; Barber, M. J.; Biresselioglu, M. E.; Burger-Scheidlin, C.; Celino, M.; Demir, M. H.; Dennis, R.; Dintzner, N.; Gammal, A. el; Fernández-Peruchena, C. M.; Gilcrease, W.; Gładysz, P.; Hoyer-Klick, C.; Joshi, K.; Kruczek, M.; Lacroix, D.; Markowska, M.; Mayo-García, R.; Morrison, R.; Paier, M.; Peronato, G.; Ramakrishnan, M.; Reid, J.; Sciullo, A.; Solak, B.; Suna, D.; Süß, W.; Unger, A.; Fernandez Vanoni, M. L.; Vasiljevic, N.
2021. Energies, 14 (20), Art. Nr.: 6692. doi:10.3390/en14206692

SemML: Facilitating development of ML models for condition monitoring with semantics
Zhou, B.; Svetashova, Y.; Gusmao, A.; Soylu, A.; Cheng, G.; Mikut, R.; Waaler, A.; Kharlamov, E.
2021. Web semantics, 71, Art.Nr. 100664. doi:10.1016/j.websem.2021.100664

Evaluierung von Merkmalen zur Abbildung von Veränderungen in ungeordneten Bilddaten = Evaluating features to represent changes in unstructured image data
Münke, F. R.; Schilling, M. P.; Mikut, R.; Reischl, M.
2021. Automatisierungstechnik, 69 (10), 892–902. doi:10.1515/auto-2021-0038

CAD-to-real: enabling deep neural networks for 3D pose estimation of electronic control units – A transferable and automated approach for industrial use cases = CAD-to-real: Eine Methode zum Einsatz tiefer neuronaler Netze bei der 3D-Lageerkennung von elektronischen Steuergeräten - Ein transferierbarer und automatisierter Ansatz für industrielle Anwendungen
Bäuerle, S.; Böhland, M.; Barth, J.; Reischl, M.; Steimer, A.; Mikut, R.
2021. Automatisierungstechnik, 69 (10), 880–891. doi:10.1515/auto-2021-0020

Ausgewählte Beiträge aus dem GMA-Fachausschuss 5.14 „Computational Intelligence“ [Editorial]
Mikut, R.; Kroll, A.; Schulte, H.
2021. Automatisierungstechnik, 69 (10), 817–819. doi:10.1515/auto-2021-0124

Is There a Connection Between Gut Microbiome Dysbiosis Occurring in COVID-19 Patients and Post-COVID-19 Symptoms?
Hilpert, K.; Mikut, R.
2021. Frontiers in Microbiology, 12, Art.-Nr.: 732838. doi:10.3389/fmicb.2021.732838

Diagnose-Spektrum somatischer Komorbiditäten bei unterschiedlichen AVEM Mustern in der Psychosomatischen Rehabilitation
Wittmann, C.; Reischl, M.; Welsch, K.; Käfer, M.; Köllner, V.
2021. Praxis klinische Verhaltensmedizin und Rehabilitation, 114 (2), 58–67

Inherently UV Photodegradable Poly(methacrylate) Gels
Scheiger, J. M.; Li, S.; Brehm, M.; Bartschat, A.; Theato, P.; Levkin, P. A.
2021. Advanced Functional Materials, 31 (49), Art.-Nr.: 2105681. doi:10.1002/adfm.202105681

Application of 3D MAPs pipeline identifies the morphological sequence chondrocytes undergo and the regulatory role of GDF5 in this process
Rubin, S.; Agrawal, A.; Stegmaier, J.; Krief, S.; Felsenthal, N.; Svorai, J.; Addadi, Y.; Villoutreix, P.; Stern, T.; Zelzer, E.
2021. Nature Communications, 12 (1), Article no: 5363. doi:10.1038/s41467-021-25714-0

Time-Delay Identification and Validation of a Liquid Film Transport Model based on Pilot Plant Experiments
Hofmann, J.; Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2021. IFAC-PapersOnLine, 54 (3), 401–408. doi:10.1016/j.ifacol.2021.08.275

A new multivariable control concept for the falling film evaporator process
Hofmann, J.; Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2021. Journal of process control, 106, 72–83. doi:10.1016/j.jprocont.2021.08.015

A graph-based cell tracking algorithm with few manually tunable parameters and automated segmentation error correction
Löffler, K.; Scherr, T.; Mikut, R.
2021. PLOS ONE, 16 (9), e0249257. doi:10.1371/journal.pone.0249257

An Automated Experimentation System for the Touch-Response Quantification of Zebrafish Larvae
Wang, Y.; Marcato, D.; Tirumalasetty, V.; Kanagaraj, N. K.; Pylatiuk, C.; Mikut, R.; Peravali, R.; Reischl, M.
2021. IEEE transactions on automation science and engineering, 19 (4), 3007–3019. doi:10.1109/TASE.2021.3104507

Hierarchical approach for coordinating energy and flexibility trading in local energy markets
Gazafroudi, A. S.; Khorasany, M.; Razzaghi, R.; Laaksonen, H.; Shafie-khah, M.
2021. Applied Energy, 302, Art.-Nr.: 117575. doi:10.1016/j.apenergy.2021.117575

Probabilistic forecasts of the distribution grid state using data-driven forecasts and probabilistic power flow
González-Ordiano, J. Á.; Mühlpfordt, T.; Braun, E.; Liu, J.; Çakmak, H.; Kühnapfel, U.; Düpmeier, C.; Waczowicz, S.; Faulwasser, T.; Mikut, R.; Hagenmeyer, V.; Appino, R. R.
2021. Applied energy, 302, Art.-Nr.: 117498. doi:10.1016/j.apenergy.2021.117498

Integrating Battery Aging in the Optimization for Bidirectional Charging of Electric Vehicles
Schwenk, K.; Meisenbacher, S.; Briegel, B.; Harr, T.; Hagenmeyer, V.; Mikut, R.
2021. IEEE transactions on smart grid, 12 (6), 5135–5145. doi:10.1109/TSG.2021.3099206

Data-Driven Copy-Paste Imputation for Energy Time Series
Weber, M.; Turowski, M.; Çakmak, H. K.; Mikut, R.; Kühnapfel, U.; Hagenmeyer, V.
2021. IEEE transactions on smart grid, 12 (6), 5409–5419. doi:10.1109/TSG.2021.3101831

Characterization of Aggregated Building Heating, Ventilation, and Air Conditioning Load as a Flexibility Service Using Gray‐Box Modeling
Kohlhepp, P.; Gröll, L.; Hagenmeyer, V.
2021. Energy technology, 9 (9), Art.-Nr.: 2100251. doi:10.1002/ente.202100251

Down-facing surfaces in laser powder bed fusion of Ti6Al4V: Effect of dross formation on dimensional accuracy and surface texture
Charles, A. P.; Elkaseer, A.; Paggi, U.; Thijs, L.; Hagenmeyer, V.; Scholz, S.
2021. Additive manufacturing, 46, Article: 102148. doi:10.1016/j.addma.2021.102148

A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light
Kumpošt, V.; Vallone, D.; Gondi, S. B.; Foulkes, N. S.; Mikut, R.; Hilbert, L.
2021. Scientific reports, 11 (1), Art.-Nr.: 14497. doi:10.1038/s41598-021-93913-2

atlite: A Lightweight Python Package for Calculating Renewable Power Potentials and Time Series
Hofmann, F.; Hampp, J.; Neumann, F.; Brown, T.; Hörsch, J.
2021. The journal of open source software, 6 (62), Art.-Nr.: 3294. doi:10.21105/joss.03294

Design of transformation initiatives implementing organisational agility: an empirical study
Kovynyov, I.; Buerck, A.; Mikut, R.
2021. SN Business & Economics, 1 (6), Art.-Nr.: 79. doi:10.1007/s43546-021-00073-6

Long photoperiod impairs learning in male but not female medaka
López-Olmeda, J. F.; Zhao, H.; Reischl, M.; Pylatiuk, C.; Lucon-Xiccato, T.; Loosli, F.; Foulkes, N. S.
2021. iScience, 24 (7), Art. Nr.: 102784. doi:10.1016/j.isci.2021.102784

Smart agriculture
Beyerer, J.; Bretthauer, G.; Längle, T.
2021. Automatisierungstechnik, 69 (4), 275–277. doi:10.1515/auto-2021-2049

Softwarezuverlässigkeit - Software Reliability
Keller, H.
2021. VDI-Richtlinien, VDI 4011

Introduction of the technical diving method for scientific diving to investigate biocoenosis in the twilight zone of freshwater lakes
Brümmer, F.; Remmers, D.; Müller, R.-W.; Scholz, S.
2021. Freiberg online geoscience, 58, 46–53

Structural analysis of a genetically encoded fret biosensor by SAXS and MD simulations
Reinartz, I.; Sarter, M.; Otten, J.; Höfig, H.; Pohl, M.; Schug, A.; Stadler, A. M.; Fitter, J.
2021. Sensors, 21 (12), Art.Nr. 4144. doi:10.3390/s21124144

Advanced Methods for Kiln-Shell Monitoring to Optimize the Waelz Process for Zinc Recycling
Vogelbacher, M.; Keller, S.; Zehm, W.; Matthes, J.
2021. Processes, 9 (6), 1062. doi:10.3390/pr9061062

I-care-an interaction system for the individual activation of people with dementia
Schultz, T.; Putze, F.; Steinert, L.; Mikut, R.; Depner, A.; Kruse, A.; Franz, I.; Gaerte, P.; Dimitrov, T.; Gehrig, T.; Lohse, J.; Simon, C.
2021. Geriatrics (Switzerland), 6 (2), 51. doi:10.3390/geriatrics6020051

Designing Inherently Photodegradable Cell‐Adhesive Hydrogels for 3D Cell Culture
Rosenfeld, A.; Göckler, T.; Kuzina, M.; Reischl, M.; Schepers, U.; Levkin, P. A.
2021. Advanced healthcare materials, 10 (16), Art.Nr. 2100632. doi:10.1002/adhm.202100632

Decreasing market value of variable renewables can be avoided by policy action
Brown, T.; Reichenberg, L.
2021. Energy economics, 100, Article: 105354. doi:10.1016/j.eneco.2021.105354

Simulation and evaluation of a body energy harvesting device for arm and leg swing motions
Petani, L.; Essig, S.; Zeilfelder, J.; Kortenhaus, M.; Pylatiuk, C.
2021. AIP Advances, 11 (6), 065201. doi:10.1063/5.0050424

Evaluation of four point cloud similarity measures for the use in autonomous driving
Berens, F.; Elser, S.; Reischl, M.
2021. Automatisierungstechnik, 69 (6), 499–510. doi:10.1515/auto-2020-0140

Performance of Different Diagnostic PD-L1 Clones in Head and Neck Squamous Cell Carcinoma
Ribbat-Idel, J.; Dressler, F. F.; Krupar, R.; Watermann, C.; Paulsen, F.-O.; Kuppler, P.; Klapper, L.; Offermann, A.; Wollenberg, B.; Rades, D.; Laban, S.; Reischl, M.; Bruchhage, K.-L.; Idel, C.; Perner, S.
2021. Frontiers in Medicine, 8, Art.-Nr.: 640515. doi:10.3389/fmed.2021.640515

Mitigating heat demand peaks in buildings in a highly renewable European energy system
Zeyen, E.; Hagenmeyer, V.; Brown, T.
2021. Energy, 231, Artice: 120784. doi:10.1016/j.energy.2021.120784

Unveiling local atomic bonding and packing of amorphous nanophases via independent component analysis facilitated pair distribution function
Mu, X.; Chen, L.; Mikut, R.; Hahn, H.; Kübel, C.
2021. Acta materialia, 212, Article: 116932. doi:10.1016/j.actamat.2021.116932

Novel Control-Oriented Models for Liquid Transport in Falling Film Evaporator Tubes
Ponomarev, A.; Hofmann, J.; Gröll, L.
2021. Computers & chemical engineering, 152, Article no: 107376. doi:10.1016/j.compchemeng.2021.107376

Two-stage mechanism design for energy trading of strategic agents in energy communities
Khorasany, M.; Razzaghi, R.; Shokri Gazafroudi, A.
2021. Applied Energy, 295, Art.-Nr.: 117036. doi:10.1016/j.apenergy.2021.117036

Burst of corneal dendritic cells during Trastuzumab and Paclitaxel treatment
Sterenczak, K. A.; Stache, N.; Bohn, S.; Allgeier, S.; Köhler, B.; Bartschat, A.; George, C.; Guthoff, R. F.; Stachs, O.; Stachs, A.
2021. Diagnostics, 11 (5), Art.Nr. 838. doi:10.3390/diagnostics11050838

Partially distributed outer approximation
Murray, A.; Faulwasser, T.; Hagenmeyer, V.; Villanueva, M. E.; Houska, B.
2021. Journal of Global Optimization, 80 (3), 523–550. doi:10.1007/s10898-021-01015-0

Development of an Efficient Prediction Model for Optimal Design of Serial Production Lines
Alkhalefah, H.; Abu Qudeiri, J. E.; Umer, U.; Abidi, M. H.; Elkaseer, A.
2021. IEEE Access, 9, 61807–61818. doi:10.1109/ACCESS.2021.3074356

Costs of regional equity and autarky in a renewable European power system
Neumann, F.
2021. Energy strategy reviews, 35, Article no: 100652. doi:10.1016/j.esr.2021.100652

Morphological characterization of the human corneal epithelium by in vivo confocal laser scanning microscopy
Sterenczak, K. A.; Winter, K.; Sperlich, K.; Stahnke, T.; Linke, S.; Farrokhi, S.; Klemm, M.; Allgeier, S.; Köhler, B.; Reichert, K.-M.; Guthoff, R. F.; Bohn, S.; Stachs, O.
2021. Quantitative imaging in medicine and surgery, 11 (5), 1737–1750. doi:10.21037/qims-20-1052

Distributed power flow and distributed optimization – formulation, solution, and open source implementation
Mühlpfordt, T.; Dai, X.; Engelmann, A.; Hagenmeyer, V.
2021. Sustainable energy, grids and networks, 26, Article no: 100471. doi:10.1016/j.segan.2021.100471

Biophotonic sensors with integrated SiN-organic hybrid (SiNOH) lasers for point-of-care diagnostics
Kohler, D.; Schindler, G.; Hahn, L.; Milvich, J.; Hofmann, A.; Länge, K.; Freude, W.; Koos, C.
2021. Light: Science and Applications, 10 (1), Art.-Nr.: 64. doi:10.1038/s41377-021-00486-w

Detektion und Tracking von Brennstoffpartikeln auf Basis eines Lichtfeldkamerasystems = Detection and tracking of refuse-derived fuel particles based on a light field camera system
Zhang, M.; Matthes, J.; Aleksandrov, K.; Gehrmann, H.-J.; Vogelbacher, M.
2021. Technisches Messen, 88 (6), 396–407. doi:10.1515/teme-2021-0016

The strong effect of network resolution on electricity system models with high shares of wind and solar
Frysztacki, M. M.; Hörsch, J.; Hagenmeyer, V.; Brown, T.
2021. Applied energy, 291, Article: 116726. doi:10.1016/j.apenergy.2021.116726

A Review of Rule Learning Based Intrusion Detection Systems and Their Prospects in Smart Grids
Liu, Q.; Hagenmeyer, V.; Keller, H. B.
2021. IEEE access, 9, 57542–57564. doi:10.1109/ACCESS.2021.3071263

Enhancing deep-learning training for phase identification in powder X-ray diffractograms
Schuetzke, J.; Benedix, A.; Mikut, R.; Reischl, M.
2021. IUCrJ, 8 (3). doi:10.1107/S2052252521002402

Energy-based stochastic MPC for integrated electricity-hydrogen VPP in real-time markets
Appino, R. R.; Wang, H.; González Ordiano, J. Á.; Faulwasser, T.; Mikut, R.; Hagenmeyer, V.; Mancarella, P.
2021. Electric power systems research, ^95, Art.Nr. 106738. doi:10.1016/j.epsr.2020.106738

Energy Pulsation Reduction in Modular Multilevel Converters Using Optimized Current Trajectories
Bräckle, D.; Himmelmann, P.; Gröll, L.; Hagenmeyer, V.; Hiller, M.
2021. IEEE Open Journal of Power Electronics, 2, 171–186. doi:10.1109/OJPEL.2021.3065115

Towards Optimality Preserving Aggregation for Scheduling Distributed Energy Resources
Appino, R. R.; Hagenmeyer, V.; Faulwasser, T.
2021. IEEE transactions on control of network systems, 8 (3), 1477–1488. doi:10.1109/TCNS.2021.3070664

Evaluation of Deep Learning-Based Segmentation Methods for Industrial Burner Flames
Großkopf, J.; Matthes, J.; Vogelbacher, M.; Waibel, P.
2021. Energies, 14 (6), 1716. doi:10.3390/en14061716

Effect of different cooling strategies on surface quality and power consumption in finishing end milling of stainless steel 316
Abbas, A. T.; Anwar, S.; Abdelnasser, E.; Luqman, M.; Abu Qudeiri, J. E.; Elkaseer, A.
2021. Materials, 14 (4), Art. Nr.: 903. doi:10.3390/ma14040903

Identification based thermal reflection compensation for radiation based temperature measurements in combustion chambers
Matthes, J.; Vogelbacher, M.; Waibel, P.; Gröll, L.
2021. Experimental thermal and fluid science, 125, Art.Nr. 110354. doi:10.1016/j.expthermflusci.2021.110354

Enhancement of High-Resolution 3D Inkjet-rinting of Optical Freeform Surfaces Using Digital Twins
Sieber, I.; Thelen, R.; Gengenbach, U.
2021. Micromachines, 12 (1), Art.-Nr.: 35. doi:10.3390/mi12010035

Analysis of Oscillating Combustion for NOx-Reduction in Pulverized Fuel Boilers
Jolibois, N.; Aleksandrov, K.; Hauser, M.; Stapf, D.; Seifert, H.; Matthes, J.; Waibel, P.; Vogelbacher, M.; Keller, H. B.; Gehrmann, H.-J.
2021. Inventions, 6 (9), Article no: 9. doi:10.3390/inventions6010009

Atypical cellular elements of unknown origin in the subbasal nerve plexus of a diabetic cornea diagnosed by large-area confocal laser scanning microscopy
Sterenczak, K. A.; Stachs, O.; Marfurt, C.; Matuszewska-Iwanicka, A.; Stratmann, B.; Sperlich, K.; Guthoff, R. F.; Hettlich, H.-J.; Allgeier, S.; Stahnke, T.
2021. Diagnostics, 11 (2), Article no: 154. doi:10.3390/diagnostics11020154

Parkinson’s disease with restless legs syndrome - an in vivo corneal confocal microscopy study
Andréasson, M.; Lagali, N.; Badian, R. A.; Utheim, T. P.; Scarpa, F.; Colonna, A.; Allgeier, S.; Bartschat, A.; Köhler, B.; Mikut, R.; Reichert, K.-M.; Solders, G.; Samuelsson, K.; Zetterberg, H.; Blennow, K.; Svenningsson, P.
2021. npj Parkinson’s Disease, 7 (1), Art.-Nr. 4. doi:10.1038/s41531-020-00148-5

A Novel Receiver Design for Energy Packet‐Based Dispatching
Wiegel, F.; De Din, E.; Monti, A.; Wehrle, K.; Hiller, M.; Zitterbart, M.; Hagenmeyer, V.
2021. Energy technology, 9 (2), Art.-Nr. 2000937. doi:10.1002/ente.202000937

Night-to-Day: Online Image-to-Image Translation for Object Detection Within Autonomous Driving by Night
Schutera, M.; Hussein, M.; Abhau, J.; Mikut, R.; Reischl, M.
2021. IEEE Transactions on Intelligent Vehicles, 6 (3), 480–489. doi:10.1109/TIV.2020.3039456

Cuepervision: self-supervised learning for continuous domain adaptation without catastrophic forgetting
Schutera, M.; Hafner, F. M.; Abhau, J.; Hagenmeyer, V.; Mikut, R.; Reischl, M.
2021. Image and vision computing, 106, Article no: 104079. doi:10.1016/j.imavis.2020.104079

epiTracker: A Framework for Highly Reliable Particle Tracking for the Quantitative Analysis of Fish Movements in Tanks
Bruch, R.; Scheikl, P. M.; Mikut, R.; Loosli, F.; Reischl, M.
2021. SLAS technology, 26 (4), 367–376. doi:10.1177/2472630320977454

Mitigating heat demand peaks in buildings in a highly renewable European energy system
Zeyen, E.; Hagenmeyer, V.; Brown, T.
2021. Applied energy, 231, Art.Nr. 120784

Miniaturized Drug Sensitivity and Resistance Test on Patient-Derived Cells Using Droplet-Microarray
Popova, A. A.; Dietrich, S.; Huber, W.; Reischl, M.; Peravali, R.; Levkin, P. A.
2021. SLAS technology, 26 (3), 274–286. doi:10.1177/2472630320934432

The near-optimal feasible space of a renewable power system model
Neumann, F.; Brown, T.
2021. Electric power systems research, 190, Art.Nr. 106690. doi:10.1016/j.epsr.2020.106690

Efficient Optimization Model for Buffer Size Problem in Production Line with Rework Path
Alkhalefah, H.; Abidi, M. H.; Umer, U.; Elkaseer, A.
2021. Proceedings 4th European International Conference on Industrial Engineering and Operations Management, IEOM 2021: 2-5 August 2021, Virtual. Ed.: M. Fargnoli, 2539–2551, IEOM Society International

Development of an Optimization Model for Multiple Production Systems with Split and Merge
Alkhalefah, H.; Abidi, M. H.; Umer, U.; Elkaseer, A.
2021. Proceedings of the International Conference on Industrial Engineering and Operations Management: Bangalore, India, August 16-18, 2021, 784–794, IEOM Society International

A Benchmark for Parking Duration Prediction of Electric Vehicles for Smart Charging Applications
Schwenk, K.; Phipps, K.; Briegel, B.; Hagenmeyer, V.; Mikut, R.
2021. 2021 IEEE Symposium Series on Computational Intelligence (SSCI), Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SSCI50451.2021.9660063

IFC-Roundtrip mit Plangrafiken
Geiger, A.; Eichler, C.; Fritzenwallner, R.; Häfele, K.-H.
2021. 32. Forum Bauinformatik, Darmstadt, 09.-10. September 2021

Quality Check of openBIM Input Data for Thermal Building Simulation based on mvdXML
Geiger, A.; Häfele, K.-H.; Hagenmeyer, V.
2021. Proceedings of Building Simulation 2021: 17th Conference of IBPSA, 1671–1678, International Building Performance Simulation Association (IBPSA). doi:10.26868/25222708.2021.30501

Supporting the Information Search and Discovery Process with the Bash-Shell
Schmidt, A.
2021. Research Challenges in Information Science. Ed.: S. Cherfi, Springer Nature Switzerland

Enabling Sustainability-Driven Control Strategies in Multimodal Energy Systems Simulations
Erdmann, A.; Kyesswa, M.; Çakmak, H. K.; Hagenmeyer, V.
2021. IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe), 937–942, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEurope52324.2021.9639920

Smart Data Representations: Impact on the Accuracy of Deep Neural Networks
Neumann, O.; Turowski, M.; Ludwig, N.; Heidrich, B.; Hagenmeyer, V.; Mikut, R.
2021. Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 113–130, KIT Scientific Publishing

A Lightweight User Interface for Smart Charging of Electric Vehicles: A Real-World Application
Meisenbacher, S.; Schwenk, K.; Galenzowski, J.; Waczowicz, S.; Mikut, R.; Hagenmeyer, V.
2021. 2021 9th International Conference on Smart Grid and Clean Energy Technologies (ICSGCE), 57–61, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICSGCE52779.2021.9621604

Concepts for Automated Machine Learning in Smart Grid Applications
Meisenbacher, S.; Pinter, J.; Martin, T.; Hagenmeyer, V.; Mikut, R.
2021. Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 11–35, KIT Scientific Publishing

Quantification Platform for Touch Response of Zebrafish Larvae using Machine Learning
Wang, Y.; Pylatiuk, C.; Mikut, R.; Peravali, R.; Reischl, M.
2021. Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021. Hrsg.: H. Schulte, Horst; F. Hoffmann; R. Mikut, 37–54, KIT Scientific Publishing

Experimentelle Absicherung von CFD-Modellen für die thermische Umsetzung von Ersatzbrennstoffen (FLUFF)
Wirtz, S.; Scherer, V.; Aleksandrov, K.; Gehrmann, H.-J.; Stapf, D.; Zhang, M.; Vogelbacher, M.; Matthes, J.
2021. 30. Deutscher Flammentag / Deutsche Sektion des Combustion Institutes und DVV/VDI-Gesellschaft Energie und Umwelt. Ed.: F. Dinkelacker, Deutsche Vereinigung für Verbrennungsforschung e.V

Ratio-based features for data-driven bridge monitoring and damage detection
Döring, A.; Waibel, P.; Matthes, J.; Scherer, O.; Keller, H. B.; Keller, S.; Müller, J.; Schneider, O.
2021. Bridge Maintenance, Safety, Management, Life-Cycle Sustainability and Innovations. Ed.: H. Yokota, 2532–2541, CRC Press. doi:10.1201/9780429279119-346

Label Assistant: A Workflow for Assisted Data Annotation in Image Segmentation Tasks
Schilling, M. P.; Rettenberger, L.; Münke, F.; Cui, H.; Popova, A. A.; Levkin, P. A.; Mikut, R.; Reischl, M.
2021. Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021. Hrsg.: H. Schulte; F. Hoffmann; R. Mikut, 211–234, KIT Scientific Publishing

Case Study of Designing a Locally Distributed Real-Time Infrastructure
Weber, M.; Kyesswa, M.; Kühnapfel, U.; Hagenmeyer, V.; Çakmak, H. K.
2021. IEEE Toronto Section, 20 th- 21st October 2021, 310–315, IEEEXplore. doi:10.1109/EPEC52095.2021.9621665

Designing the Interplay of Energy Plane and Communication Plane in the Energy Packet Grid
Schneider, K.; Wiegel, F.; Schulz, D.; Hagenmeyer, V.; Hiller, M.; Bless, R.; Zitterbart, M.
2021. 2021 IEEE 46th Conference on Local Computer Networks (LCN), 331–334, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/LCN52139.2021.9525020

An evaluation of graph algorithms for the wind farm cable layout problem under electrical aspects
Gritzbach, S.; Cakmak, H.; Mehnert, P.; Ueckerdt, T.; Hagenmeyer, V.
2021. 2021 56th International Universities Power Engineering Conference (UPEC): 31 Aug.-3 Sept. 2021, online, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/UPEC50034.2021.9548251

Mathematical Model for Agent-based Local Energy Exchange Engine (D3A)
Gazafroudi, A. S.; Okwuibe, G. C.; Hambridge, S.; Dietrich, C.; Trbovich, A.; Tzscheutschler, P.; Hamacher, T.; Shafie-khah, M.
2021. SEST’21: 4th International Conference on Smart Energy Systems and Technologies ; 6-8 September 2021. Ed.: IEEE, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEST50973.2021.9543262

Approaches towards Resource-saving and Explainability/Transparency of Deep-learning-based Image Classification in Industrial Applications
Rieder, C.; Germann, M.; Mezger, S.; Scherer, K.
2021. Proceedings of the 2nd International Conference on Deep Learning Theory and Applications. Ed.: A. Fred, 164–169, SciTePress. doi:10.5220/0010575901640169

Effect of build platform location and part orientation on dimensional accuracy of downfacing surfaces in LPBF
Charles, A.; Elkaseer, A.; Thijs, L.; Scholz, S.
2021. Proceedings of the World Congress on Micro and Nano Manufacturing 2021, Bringing together the worldwide community of micro- & nano-manufacturing experts, 20-23 September 2021, IIT Bombay, Mumbai, India, Taylor and Francis

Geometrical-based Simulation of Drop-on-Demand 3D Inkjet Printing
Elkaseer, A.; Schneider, S.; Scholz, S.
2021. Proceedings of the World Congress on Micro and Nano Manufacturing 2021: bringing together the worldwide community of micro- & nano-manufacturing experts, 20-23 September 2021, IIT Bombay, Mumbai, India

Adaptive Feedforward Control for DC/DC Converters in Microgrids - A Power Hardware in the Loop Study
Wachter, J.; Gröll, L.; Hagenmeyer, V.
2021. 9th International Conference on Smart Grid (icSmartGrid), 29th June - 01st July 2021, Sebútal, Portugal, 49–56, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/icSmartGrid52357.2021.9551250

Comparing Time Series Classification and Forecasting to Automatically Detect Distributed Generation
Petrusev, A.; Bauer, R.; Rigo-Mariani, R.; Debusschere, V.; Reignier, P.; Hadjsaid, N.
2021. 2021 IEEE Madrid PowerTech: Conference Proceedings ; 28 June-2 July 2021, online, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PowerTech46648.2021.9494895

A Bayesian Rule Learning Based Intrusion Detection System for the MQTT Communication Protocol
Liu, Q.; Keller, H. B.; Hagenmeyer, V.
2021. ARES 2021 : the 16th International Conference on Availability, Reliability and Security, Wien, A, August 17-20, 2021, Article no: 81, Association for Computing Machinery (ACM). doi:10.1145/3465481.3470046

The effects of pattern screen surface deformation on deflectometric measurements - A simulation study
Allgeier, S.; Gengenbach, U.; Köhler, B.; Reichert, K.-M.; Hagenmeyer, V.
2021. Automated Visual Inspection and Machine Vision IV: SPIE Optical Metrology, 21-26 June 2021. Ed.: J. Beyerer, Art.-Nr.: 1178708, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2591877

Modeling of a distillation column without measurement data
Schaßberger, J.; Hagenmeyer, V.; Gröll, L.
2021. Internatiional Scientific Conference on Control Processes and Stability, 167–173, Publishing House Fedorova G.V

Smart Charging of Electric Vehicles with Cloud-based Optimization and a Lightweight User Interface – A Real-World Application in the Energy Lab 2.0: Poster
Meisenbacher, S.; Schwenk, K.; Galenzowski, J.; Waczowicz, S.; Mikut, R.; Hagenmeyer, V.
2021. e-Energy ’21: The Twelfth ACM International Conference on Future Energy Systems Virtual Event Italy 28 June 2021- 2 July 2021, 284–285, Association for Computing Machinery (ACM). doi:10.1145/3447555.3466571

Energy Hub Gas : A Multi-Domain System Modelling and Co-Simulation Approach
Poppenborg, R.; Ruf, J.; Chlosta, M.; Liu, J.; Hotz, C.; Düpmeier, C.; Kolb, T.; Hagenmeyer, V.
2021. Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES ’21), Art.Nr. 12, Association for Computing Machinery (ACM). doi:10.1145/3470481.3472712

Control Loop Pairing and Interaction Analyses of the Falling Film Evaporator Process
Hofmann, J.; Gröll, L.; Hagenmeyer, V.
2021. Proceedings of the 23rd International Conference on Process Control, 2021. Ed.: R. Paulen, 186–193, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PC52310.2021.9447487

Realtime Testbench for Inverters - A Sliding Mode Control Experiment
Wachter, J.; Gröll, L.; Hagenmeyer, V.
2021. 52th International Scientific Conference on Control Processes and Stability (CPS’21), St. Petersburg, RUS, April 5-9, 2021, 93–99, Publishing House Fedorova G.V

Abstractions in Modeling of Switching DC/AC Power Converters
Kastner, A.; Gröll, L.; Hagenmeyer, V.
2021. Control Processes and Stability : Proceedings of the LII International Conference. St. Petersburg April 5–9, 2021. Ed.: N. Smirnov, 85–92, Publishing House Fedorova G.V

Radar Artifact Labeling Framework (RALF): Method for Plausible Radar Detections in Datasets
Isele, S.; Schilling, M.; Klein, F.; Saralajew, S.; Zoellner, J.
2021. Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS), April 28-30, 2021, 22–33, SciTePress. doi:10.5220/0010395100220033

Introduction of the technical diving method for scientific diving to investigate biocoenosis in the twilight zone of freshwater lakes
Brümmer, F.; Remmers, D.; Müller, R.-W.; Scholz, S.
2021. 6th European Conference on Scientific Diving - TU Bergakademie Freiberg

On Optimal Grid Partitioning for Distributed Optimization of Reactive Power Dispatch
Murray, A.; Kyesswa, M.; Çakmak, H.; Hagenmeyer, V.
2021. IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 16-18 February, 2021, Washington, DC, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT49243.2021.9372275

A Generic Scalable Method for Scheduling Distributed Energy Resources Using Parallelized Population-Based Metaheuristics
Khalloof, H.; Jakob, W.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2021. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2. Ed.: K. Arai, 1–21, Springer Nature. doi:10.1007/978-3-030-63089-8_1

Incorporating Unsupervised Deep Learning into Meta Learning for Energy Time Series Forecasting
Shahoud, S.; Khalloof, H.; Duepmeier, C.; Hagenmeyer, V.
2021. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. Ed.: K. Arai, 326–345, Springer Nature. doi:10.1007/978-3-030-63128-4_25

Additive Manufacturing: Comparative Study of an IoT Integrated Approach and a Conventional Solution
Shandilya, H.; Kuchta, M.; Elkaseer, A.; Müller, T.; Scholz, S. G.
2021. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 2. Ed.: K. Arai, 976–986, Springer International Publishing. doi:10.1007/978-3-030-63089-8_64

The Thirteenth International Conference on Advances in Databases, Knowledge, and Data Applications (DBKDA 2021)
Crowe, M.; Laux, F.; Schmidt, A.; Dini, C. (Eds.)
2021. International Academy Research and Industry Association (IARIA)

Proceedings - 31. Workshop Computational Intelligence : Berlin, 25. - 26. November 2021
Schulte, H.; Hoffmann, F.; Mikut, R. (Eds.)
2021. KIT Scientific Publishing. doi:10.5445/KSP/1000138532

DiversityScanner
Wührl, L.; Pylatiuk, C.
2021, May 20

Methoden, Materialien und Ergebnisse der Entwicklung funktionaler Druckprozesse. Zusätzliche Daten zur Dissertation "Neue Methodik zur Optimierung von Druckverfahren für die Herstellung funktionaler Mikrostrukturen und hybrider elektronischer Schaltungen"
Ungerer, M.
2021, March 2. doi:10.5445/IR/1000099352

Data on the Safety of Innovative Materials – DaNa4.0
Katja Nau, Clarissa Marquardt, Dana Kühnel, Andreas Mattern, Sara Espinoza, Harald Krug, Christoph Steinbach
2021, December

Daten zur Sicherheit von innovativen Materialien – DaNa4.0
Nau, K.; Marquardt, C.; Kühnel, D.; Mattern, A.; Espinoza, S.; Krug, H.; Steinbach, C.
2021, December

„Nicht mehr von Hand“ – der Campus Nord des KIT wird zum Reallabor für die automatisierte Steuerung einer CO2-freien Energieversorgung - Campus-Report am 26.10.2021
Fuchs, S.; Duepmeier, C.
2021. doi:10.5445/IR/1000139471

„Kein Nutzen für Verbraucher und Umwelt“ - IT-Sicherheitsexperte am Karlsruher Institut für Technologie warnt vor digitalen Stromzählern - Campus-Report am 20.04.2021
Fuchs, S.; Keller, H.
2021. doi:10.5445/IR/1000131717

„Bashing“ the Killer from the Command Line
Schmidt, A.; Ehrlinger, L.; Laux, F.
2021, May 30

Ontology-Enhanced Machine Learning : A Bosch Use Case of Welding Quality Monitoring
Svetashova, Y.; Zhou, B.; Pychynski, T.; Schmidt, S.; Sure-Vetter, Y.; Mikut, R.; Kharlamov, E.
2020. The Semantic Web - ISWC 2020 : 19th International Semantic Web Conference, Athens, Greece, November 2–6, 2020, Proceedings, Part II. Ed.: J. Pan, 531–550, Springer International Publishing. doi:10.1007/978-3-030-62466-8_33

Stakeholder-Driven Conceptualization of Open Innovation Approaches in the SYNERGY Project
Fauth, J.; Marquardt, C.; Di Bari, G.; Raule, N.; Ronco, J. L.; Scholz, S. G.
2020. Sustainable Design and Manufacturing 2020 – Proceedings of the 7th International Conference on Sustainable Design and Manufacturing (KES-SDM 2020). Ed.: S. Scholz, 307–317, Springer. doi:10.1007/978-981-15-8131-1_28

Development of Precision Additive Manufacturing Processes
Elkaseer, A.; Charles, A. P.; Scholz, S. G.
2020. Precision additive metal manufacturing. Ed.: R. Leach, 35–68, CRC Press. doi:10.1201/9780429436543-3

A low-tech Approach to Serial Section Arrays
Spomer, W.; Hofmann, A.; Veit, L.; Gengenbach, U.
2020. Volume Microscopy. Hrsg.: I. Wacker, 79–96, Springer US. doi:10.1007/978-1-0716-0691-9_5

Echtzeit-Monitoring und Optimierung der Sinterzone in Zementdrehrohröfen zur Stabilisierung der Klinkerqualität bei veränderlicher Zusammensetzung der Ersatzbrennstoffe
Hoyer, M.; Melerski, R.; Dittrich, A.; Vogelbacher, M.; Matthes, J.; Keller, H. B.
2020. Energie aus Abfall. Hrsg.: S. Thiel. Band 17, 773–786, Thomé-Kozmiensky Verlag (TK)

Software Toolkit for Visualization and Process Selection for Modular Scalable Manufacturing of 3D Micro-Devices
Scholz, S.; Elkaseer, A.; Salem, M.; Hagenmeyer, V.
2020. Information Systems Architecture and Technology: Proceedings of 40th Anniversary International Conference on Information Systems Architecture and Technology – ISAT 2019. Ed.: L. Borzemski, 160–172, Springer International Publishing. doi:10.1007/978-3-030-30440-9_16

GML-Toolbox 11.1 : Benutzerhandbuch - Datum: März 2020
Benner, J.
2020. Karlsruher Institut für Technologie (KIT)

Ein neues Konzept für die Optimierung intelligenter Aktoren im Bereich beweglicher elektrischer Verbraucher. PhD dissertation
Manz, F.
2020, December 21. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000127792

Microservice-based Reference Architecture for Semantics-aware Measurement Systems. PhD dissertation
Braun, E.
2020, November 17. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000125950

Data-Driven Methods for Demand-Side Flexibility in Energy Systems. PhD dissertation
Ludwig, N. N.
2020, September 30. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000123985

Ein neues Konzept für eine serviceorientierte Datenhaltungsplattform für Lebenszyklusdaten. PhD dissertation
Kusche, O.
2020, May 22. Karlsruher Institut für Technologie (KIT)

Entwicklung eines neuen Konzeptes für die Nutzung des Pupillennahreflexes für das Künstliche Akkommodationssystem. PhD dissertation
Rothmund, J.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000105311

Uncertainty Quantification via Polynomial Chaos Expansion – Methods and Applications for Optimization of Power Systems. PhD dissertation
Mühlpfordt, T.
2020. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000104661

IBEET-RSA: Identity-Based Encryption with Equality Test over RSA for Wireless Body Area Networks
Ramadan, M.; Liao, Y.; Li, F.; Zhou, S.; Abdalla, H.
2020. Mobile Networks and Applications, 25 (1), 223–233. doi:10.1007/s11036-019-01215-9

Approaches for Solution-Processed Encapsulation of Printed Medical Wearable Devices
Chen, Z.; Gengenbach, U.; Koker, L.; Mansour, M.
2020. Current directions in biomedical engineering, 6 (3), 131–134. doi:10.1515/cdbme-2020-3034

Dynamic modelling and control for assessment of large-scale wind and solar integration in power systems
Kyesswa, M.; Çakmak, H.; Kühnapfel, U.; Hagenmeyer, V.
2020. IET Renewable Power Generation, 14 (19), 4010–4018. doi:10.1049/iet-rpg.2020.0458

Unconventional monetary policy in a nonlinear quadratic model
Faulwasser, T.; Gross, M.; Semmler, W.; Loungani, P.
2020. Studies in nonlinear dynamics and econometrics, 24 (5), Art.-Nr.: 20190099. doi:10.1515/snde-2019-0099

3D Imaging Technique for High-Resolution Slit Lamp Microscopy in Ophthalmology
Kornelius, L.; Allgeier, S.; Bohn, S.; Reichert, K.-M.; Sperlich, K.; Stachs, O.; Köhler, B.
2020. Biomedical engineering, 65 (s1), S126

Evaluation of semi-supervised learning using sparse labeling to segment cell nuclei
Bruch, R.; Rudolf, R.; Mikut, R.; Reischl, M.
2020. Current directions in biomedical engineering, 6 (3), Art.Nr. 20203103. doi:10.1515/cdbme-2020-3103

Precision hard turning of ti6al4v using polycrystalline diamond inserts: Surface quality, cutting temperature and productivity in conventional and high-speed machining
Abdelnasser, E.; Barakat, A.; Elsanabary, S.; Nassef, A.; Elkaseer, A.
2020. Materials, 13 (24), Art.Nr. 5677. doi:10.3390/ma13245677

Cell segmentation and tracking using CNN-based distance predictions and a graph-based matching strategy
Scherr, T.; Löffler, K.; Böhland, M.; Mikut, R.
2020. PLOS ONE, 15 (12), Art. Nr.: e0243219. doi:10.1371/journal.pone.0243219

In vivo Histology of the Cornea – from the “Rostock Cornea Module” to the “Rostock Electronic Slit Lamp” – a Clinical “Proof of Concept” Study
Bohn, S.; Stahnke, T.; Sperlich, K.; Linke, S. J.; Farrokhi, S.; Klemm, M.; Allgeier, S.; Köhler, B.; Reichert, K.-M.; Witt, M.; Stachs, O.; Guthoff, R. F.
2020. Klinische Monatsblätter für Augenheilkunde, 237 (12), 1442–1454. doi:10.1055/a-1297-4717

Comparative evaluation of surface quality, tool wear, and specific cutting energy for wiper and conventional carbide inserts in hard turning of aisi 4340 alloy steel
Abbas, A. T.; Anwar, S.; Hegab, H.; Benyahia, F.; Ali, H.; Elkaseer, A.
2020. Materials, 13 (22), Art.-Nr.: 5233. doi:10.3390/ma13225233

Open database analysis of scaling and spatio-temporal properties of power grid frequencies
Rydin Gorjão, L.; Jumar, R.; Maass, H.; Hagenmeyer, V.; Yalcin, G. C.; Kruse, J.; Timme, M.; Beck, C.; Witthaut, D.; Schäfer, B.
2020. Nature Communications, 11 (1), Art.-Nr. 6362. doi:10.1038/s41467-020-19732-7

Early decarbonisation of the European energy system pays off
Victoria, M.; Zhu, K.; Brown, T.; Andresen, G. B.; Greiner, M.
2020. Nature Communications, 11 (1), Art.-Nr. 6223. doi:10.1038/s41467-020-20015-4

SemML: Reusable ML for condition monitoring in discrete manufacturing
Svetashova, Y.; Zhou, B.; Schmid, S.; Pychinsky, T.; Kharlamov, E.
2020. CEUR workshop proceedings, 2721, 214–218

Semantic ML for manufacturing monitoring at Bosch
Zhou, B.; Svetashova, Y.; Pychynski, T.; Kharlamov, E.
2020. CEUR workshop proceedings, 2721, 397–398

Impact of grid partitioning algorithms on combined distributed AC optimal power flow and parallel dynamic power grid simulationn
Kyesswa, M.; Murray, A.; Schmurr, P.; Cakmak, H.; Kühnapfel, U.; Hagenmeyer, V.
2020. IET generation, transmission and distribution, 14 (25), 6133–6141. doi:10.1049/iet-gtd.2020.1393

On modelling effects in the battery and thermal storage scheduling problem
Murray, A.; Schütz, T.; Pan, G.; Müller, D.; Hagenmeyer, V.
2020. Journal of building performance simulation, 14 (1), 38–51. doi:10.1080/19401493.2020.1838611

MondoA regulates gene expression in cholesterol biosynthesis-associated pathways required for zebrafish epiboly
Weger, M.; Weger, B. D.; Schink, A.; Takamiya, M.; Stegmaier, J.; Gobet, C.; Parisi, A.; Kobitski, A. Y.; Mertes, J.; Krone, N.; Strähle, U.; Nienhaus, G. U.; Mikut, R.; Gachon, F.; Gut, P.; Dickmeis, T.
2020. eLife, 9, Art. Nr. e57068. doi:10.7554/eLife.57068

Hybrid low-voltage physical unclonable function based on inkjet-printed metal-oxide transistors
Scholz, A.; Zimmermann, L.; Gengenbach, U.; Koker, L.; Chen, Z.; Hahn, H.; Sikora, A.; Tahoori, M. B.; Aghassi-Hagmann, J.
2020. Nature Communications, 11 (1), Art.-Nr. 5543. doi:10.1038/s41467-020-19324-5

Architectured Lattice Materials with Tunable Anisotropy: Design and Analysis of the Material Property Space with the Aid of Machine Learning
Kulagin, R.; Beygelzimer, Y.; Estrin, Y.; Schumilin, A.; Gumbsch, P.
2020. Advanced engineering materials, 22 (12), Art.Nr. 2001069. doi:10.1002/adem.202001069

On complexity reduction of the discrete-event subsystem of Flat Hybrid Automata for control design
Kleinert, T.; Zahn, F.; Hagenmeyer, V.
2020. Automatisierungstechnik, 68 (7), 529–540. doi:10.1515/auto-2020-0061

Opinion Behavior Analysis in Social Networks Under the Influence of Coopetitive Media
Xue, D.; Hirche, S.; Cao, M.
2020. IEEE transactions on network science and engineering, 7 (3), 961–974. doi:10.1109/TNSE.2019.2894565

Zum 80. Geburtstag von Professor Dr.-Ing. habil. Jürgen Wernstedt
Rauschenbach, T.; Bretthauer, G.
2020. Automatisierungstechnik, 68 (8), 705–707. doi:10.1515/auto-2020-0113

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations
Elbez, G.; Keller, H. B.; Bohara, A.; Nahrstedt, K.; Hagenmeyer, V.
2020. Energies, 13 (19), Art.-Nr. 5176. doi:10.3390/en13195176

Grundprinzipien für die Abschätzung von Einzugsbereichen in Totzeitsystemen
Scholl, T. H.; Hagenmeyer, V.; Gröll, L.
2020. Automatisierungstechnik, 68 (8), 667–686. doi:10.1515/auto-2020-0034

An Industry 4.0 framework for tooling production using metal additive manufacturing-based first-time-right smart manufacturing system
Moshiri, M.; Charles, A. P.; Elkaseer, A.; Scholz, S.; Mohanty, S.; Tosello, G.
2020. Procedia CIRP, 93, 32–37. doi:10.1016/j.procir.2020.04.151

Towards an Adaptive Design of Quality, Productivity and Economic Aspects When Machining AISI 4340 Steel With Wiper Inserts
Abbas, A. T.; Abubakr, M.; Elkaseer, A.; El Rayes, M. M.; Mohammed, M. L.; Hegab, H.
2020. IEEE access, 8, 159206–159219. doi:10.1109/ACCESS.2020.3020623

On polynomial real-time control policies in stochastic AC optimal power flow
Mühlpfordt, T.; Faulwasser, T.; Hagenmeyer, V.; Roald, L.; Misra, S.
2020. Electric power systems research, 189, Art.-Nr.: 106792. doi:10.1016/j.epsr.2020.106792

Automated fabrication of hybrid printed electronic circuits
Gengenbach, U.; Ungerer, M.; Koker, L.; Reichert, K.-M.; Stiller, P.; Allgeier, S.; Köhler, B.; Zhu, X.; Huang, C.; Hagenmeyer, V.
2020. Mechatronics, 70, 102403. doi:10.1016/j.mechatronics.2020.102403

GPU-accelerated ray-casting for 3D fiber orientation analysis
Shkarin, R.; Shkarina, S.; Weinhardt, V.; Surmenev, R. A.; Surmeneva, M. A.; Shkarin, A.; Baumbach, T.; Mikut, R.
2020. PLOS ONE, 15 (7), Article: e0236420. doi:10.1371/journal.pone.0236420

Decomposition of non-convex optimization via bi-level distributed ALADIN
Engelmann, A.; Jiang, Y.; Houska, B.; Faulwasser, T.
2020. IEEE transactions on control of network systems, 7 (4), 1848–1858. doi:10.1109/TCNS.2020.3005079

Pax6 organizes the anterior eye segment by guiding two distinct neural crest waves
Takamiya, M.; Stegmaier, J.; Kobitski, A. Y.; Schott, B.; Weger, B. D.; Margariti, D.; Cereceda Delgado, A. R.; Gourain, V.; Scherr, T.; Yang, L.; Sorge, S.; Otte, J. C.; Hartmann, V.; Wezel, J. van; Stotzka, R.; Reinhard, T.; Schlunck, G.; Dickmeis, T.; Rastegar, S.; Mikut, R.; Nienhaus, G. U.; Strähle, U.
2020. PLoS Genetics, 16 (6), Art. Nr.: e1008774. doi:10.1371/journal.pgen.1008774

Erstellung von effektiven Sensibilisierungsmaterialien zur Passwortsicherheit
Mayer, P.; Ballreich, F.; Düzgün, R.; Schwarz, C.; Volkamer, M.
2020. Datenschutz und Datensicherheit, 44 (8), 522–527. doi:10.1007/s11623-020-1318-9

DeepDB – learn from data, not from queries!
Hilprecht, B.; Schmidt, A.; Kulessa, M.; Molina, A.; Kersting, K.; Binnig, C.
2020. Proceedings of the VLDB Endowment, 13 (7), 992–1005. doi:10.14778/3384345.3384349

FE Simulation of Inertia Friction Welding of Similar PVC-PVC and PA6-PA6 Hollow Cylinders for Process Optimization
Kouta, H.; Elsanabary, S.; El Hadek, M.; Elkaseer, A.
2020. Sylwan, 164 (1), 407–428

Transportmodelle für Flüssigkeitsfilme
Hofmann, J.; Ponomarev, A.; Hagenmeyer, V.; Gröll, L.
2020. Automatisierungstechnik, 68 (8), 625–640. doi:10.1515/auto-2020-0016

Eight Weeks Later - The Unprecedented Rise of 3D Printing during the COVID-19 Pandemic : a Case Study, Lessons Learned, and Implications on the Future of Global Decentralized Manufacturing
Mueller, T.; Elkaseer, A.; Charles, A. P.; Fauth, J.; Rabsch, D.; Scholz, A.; Marquardt, C.; Nau, K.; Scholz, S. G.
2020. Applied Sciences, 10 (12), 4135. doi:10.3390/app10124135

FRET Dyes Significantly Affect SAXS Intensities of Proteins
Reinartz, I.; Weiel, M.; Schug, A.
2020. Israel journal of chemistry, 60 (7), 725–734. doi:10.1002/ijch.202000007

A New Synthetic Conduit for the Treatment of Peripheral Nerve Injuries
Uranues, S.; Bretthauer, G.; Tomasch, G.; Rafolt, D.; Nagele-Moser, D.; Berghold, A.; Kleinert, R.; Justich, I.; Waldert, J.; Koch, H.
2020. World journal of surgery, 44, 3373–3382. doi:10.1007/s00268-020-05620-0

BeadNet: Deep learning-based bead detection and counting in low-resolution microscopy images
Scherr, T.; Streule, K.; Bartschat, A.; Böhland, M.; Stegmaier, J.; Reischl, M.; Orian-Rousseau, V.; Mikut, R.
2020. Bioinformatics, 36 (17), 4668–4670. doi:10.1093/bioinformatics/btaa594

Turnpike Properties in Discrete-Time Mixed-Integer Optimal Control
Faulwasser, T.; Murray, A.
2020. IEEE control systems letters, 4 (3), 704–709. doi:10.1109/LCSYS.2020.2988943

Recent Developments in Ozone Sensor Technology for Medical Applications
Petani, L.; Koker, L.; Herrmann, J.; Hagenmeyer, V.; Gengenbach, U.; Pylatiuk, C.
2020. Micromachines, 11 (6), Article: 624. doi:10.3390/mi11060624

The effect of lipidation and glycosylation on short cationic antimicrobial peptides
Grimsey, E.; Collis, D. W. P.; Mikut, R.; Hilpert, K.
2020. Biochimica et biophysica acta / Biomembranes, 1862 (8), Art.Nr.: 183195. doi:10.1016/j.bbamem.2020.183195

Maschinelles Lernen und Künstliche Intelligenz – Eine Revolution in der Automatisierungstechnik oder nur ein Hype?
Mikut, R.
2020. Automatisierungstechnik, 68 (5), 295–300. doi:10.1515/auto-2020-0041

The bioliq® Entrained-Flow Gasifier - A Model for the German Energiewende
Eberhard, M.; Santo, U.; Michelfelder, B.; Günther, A.; Weigand, P.; Matthes, J.; Waibel, P.; Hagenmeyer, V.; Kolb, T.
2020. ChemBioEng reviews, 7 (4), 1–14. doi:10.1002/cben.202000006

A Novel Optimization Method for Urban Resilient and Fair Power Distribution Preventing Critical Network States
Ottenburger, S. S.; Çakmak, H. K.; Jakob, W.; Blattmann, A.; Trybushnyi, D.; Raskob, W.; Kühnapfel, U.; Hagenmeyer, V.
2020. International journal of critical infrastructure protection, 29, Art.Nr. 100354. doi:10.1016/j.ijcip.2020.100354

Data analytics in the electricity sector – A quantitative and qualitative literature review
Scheidt, F. vom; Medinová, H.; Ludwig, N.; Richter, B.; Staudt, P.; Weinhardt, C.
2020. Energy and AI, 1, Article no: 100009. doi:10.1016/j.egyai.2020.100009

Überwachung von Brückeninfrastrukturen : Neuer Ansatz von konventionellen und berührungslosen Sensoren
Keller, S.; Michel, C.; Schneider, O.; Müller, J.; Arnold, M.; Döring, A.; Hoyer, M.; Hinz, S.; Keller, H. B.
2020. Brückenbau, (3), 22–29

Segregation of Dispersed Silica Nanoparticles in Microfluidic Water‐in‐Oil Droplets: A Kinetic Study
Sheshachala, S.; Grösche, M.; Scherr, T.; Hu, Y.; Sun, P.; Bartschat, A.; Mikut, R.; Niemeyer, C. M.
2020. ChemPhysChem, 21 (10), 1070–1078. doi:10.1002/cphc.201901151

Hydrogen refueling station networks for heavy-duty vehicles in future power systems
Rose, P. K.; Neumann, F.
2020. Transportation research / D, 83, Article no: 102358. doi:10.1016/j.trd.2020.102358

Hybrid multi-chip assembly of optical communication engines by in situ 3D nano-lithography
Blaicher, M.; Billah, M. R.; Kemal, J.; Hoose, T.; Marin-Palomo, P.; Hofmann, A.; Kutuvantavida, Y.; Kieninger, C.; Dietrich, P.-I.; Lauermann, M.; Wolf, S.; Troppenz, U.; Moehrle, M.; Merget, F.; Skacel, S.; Witzens, J.; Randel, S.; Freude, W.; Koos, C.
2020. Light, 9 (1), 71. doi:10.1038/s41377-020-0272-5

Assessment of high-resolution 3D printed optics for the use case of rotation optics
Sieber, I.; Thelen, R.; Gengenbach, U.
2020. Optics express, 28 (9), 13423–13431. doi:10.1364/OE.391697

On norm-based estimations for domains of attraction in nonlinear time-delay systems
Scholl, T. H.; Hagenmeyer, V.; Gröll, L.
2020. Nonlinear dynamics, 100, 2027–2045. doi:10.1007/s11071-020-05620-8

On the Assessment of Surface Quality and Productivity Aspects in Precision Hard Turning of AISI 4340 Steel Alloy: Relative Performance of Wiper vs. Conventional Inserts
Abbas, A. T.; El Rayes, M. M.; Luqman, M.; Naeim, N.; Hegab, H.; Elkaseer, A.
2020. Materials, 13 (9), Article: 2036. doi:10.3390/ma13092036

Experiment-Based Process Modeling and Optimization for High-Quality and Resource-Efficient FFF 3D Printing
Elkaseer, A.; Schneider, S.; Scholz, S. G.
2020. Applied Sciences, 10 (8), Article: 2899. doi:10.3390/app10082899

Dimensional Errors Due to Overhanging Features in Laser Powder Bed Fusion Parts Made of Ti-6Al-4V
Charles, A. P.; Elkaseer, A.; Thijs, L.; Scholz, S. G.
2020. Applied Sciences, 10 (7), Article: 2416. doi:10.3390/app10072416

Towards Flexibility Trading at TSO-DSO-Customer Levels: A Review
Khajeh, H.; Laaksonen, H.; Gazafroudi, A. S.; Shafie-khah, M.
2020. Energies, 13 (1), Art. Nr.: 165. doi:10.3390/en13010165

A novel approach to label road defects in video data: semi-automated video analysis
Thumm, J.; Masino, J.; Knoche, M.; Gauterin, F.; Reischl, M.
2020. International journal on smart sensing and intelligent systems, 13 (1), 1–9. doi:10.21307/ijssis-2020-007

Advances in microcellular injection moulding
Llewelyn, G.; Rees, A.; Griffiths, C. A.; Scholz, S. G.
2020. Journal of cellular plastics, 56 (6), 646–674. doi:10.1177/0021955X20912207

Principles and Characteristics of Different EDM Processes in Machining Tool and Die Steels
Abu Qudeiri, J. E.; Zaiout, A.; Mourad, A.-H. I.; Abidi, M. H.; Elkaseer, A.
2020. Applied Sciences, 10 (6), Article no.: 2082. doi:10.3390/app10062082

Robust scheduling of Electric Vehicle Charging in LV Distribution Networks under Uncertainty
Sun, W.; Neumann, F.; Harrison, G. P.
2020. IEEE transactions on industry applications, 56 (5), 5785–5795. doi:10.1109/TIA.2020.2983906

Model compendium, data, and optimization benchmarks for sector-coupled energy systems
Sass, S.; Faulwasser, T.; Hollermann, D. E.; Kappatou, C. D.; Sauer, D.; Schütz, T.; Shu, D. Y.; Bardow, A.; Gröll, L.; Hagenmeyer, V.; Müller, D.; Mitsos, A.
2020. Computers & chemical engineering, 135, Art. Nr.: 106760. doi:10.1016/j.compchemeng.2020.106760

High‐Throughput Screening of Cell Transfection Enhancers Using Miniaturized Droplet Microarrays
Liu, Y.; Tronser, T.; Peravali, R.; Reischl, M.; Levkin, P. A.
2020. Advanced biosystems, 4 (3), 1900257. doi:10.1002/adbi.201900257

Automated high-throughput heartbeat quantification in medaka and zebrafish embryos under physiological conditions
Gierten, J.; Pylatiuk, C.; Hammouda, O. T.; Schock, C.; Stegmaier, J.; Wittbrodt, J.; Gehrig, J.; Loosli, F.
2020. Scientific reports, 10 (1), Article no: 2046. doi:10.1038/s41598-020-58563-w

Variability of running coordination in experts and novices: A 3D uncontrolled manifold analysis
Möhler, F.; Marahrens, S.; Ringhof, S.; Mikut, R.; Stein, T.
2020. European journal of sport science, 20 (9), 1187–1196. doi:10.1080/17461391.2019.1709561

The role of photovoltaics in a sustainable European energy system under variable CO emissions targets, transmission capacities, and costs assumptions
Victoria, M.; Zhu, K.; Brown, T.; Andresen, G. B.; Greiner, M.
2020. Progress in photovoltaics, 28 (6), 483–492. doi:10.1002/pip.3198

A note on efficient computation of privileged directions in modifier adaptation
Singhal, M.; Marchetti, A. G.; Faulwasser, T.; Bonvin, D.
2020. Computers & chemical engineering, 132, Article No.106524. doi:10.1016/j.compchemeng.2019.106524

Modular Simulation Model for Falling Film Evaporators with Novel Approach to Manage Dominant Time-varying Transport Delays
Schwaer, C.; Hofmann, J.; Mühlpfordt, M.; Frank, A.; Gröll, L.
2020. Computers & chemical engineering, 132, Article: 106604. doi:10.1016/j.compchemeng.2019.106604

Probabilistic energy forecasting using the nearest neighbors quantile filter and quantile regression
González Ordiano, J. Á.; Gröll, L.; Mikut, R.; Hagenmeyer, V.
2020. International journal of forecasting, 36 (2), 310–323. doi:10.1016/j.ijforecast.2019.06.003

Comparison of PD-L1 expression between paired cytologic and histologic specimens from non-small cell lung cancer patients
Kuempers, C.; Linde, L. I. S. van der; Reischl, M.; Vogel, W.; Stellmacher, F.; Reck, M.; Heigener, D.; Rabe, K. F.; Kirfel, J.; Perner, S.; Welker, L.
2020. Virchows Archiv, 476, 261–271. doi:10.1007/s00428-019-02632-7

Toward economic NMPC for multistage AC optimal power flow
Faulwasser, T.; Engelmann, A.
2020. Optimal control, applications and methods, 41 (1), 107–127. doi:10.1002/oca.2487

A Generic Flexible and Scalable Framework for Hierarchical Parallelization of Population-Based Metaheuristics
Khalloof, H.; Mohammad, M.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2020. Proceedings of the 12th International Conference on Management of Digital EcoSystems (MEDES’20), 2nd - 4th November 2020, Online. Ed.: Richard Chbeir, 124–131, Association for Computing Machinery (ACM). doi:10.1145/3415958.3433041

Polychaos.jl - A Julia package for polynomial chaos in systems and control
Mühlpfordt, T.; Zahn, F.; Hagenmeyer, V.; Faulwasser, T.
2020. 21th IFAC World Congress. Ed.: R. Findeisen, 7210–7216, Elsevier. doi:10.1016/j.ifacol.2020.12.552

Control and communication technologies for wireline borehole probes and inspection systems in hot geothermal environments
Dietze, S.
2020. Geothermal Resources Council Virtual Annual Meeting and Expo: Clean, Renewable and Always On, GRC 2020; Virtual, Online; ; 19 October 2020 through 23 October 2020, 38–45, Geothermal Resources Council (GRC)

Towards classification of technical sound events with deep learning models
Rieder, C.; Germann, M.; Scherer, K. P.
2020. WM in digitalen Arbeitswelten – Aktuelle Ansätze und Perspektiven, Proceedings 10. Konferenz Prof. WM, Potsdam 18.-20.03.2019. Hrsg.: P. Heisig, 188–193, Gesellschaft für Informatik (GI)

ED4GAP: Efficient Detection for GOOSE-Based Poisoning Attacks on IEC 61850 Substations
Bohara, A.; Ros-Giralt, J.; Elbez, G.; Valdes, A.; Nahrstedt, K.; Sanders, W. H.
2020. 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), 11-13 November 2020, online, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm47815.2020.9303015

Semi-Automatic Generation Of Tight Binary Masks And Non-Convex Isosurfaces For Quantitative Analysis Of 3d Biological Samples
Bhide, S.; Mikut, R.; Leptin, M.; Stegmaier, J.
2020. 2020 IEEE International Conference on Image Processing (ICIP), Abu Dhabi, United Arab Emirates, United Arab Emirates, 25-28 Oct. 2020, 2820–2824, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICIP40778.2020.9190951

Potential of Ensemble Copula Coupling for Wind Power Forecasting
Phipps, K.; Ludwig, N.; Hagenmeyer, V.; Mikut, R.
2020. Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020, 87–109, KIT Scientific Publishing

CAD2Real: Deep learning with domain randomization of CAD data for 3D pose estimation of electronic control unit housings
Bäuerle, S.; Barth, J.; Tavares, E. de M.; Steimer, A.; Mikut, R.
2020. Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020, 33–52, KIT Scientific Publishing

WaSam, a Modularly Designed Fluid Downhole Sampler for Deep Geothermal Applications
Berentelg, G.; Spatafora, L.; Hagenmeyer, V.
2020. Geothermal Resources Council Virtual Annual Meeting and Expo: Clean, Renewable and Always On, GRC 2020; Virtual, Online; ; 19 October 2020 through 23 October 2020, 535–541, Geothermal Resources Council (GRC)

Annotating Automotive Radar efficiently: Semantic Radar Labeling Framework (SeRaLF)
Isele, S. T.; Schilling, M. P.; Klein, F. E.; Zoellner, M. J.
2020. Conference on Neural Information Processing Systems, Sun Dec 6th through Sat the 12th

On Grid Partitioning in AC Optimal Power Flow
Murray, A.; Kyesswa, M.; Schmurr, P.; Cakmak, H.; Hagenmeyer, V.
2020. IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), 524–528, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe47291.2020.9248824

Siamese Networks for 1D Signal Identification
Schützke, J.; Benedix, A.; Mikut, R.; Reischl, M.
2020. Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020, 17–31, KIT Scientific Publishing

Transforming Lidar Point Cloud Characteristics Between Different Datasets Using Image-to-Image Translation
Berens, F.; Knapp, Y.; Reischl, M.; Elser, S. T.
2020. Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020, 73–86, KIT Scientific Publishing

Towards Smart Buildings: A Versatile Acquisition Setup for Indoor Climate Data
Sauer, D.; Jumar, R.; Lutz, R.; Schlachter, T.; Schmitt, C.; Hagenmeyer, V.
2020. 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), The Hague, Netherlands, Netherlands, 26-28 Oct. 2020, 1196–1200, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe47291.2020.9248925

Analyse des Flug- und Abbrandverhaltens von Ersatzbrennstoffen auf Basis eines Lichtfeldkamerasystems
Zhang, M.; Vogelbacher, M.; Aleksandrov, K.; Gehrmann, H.-J.; Matthes, J.
2020. Forum Bildverarbeitung 2020. Hrsg.: T. Längle, 105–117, KIT Scientific Publishing

Point and contextual anomaly detection in building load profiles of a university campus
Wang, L.; Turowski, M.; Zhang, M.; Riedel, T.; Beigl, M.; Mikut, R.; Hagenmeyer, V.
2020. 2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), 11–15, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe47291.2020.9248792

On Optimal Control of Flat Hybrid Automata
Zahn, F.; Kleinert, T.; Hagenmeyer, V.
2020. IFAC World Congress 2020, Germany, July 11 - 17, 2020. Ed.: R. Findeisen, 6800–6805, Elsevier. doi:10.1016/j.ifacol.2020.12.332

Predicting Quality of Automated Welding with Machine Learning and Semantics – A Bosch Case Study
Zhou, B.; Svetashova, Y.; Byeon, S.; Pychynski, T.; Mikut, R.; Kharlamov, E.
2020. CIKM ’20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. Ed.: M. d’Aquin, 2933–2940, Association for Computing Machinery (ACM). doi:10.1145/3340531.3412737

SemFE – Facilitating ML Pipeline Development with Semantics
Zhou, B.; Svetashova, Y.; Pychynski, T.; Baimuratov, I.; Soylu, A.; Kharlamov, E.
2020. CIKM ’20: Proceedings of the 29th ACM International Conference on Information & Knowledge Management. Ed.: M. d’Aquin, 3489–3492, Association for Computing Machinery (ACM). doi:10.1145/3340531.3417436

Convergence of Mixed-Integer ALADIN
Murray, A.; Hagenmeyer, V.
2020. 4th International Conference on Algorithms, Computing and Systems, Berlin, 18.-20. September 2020, Association for Computing Machinery (ACM)

A New Distributed Optimization Algorithm for MINLPs with Affinely Coupled Decision Variables
Murray, A.; Hagenmeyer, V.
2020. 4th International Conference on Algorithms, Computing and Systems, Berlin, 18.-20. September 2020, Association for Computing Machinery (ACM)

Towards automatic embryo staging in 3d+t microscopy images using convolutional neural networks and pointnets
Traub, M.; Stegmaier, J.
2020. Simulation and Synthesis in Medical Imaging: 5th International Workshop, SASHIMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Ed.: N. Burgos, 153–163, Springer. doi:10.1007/978-3-030-59520-3_16

Dynamic Modeling of Wind and Solar Power Generation with Grid Support for Large-Scale Integration in Power Systems
Kyesswa, M.; Cakmak, H.; Kühnapfel, U.; Hagenmeyer, V.
2020. IEEE PES Innovative Smart Grid Technologies (ISGT-Europe ), 569–573, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Europe47291.2020.9248883

Modelling Curtailment in Germany: How spatial resolution impacts line congestion
Frysztacki, M.; Brown, T.
2020. 17th International Conference on the European Energy Market (EEM), Stockholm, S, September 16-18, 2020, Article no: 1241, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM49802.2020.9221886

Sensitivity of input data in building heating energy demand simulation
Geiger, A.; Nichersu, A.; Hagenmeyer, V.
2020. BauSIM 2020, 23. - 25. September 2020, Graz

Automatisierte Generierung eines 3D-Baumkatasters am Beispiel des KIT Campus Nord
Hurst, J.; Geiger, A.
2020. REAL CORP 2020: Shaping urban change - livable city regions for the 21st century : proceedings of the 25th International Conference on Urban Planning, Regional Development and Information Society : 15-18 September 2020, virtual conference. Ed.: Manfred Schrenk, Competence Center of Urban and Regional Planning (CORP)

A New Julia-Based Parallel Time-Domain Simulation Algorithm for Analysis of Power System Dynamics
Kyesswa, M.; Schmurr, P.; Cakmak, H. K.; Kühnapfel, U.; Hagenmeyer, V.
2020. 2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), Prag, CZ, September 14-16, 2020. Vol. 1, 9 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DS-RT50469.2020.9213602

On Verification of Designed Energy Systems Using Distributed Co-Simulations
Erdmann, A.; Marcellan, A.; Hering, D.; Suriyah, M.; Ulbrich, C.; Henke, M.; Xhonneux, A.; Müller, D.; Schlatmann, R.; Hagenmeyer, V.
2020. 2020 IEEE/ACM 24th International Symposium on Distributed Simulation and Real Time Applications (DS-RT), 25–32, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DS-RT50469.2020.9213689

3Dprinted highly compact varifocal optics
Sieber, I.; Thelen, R.; Gengenbach, U.
2020. 3D Image Acquisition and Display: Technology, Perception and Applications : part of Imaging and Applied Optics Congress : 22-26 June 2020, Washington, DC, Article no: ITh4E.5, Optica Publishing Group (OSA). doi:10.1364/ISA.2020.ITh4E.5

Principle Structure and Architecture of a Code Generator
Schmidt, A.
2020. The Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications

In-Process Digital Monitoring of Additive Manufacturing: Proposed Machine Learning Approach and Potential Implications on Sustainability
Charles, A. P.; Salem, M.; Moshiri, M.; Elkaseer, A.; Scholz, S. G.
2020. Sustainable Design and Manufacturing 2020 – Proceedings of the 7th International Conference on Sustainable Design and Manufacturing (KES-SDM 2020), 9-11 September 2020. Ed.: S. Scholz, 297–306, Springer. doi:10.1007/978-981-15-8131-1_27

Impact of Nonplanar 3D Printing on Surface Roughness and Build Time in Fused Filament Fabrication
Elkaseer, A.; Müller, T.; Rabsch, D.; Scholz, S. G.
2020. Sustainable Design and Manufacturing 2020 – Proceedings of the 7th International Conference on Sustainable Design and Manufacturing (KES-SDM 2020), 9-11 September 2020. Ed.: S. Scholz, 285–295, Springer. doi:10.1007/978-981-15-8131-1_26

Transmission Expansion Planning Using Cycle Flows
Neumann, F.; Brown, T.
2020. Proceedings of the Eleventh ACM International Conference on Future Energy Systems, Melbourne, Australia from 22nd to 26th of June 2020, 253–263, Association for Computing Machinery (ACM). doi:10.1145/3396851.3397688

Identification and Localization of Cyber-Attacks in Industrial Facilities
Reibelt, K.; Matthes, J.; Keller, H. B.; Hagenmeyer, V.
2020. ESCAPE 30, 30th European Symposium on Computer Aided Process Engineering, Milan, Italy, 30 August 2020 – 2 September 2020. Ed.: S. Pierucci, 1747–1752, Elsevier

Reproducibility of two calibration procedures for phase-measuring deflectometry
Allgeier, S.; Gengenbach, U.; Köhler, B.; Reichert, K.-M.; Hagenmeyer, V.
2020. Interferometry XX : 24 August - 4 September 2020, online only, United States. Ed.: M.B. North Morris, 14, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2567092

DBMS Fitting: Why should we learn what we already know
Hilprecht, B.; Bang, T.; Binnig, C.; El-Hindi, M.; Hättasch, B.; Khanna, A.; Rehrmann, R.; Röhm, U.; Schmidt, A.; Thostrup, L.; Ziegler, T.
2020. CIDR 2020, January 12-15, 2020 Amsterdam, Netherlands

Characteristics-based Simulink Implementation of First-order Quasilinear Partial Differential Equations
Ponomarev, A.; Hofmann, J.; Gröll, L.
2020. Proceedings of the 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications. Ed.: F. De Rango, 139–146, SciTePress. doi:10.5220/0009569001390146

Forecasting energy time series with profile neural networks
Heidrich, B.; Turowski, M.; Ludwig, N.; Mikut, R.; Hagenmeyer, V.
2020. e-Energy ’20: The Eleventh ACM International Conference on Future Energy Systems, Virtual Event, Australia, June, 2020, 220–230, Association for Computing Machinery (ACM). doi:10.1145/3396851.3397683

Mathematical Measures for calibration and evaluation of gas sensor data
Seifert, R.; Keller, H., B.
2020. SMSI 2020 Conference – Sensor and Measurement Science International. doi:10.5162/SMSI2020/P4.6

A distributed modular scalable and generic framework for parallelizing population-based metaheuristics
Khalloof, H.; Ostheimer, P.; Jakob, W.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2020. Parallel Processing and Applied Mathematics : 13th International Conference, PPAM 2019, Bialystok, Poland, September 8–11, 2019, Revised Selected Papers, Part I. Ed: R. Wyrzykowski, 432–444, Springer. doi:10.1007/978-3-030-43229-4_37

Ontology based information management for industrial applications
Germann, M.; Rieder, C.; Scherer, K. P.
2020. ICAART 2020 - Proceedings of the 12th International Conference on Agents and Artificial Intelligence. Vol. 2. Ed.: A. Rocha, 773–779, SciTePress

A Parallel Decomposition Scheme for Solving Long-Horizon Optimal Control Problems
Shin, S.; Faulwasser, T.; Zanon, M.; Zavala, V. M.
2020. 58th IEEE Conference on Decision and Control (CDC), Nice, F, December 11-13, 2019, 5264–5271, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC40024.2019.9030139

Distributed State Estimation for AC Power Systems using Gauss-Newton ALADIN
Du, X.; Engelmann, A.; Jiang, Y.; Faulwasser, T.; Houska, B.
2020. 2019 IEEE 58th Conference on Decision and Control (CDC), 1919–1924, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CDC40024.2019.9028966

Descriptive Statistics Time-based Meta Features (DSTMF): Constructing a better Set of Meta Features for Model Selection in Energy Time Series Forecasting
Shahoud, S.; Khalloof, H.; Duepmeier, C.; Hagenmeyer, V.
2020. APPIS 2020: Proceedings of the 3rd International Conference on Applications of Intelligent Systems. Ed.: N. Petkov, 3378221, Association for Computing Machinery (ACM). doi:10.1145/3378184.3378221

Design of a Web-Service for Formal Descriptions of Domain-Specific Data
Sidler, J.; Braun, E.; Schlachter, T.; Düpmeier, C.; Hagenmeyer, V.
2020. Environmental Software Systems. Data Science in Action – 13th IFIP WG 5.11 International Symposium, ISESS 2020, Wageningen, The Netherlands, February 5–7, 2020, Proceedings. Ed.: I. Athanasiadis, 201–215, Springer International Publishing. doi:10.1007/978-3-030-39815-6_20

The Near-Optimal Feasible Space of a Renewable Power System Model
Neumann, F.; Brown, T.
2020. 21st Power Systems Computation Conference, Porto, P, June 29 - July 03, 2020 (PSCC 2020)

DBKDA 2020: Proceedings of the Twelfth International Conference on Advances in Databases, Knowledge, and Data Applications
Crowe, M.; Ehrlinger, L.; Laux, F.; Schmidt, A.
2020

Proceedings - 30. Workshop Computational Intelligence : Berlin, 26. - 27. November 2020
Schulte, H.; Hoffmann, F.; Mikut, R. (Eds.)
2020. KIT Scientific Publishing. doi:10.5445/KSP/1000124139

Python for Power System Analysis (PyPSA) Version 0.16.0
Brown, T.; Hörsch, J.; Schlachtberger, D.
2020, January 10. doi:10.5281/zenodo.3604277

AI Word of the Week
Heidrich, B.
2020, July 12

Energy planning using 3D spatial models
Nichersu, A.
2020. doi:10.5445/IR/1000124784

„Mit künstlicher Intelligenz gegen betrügerische Online-Angebote“ - Das INSPECTION-Projekt am Karlsruher Institut für Technologie bekämpft Fakeshops - Campus-Report am 08.09.2020
Fuchs, S.; Mayer, P.; Volkamer, M.
2020. doi:10.5445/IR/1000123419

Einsatz von VR-Technologien in BIM/GIS
Schürstedt, S.; Geiger, A.
2019. 31. Forum Bauinformatik : 11.–13. September 2019 in Berlin. Proceedings. Hrsg.: M. Sternal, 283–290, Universitätsverlag der TU Berlin

Advances in near net shape polymer manufacturing through microcellular injection moulding
Llewelyn, G.; Rees, A.; Griffiths, C. A.; Scholz, S. G.
2019. Near net shape manufacturing processes. Ed.: K. Gupta, 177–189, Springer International Publishing. doi:10.1007/978-3-030-10579-2_8

Nonlinear Predictive Control for Trajectory Tracking and Path Following: An Introduction and Perspective
Matschek, J.; Bäthge, T.; Faulwasser, T.; Findeisen, R.
2019. Handbook of Model Predictive Control. Ed.: S. Raković, 169–198, Springer International Publishing. doi:10.1007/978-3-319-77489-3_8

Laser Ablation of Cobalt-Bound Tungsten Carbide and Aluminium Oxide Ceramic: Experimental Investigation with ANN Modelling and GA Optimisation
Elkaseer, A.; Lambarri, J.; Quintana, I.; Scholz, S.
2019. Sustainable Design and Manufacturing 2018 – Proceedings of the 5th International Conference on Sustainable Design and Manufacturing (KES-SDM-18). Ed.: D. Dao, 21–30, Springer International Publishing. doi:10.1007/978-3-030-04290-5_3

Entwicklung von Echtzeitsystemen – Einführung in die Entwicklung zuverlässiger softwarebasierter Funktionen unter Echtzeitbedingungen
Keller, H. B.
2019. Springer Fachmedien Wiesbaden. doi:10.1007/978-3-658-26641-7

Scheduling of energy storage using probabilistic forecasts and energy-based aggregated models. PhD dissertation
Appino, R. R.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000100684

Neues Konzept zur skalierbaren, explorativen Analyse großer Zeitreihendaten mit Anwendung auf umfangreiche Stromnetz-Messdaten. PhD dissertation
Bach, F.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000097843

Theoretische und Experimentelle Kältemittel- und Dichtungsauswahl und Komponentenentwicklung zur Langzeitkühlung von Elektronik in Untertagewerkzeugen. PhD dissertation
Holbein, B.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000094597

New Data-Driven Probabilistic Forecasting Methods with Applications in Energy Systems. PhD dissertation
González Ordiano, J. Á.
2019. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000092701

Ein neues Konzept für die geberlose Regelung von Permanentmagnet-Synchronmaschinen für Hybrid- und Elektrofahrzeuge. PhD dissertation
Paulus, S.
2019. KIT Scientific Publishing. doi:10.5445/KSP/1000087356

Cryptanalysis of an Identity-Based Encryption Scheme With Equality Test and Improvement
Liao, Y.; Fan, Y.; Liang, Y.; Liu, Y.; Ramadan, M.
2019. IEEE Access, 7, 75067–75072. doi:10.1109/ACCESS.2019.2920897

Insecurity of an IBEET Scheme and an ABEET Scheme
Liao, Y.; Chen, H.; Huang, W.; Ramadan, M.; Pan, H.; Zhou, S.
2019. IEEE Access, 7, 25087–25094. doi:10.1109/ACCESS.2019.2900752

Vision system-based inspection and alignment of laminated polymer films for 3D-Integration of microsystems
Elkaseer, A.; Salem, M.; Hagenmeyer, V.; Scholz, S.
2019. IFAC-PapersOnLine, 52 (15), 13–18. doi:10.1016/j.ifacol.2019.11.642

Modeling and control of multimodal and hybrid energy systems (Editorial)
Wolter, M.; Hagenmeyer, V.
2019. Automatisierungstechnik, 67 (11), 891–892. doi:10.1515/auto-2019-0112

Motion prediction enables simulated MR-imaging of freely moving model organisms
Reischl, M.; Jouda, M.; MacKinnon, N.; Fuhrer, E.; Bakhtina, N.; Bartschat, A.; Mikut, R.; Korvink, J. G.
2019. PLoS Computational Biology, 15 (12), e1006997. doi:10.1371/journal.pcbi.1006997

Errata for “Comments on Truncation Errors for Polynomial Chaos Expansions”
Mühlpfordt, T.; Findeisen, R.; Hagenmeyer, V.; Faulwasser, T.
2019. IEEE Control Systems Letters, 1. doi:10.1109/LCSYS.2019.2960612

Time delay in the swing equation: A variety of bifurcations
Scholl, T. H.; Gröll, L.; Hagenmeyer, V.
2019. Chaos, 29 (12), Article: 123118. doi:10.1063/1.5122784

Synergy Pattern of Short Cationic Antimicrobial Peptides Against Multidrug-Resistant Pseudomonas aeruginosa
Ruden, S.; Rieder, A.; Chis Ster, I.; Schwartz, T.; Mikut, R.; Hilpert, K.
2019. Frontiers in microbiology, 10, Art. Nr.: 2740. doi:10.3389/fmicb.2019.02740

Digitale Bildverarbeitung und Tiefe Neuronale Netze in der Augenheilkunde – aktuelle Trends - Digital Image Processing and Deep Neural Networks in Ophthalmology – Current Trends
Bartschat, A.; Allgeier, S.; Bohn, S.; Scherr, T.; Blessing, D.; Reichert, K.-M.; Reischl, M.; Stachs, O.; Koehler, B.; Mikut, R.
2019. Klinische Monatsblätter für Augenheilkunde, 236 (12), 1399–1406. doi:10.1055/a-1008-9400

Uncertainty Quantification for Optimal Power Flow Problems
Mühlpfordt, T.; Hagenmeyer, V.; Faulwasser, T.
2019. Proceedings in applied mathematics and mechanics, 19 (1), Art.Nr. e201900087. doi:10.1002/Pamm.201900087

Siloxane-functionalised surface patterns as templates for the ordered deposition of thin lamellar objects
Hoffmann, J.; Gamboa, S. M.; Hofmann, A.; Gliemann, H.; Welle, A.; Wacker, I.; Schröder, R. R.; Ness, L.; Hagenmeyer, V.; Gengenbach, U.
2019. Scientific reports, 9 (1), Article no: 17952. doi:10.1038/s41598-019-54507-1

Applanation force monitoring during in vivo corneal confocal laser scanning microscopy
Bohn, S.; Sperlich, K.; Bartschat, A.; Stolu, H.; Guthoff, R. R.; Mikut, R.; Köhler, B.; Stacks, O.
2019. Der Ophthalmologe, 116 (Suppl.2), S139

A new distributed co-simulation architecture for multi-physics based energy systems integration
Çakmak, H.; Erdmann, A.; Kyesswa, M.; Kühnapfel, U.; Hagenmeyer, V.
2019. Automatisierungstechnik, 67 (11), 972–983. doi:10.1515/auto-2019-0081

The role of storage technologies throughout the decarbonisation of the sector-coupled European energy system
Victoria, M.; Zhu, K.; Brown, T.; Andresen, G. B.; Greiner, M.
2019. Energy conversion and management, 201, Article no: 111977. doi:10.1016/j.enconman.2019.111977

Flexibility From Energy Systems Integration: Supporting Synergies Among Sectors
Orths, A.; Anderson, C. L.; Brown, T.; Mulhern, J.; Pudjianto, D.; Ernst, B.; OMalley, M.; McCalley, J.; Strbac, G.
2019. IEEE power & energy magazine, 17 (6), 67–78. doi:10.1109/MPE.2019.2931054

Tailored Chip Breaker Development for Polycrystalline Diamond Inserts: FEM-based Design and Validation
Cascón, I.; Sarasua, J. A.; Elkaseer, A.
2019. Applied Sciences, 9 (19), 4117. doi:10.3390/app9194117

Image based analysis of multi-fuel burners in industrial combustion processes
Vogelbacher, M.; Waibel, P.; Matthes, J.; Hyer, M.; Keller, H. B.
2019. Cement, lime, gypsum, 72 (7-8), 56–61

Bildbasierte Analyse von Mehrstoffbrennern bei industriellen Verbrennungsprozessen
Vogelbacher, M.; Waibel, P.; Matthes, J.; Hoyer, M.; Keller, H. B.
2019. Prozesswärme

Ausgewählte Beiträge aus dem GMA-Fachausschuss 5.14 „Computational Intelligence
Mikut, R.; Kroll, A.; Hoffmann, F.
2019. Automatisierungstechnik, 67 (10), 817–819. doi:10.1515/auto-2019-0101

Fuzzy tissue detection for real-time focal control in corneal confocal microscopy = Fuzzy-Gewebeerkennung für Echtzeit-Fokusregelung in der Kornea-Konfokalmikroskopie
Bartschat, A.; Allgeier, S.; Scherr, T.; Stegmaier, J.; Bohn, S.; Reichert, K.-M.; Kuijper, A.; Reischl, M.; Stachs, O.; Köhler, B.; Mikut, R.
2019. Automatisierungstechnik, 67 (10), 879–888. doi:10.1515/auto-2019-0034

Automated design process for hybrid regression modeling with a one-class SVM = Ein automatisiertes Entwurfsverfahren für hybride Regressionsmodelle mit einer Ein-Klassen-Support-Vektor-Maschine
Böhland, M.; Doneit, W.; Gröll, L.; Mikut, R.; Reischl, M.
2019. Automatisierungstechnik, 67 (10), 843–852. doi:10.1515/auto-2019-0013

Avoiding Thermal-Stress-Induced Failures by Design Optimization when Brazing Perlucor® to Inconel® 718 Components
Spatafora, L.; Isele, J.; Ritzhaupt-Kleissl, H.-J.; Hagenmeyer, V.; Aktaa, J.
2019. Journal of ceramic science and technology, 10 (2), 1–10. doi:10.4416/JCST2019-00011

BioSAXS Measurements Reveal That Two Antimicrobial Peptides Induce Similar Molecular Changes in Gram-Negative and Gram-Positive Bacteria
Gundlach, A. von; Ashby, M. P.; Gani, J.; Lopez-Perez, P. M.; Cookson, A. R.; Ann Huws, S.; Rumancev, C.; Garamus, V. M.; Mikut, R.; Rosenhahn, A.; Hilpert, K.
2019. Frontiers in pharmacology, 10, Art. Nr.: 1127. doi:10.3389/fphar.2019.01127

Volume reconstruction of the human cornea with oscillating focus scans
Kornelius, L.; Allgeier, S.; Bohn, S.; Reichert, K.-M.; Sperlich, K.; Stachs, O.; Köhler, B.
2019. Biomedical engineering, 64 (s2), S193. doi:10.1515/bmt-2019-6023

Machine Learning Methods for Automated Quantification of Ventricular Dimensions
Schutera, M.; Just, S.; Gierten, J.; Mikut, R.; Reischl, M.; Pylatiuk, C.
2019. Zebrafish, 16 (6), 542–545. doi:10.1089/zeb.2019.1754

FEM-based study of precision hard turning of stainless steel 316L
Elkaseer, A.; Abdelaziz, A.; Saber, M.; Nassef, A.
2019. Materials, 12 (16), Art.-Nr.: 2522. doi:10.3390/ma12162522

mTORC1 and PKB/Akt control the muscle response to denervation by regulating autophagy and HDAC4
Castets, P.; Rion, N.; Théodore, M.; Falcetta, D.; Lin, S.; Reischl, M.; Wild, F.; Guérard, L.; Eickhorst, C.; Brockhoff, M.; Guridi, M.; Ibebunjo, C.; Cruz, J.; Sinnreich, M.; Rudolf, R.; Glass, D. J.; Rüegg, M. A.
2019. Nature Communications, 10 (1), 3187. doi:10.1038/s41467-019-11227-4

Microfluidic Chips for Life Sciences - A Comparison of Low Entry Manufacturing Technologies
Grösche, M.; Zoheir, A. E.; Stegmaier, J.; Mikut, R.; Mager, D.; Korvink, J. G.; Rabe, K. S.; Niemeyer, C. M.
2019. Small, 15 (35), 1901956. doi:10.1002/smll.201901956

Augmented reality-assisted ventricular puncture with marker-based scene registration
Kunz, C.; Schneider, M.; Hlavac, M.; Zenth, D.; Pylatiuk, C.; Hein, B.
2019. International journal of computer assisted radiology and surgery, 14 (Suppl. 1), S151-S152

Strategies for supplementing recurrent neural network training for spatio-temporal prediction = Strategien zur Unterstützung des Trainings von Rekurrenten Neuronalen Netzen zur räumlich-zeitlichen Vorhersage
Schutera, M.; Elser, S.; Abhau, J.; Mikut, R.; Reischl, M.
2019. Automatisierungstechnik, 67 (7), 545–556. doi:10.1515/auto-2018-0124

buildingSMART Software Zertifizierung
Geiger, A.; Haefele, K.-H.
2019. Ernst & Sohn Special - Bauprodukte digital, April 2019 (April), 21–25

Toward a Unifying Framework Blending Real-Time Optimization and Economic Model Predictive Control
Faulwasser, T.; Pannocchia, G.
2019. Industrial & engineering chemistry research, 58 (30), 13583–13598. doi:10.1021/acs.iecr.9b00782

Benchmarking in classification and regression
Hoffmann, F.; Bertram, T.; Mikut, R.; Reischl, M.; Nelles, O.
2019. Wiley interdisciplinary reviews / Data mining and knowledge discovery, 9 (5), e1318. doi:10.1002/widm.1318

A high-resolution hydro power time-series model for energy systems analysis: Validated with Chinese hydro reservoirs
Liu, H.; Andresen, G. B.; Brown, T.; Greiner, M.
2019. MethodsX, 6, 1370–1378. doi:10.1016/j.mex.2019.05.024

Improving Root Cause Analysis by Detecting and Removing Transient Changes in Oscillatory Time Series with Application to a 1,3-Butadiene Process
Zhou, B.; Chioua, M.; Bauer, M.; Schlake, J. C.; Thornhill, N. F.
2019. Industrial & engineering chemistry research, 58 (26), 11234–11250. doi:10.1021/acs.iecr.8b06138

Photonic-integrated circuits with non-planar topologies realized by 3D-printed waveguide overpasses
Nesic, A.; Blaicher, M.; Hoose, T.; Hofmann, A.; Lauermann, M.; Kutuvantavida, Y.; Nöllenburg, M.; Randel, S.; Freude, W.; Koos, C.
2019. Optics express, 27 (12), 17402. doi:10.1364/OE.27.017402

Chance-constrained AC optimal power flow - A polynomial chaos approach
Mühlpfordt, T.; Roald, L.; Hagenmeyer, V.; Faulwasser, T.; Misra, S.
2019. IEEE transactions on power systems, 34 (6), 4806–4816. doi:10.1109/TPWRS.2019.2918363

Enforcing optimal operation in solid-oxide fuel-cell systems
Avila Ferreira, T. de; Wuillemin, Z.; Faulwasser, T.; Salzmann, C.; Van herle, J.; Bonvin, D.
2019. Energy, 181, 281–293. doi:10.1016/j.energy.2019.04.188

Feedback, dynamics, and optimal control in climate economics
Kellett, C. M.; Weller, S. R.; Faulwasser, T.; Grüne, L.; Semmler, W.
2019. Annual reviews in control, 47, 7–20. doi:10.1016/j.arcontrol.2019.04.003

High accuracy beam splitting using spatial light modulator combined with machine learning algorithms
Mikhaylov, D.; Zhou, B.; Kiedrowski, T.; Mikut, R.; Lasagni, A.-F.
2019. Optics and lasers in engineering, 121, 227–235. doi:10.1016/j.optlaseng.2019.04.010

The need for a statutory base to establish modern safety directives
Pilz, W.-D.; Schulz-Forberg, B.; Keller, H.; Langenbach, C.
2019. Technische Sicherheit, (3), 21–28

A new camera-based method for measuring the flame stability of non-oscillating and oscillating combustions
Matthes, J.; Waibel, P.; Vogelbacher, M.; Gehrmann, H.-J.; Keller, H. B.
2019. Experimental thermal and fluid science, 105, 27–34. doi:10.1016/j.expthermflusci.2019.03.008

DIY Automated Feeding and Motion Recording System for the Analysis of Fish behaviour
Pylatiuk, C.; Zhao, H.; Gursky, E.; Reischl, M.; Peravali, R.; Foulkes, N.; Loosli, F.
2019. SLAS technology, 24 (4), 394–398. doi:10.1177/2472630319841412

Progression and Evaluation of a Camera-Based Measurement System for Multifuel Burners under Industrial Process Conditions
Vogelbacher, M.; Matthes, J.; Keller, H.; Waibel, P.
2019. IEEE transactions on industrial informatics, 15 (10), 5466–5474. doi:10.1109/TII.2019.2899946

Quanfima: An open source Python package for automated fiber analysis of biomaterials
Shkarin, R.; Shkarin, A.; Shkarina, S.; Cecilia, A.; Surmenev, R. A.; Surmeneva, M. A.; Weinhardt, V.; Baumbach, T.; Mikut, R.
2019. PLOS ONE, 14 (4), e0215137. doi:10.1371/journal.pone.0215137

Automated Classification of Fertilized Zebrafish Embryos
Neukum, A.; Bartschat, A.; Breitwieser, H.; Strähle, U.; Dickmeis, T.; Pylatiuk, C.
2019. Zebrafish, 16 (3), 326–328. doi:10.1089/zeb.2019.1728

In silico identification of novel peptides with antibacterial activity against multidrug resistant Staphylococcus aureus
Oyama, L. B.; Olleik, H.; Nery Teixeira, A. C.; Guidini, M. M.; Pickup, J. A.; Cookson, A. R.; Vallin, H.; Wilkinson, T.; Bazzolli, D.; Richards, J.; Wootton, M.; Mikut, R.; Hilpert, K.; Maresca, M.; Perrier, J.; Hess, M.; Mantovani, H. C.; Fernandez-Fuentes, N.; Creevey, C. J.; Huws, S. A.
2019. bioRxiv beta, 42 S. doi:10.1101/577221

Digital technologies in airport ground operations
Kovynyov, I.; Mikut, R.
2019. Netnomics, 20 (1), 1–30. doi:10.1007/s11066-019-09132-5

Data mining tools
Bartschat, A.; Reischl, M.; Mikut, R.
2019. Wiley interdisciplinary reviews / Data mining and knowledge discovery, 9 (4), Article: e1309. doi:10.1002/widm.1309

The HMG box transcription factors Sox1a and Sox1b specify a new class of glycinergic interneuron in the spinal cord of zebrafish embryos
Gerber, V.; Yang, L.; Takamiya, M.; Ribes, V.; Gourain, V.; Peravali, R.; Stegmaier, J.; Mikut, R.; Reischl, M.; Ferg, M.; Rastegar, S.; Strähle, U.
2019. Development <Cambridge>, 146 (4), dev172510. doi:10.1242/dev.172510

Self-Flushing in EDM Drilling of Ti6Al4V Using Rotating Shaped Electrodes
Goiogana, M.; Elkaseer, A.
2019. Materials, 12 (6), Article: 989. doi:10.3390/ma12060989

Effect of Process Parameters on the Generated Surface Roughness of Down-Facing Surfaces in Selective Laser Melting
Charles, A. P.; Elkaseer, A.; Thijs, L.; Hagenmeyer, V.; Scholz, S.
2019. Applied Sciences, 9 (6), Article: 1256. doi:10.3390/app9061256

Advanced Electric Discharge Machining of Stainless Steels: Assessment of the State of the Art, Gaps and Future Prospect
Abu Qudeiri, J.; Saleh, A.; Ziout, A.; Mourad, A.-H.; Abidi, M.; Elkaseer, A.
2019. Materials, 12 (6), 907. doi:10.3390/ma12060907

Sectoral Interactions as Carbon Dioxide Emissions Approach Zero in a Highly-Renewable European Energy System
Brown, T.; Schäfer, M.; Greiner, M.
2019. Energies, 12 (6), 1032/1–16. doi:10.3390/en12061032

A Novel Optical Tissue Clearing Protocol for Mouse Skeletal Muscle to Visualize Endplates in Their Tissue Context
Williams, M. P. I.; Rigon, M.; Straka, T.; Hörner, S. J.; Thiel, M.; Gretz, N.; Hafner, M.; Reischl, M.; Rudolf, R.
2019. Frontiers in cellular neuroscience, 13, Article No.49. doi:10.3389/fncel.2019.00049

The role of hydro power, storage and transmission in the decarbonization of the Chinese power system
Liu, H.; Brown, T.; Andresen, G. B.; Schlachtberger, D. P.; Greiner, M.
2019. Applied energy, 239, 1308–1321. doi:10.1016/j.apenergy.2019.02.009

Architectural Concept and Evaluation of a Framework for the Efficient Automation of Computational Scientific Workflows: An Energy Systems Analysis Example
Liu, J.; Braun, E.; Düpmeier, C.; Kuckertz, P.; Ryberg, D.; Robinius, M.; Stolten, D.; Hagenmeyer, V.
2019. Applied Sciences, 9 (4), Article no: 728. doi:10.3390/app9040728

Comprehensive characterization and material modeling for ceramic injection molding simulation performance validations
Tosello, G.; Marhöfer, D. M.; Islam, A.; Müller, T.; Plewa, K.; Piotter, V.
2019. The international journal of advanced manufacturing technology, 102 (1-4), 225–240. doi:10.1007/s00170-018-03251-3

Chancen der Digitalisierung für die Energiewende
Waczowicz, S.; Müller-Langer, F.; Kröner, M.; Steubing, M.; Fischedick, M.; Weigel, P.; Hagenmeyer, V.
2019. GWF / Gas+Energie, (1), 60–64

Counter-intuitive behaviour of energy system models under CO₂ caps and prices
Weber, J.; Heinrichs, H. U.; Gillessen, B.; Schumann, D.; Hörsch, J.; Brown, T.; Witthaut, D.
2019. Energy, 170, 22–30. doi:10.1016/j.energy.2018.12.052

Impact of CO2 prices on the design of a highly decarbonised coupled electricity and heating system in Europe
Zhu, K.; Victoria, M.; Brown, T.; Andresen, G. B.; Greiner, M.
2019. Applied energy, 236, 622–634. doi:10.1016/j.apenergy.2018.12.016

Dual-Objective NMPC: Considering Economic Costs near Manifolds
Van Duijkeren, N.; Faulwasser, T.; Pipeleers, G.
2019. IEEE transactions on automatic control, 64 (9), 3788–3795. doi:10.1109/TAC.2018.2886177

Large-scale grid integration of residential thermal energy storages as demand-side flexibility resource: A review of international field studies
Kohlhepp, P.; Harb, H.; Wolisz, H.; Waczowicz, S.; Müller, D.; Hagenmeyer, V.
2019. Renewable & sustainable energy reviews, 101, 527–547. doi:10.1016/j.rser.2018.09.045

Performing energy modelling exercises in a transparent way - The issue of data quality in power plant databases
Gotzens, F.; Heinrichs, H.; Hörsch, J.; Hofmann, F.
2019. Energy strategy reviews, 23, 1–12. doi:10.1016/j.esr.2018.11.004

Towards Distributed OPF using ALADIN
Engelmann, A.; Jiang, Y.; Muhlpfordt, T.; Houska, B.; Faulwasser, T.
2019. IEEE transactions on power systems, 34 (1), 584–594. doi:10.1109/TPWRS.2018.2867682

Modelling and experimental validation of surface roughness in precision turning of dual-phase materials considering process uncertainties
Elsanabary, S.; Elkaseer, A.; Abd-Rabbo, S.; AbdElsalam, M.; Abdou, S.
2019. International journal on interactive design and manufacturing, 13 (1), 59–74. doi:10.1007/s12008-018-0490-8

Industrial internet of things solution for real-time monitoring of the additive manufacturing process
Salama, M.; Elkaseer, A.; Saied, M.; Ali, H.; Scholz, S.
2019. Advances in Intelligent Systems and Computing, 852, 355–365. doi:10.1007/978-3-319-99981-4_33

Celitement quality parameter determination by online NIR-spectroscopy
Lutz, C.; Matthes, J.; Waibel, P.; Precht, U.; Beuchle, G.; Garbev, K.; Schweike, U.; Stemmermann, P.; Keller, H. B.
2019. Advances in cement research, 31 (2), 80–91. doi:10.1680/jadcr.17.00016

ANN-based modelling of dimensional accuracy in L-PBF
Charles, A. P.; Elkaseer, A.; Salem, M.; Thijs, L.; Scholz, S. G.
2019. Proceedings of the Joint Special Interest Group meeting between euspen and ASPE Advancing Precision in Additive Manufacturing (2019). Ed.: A. Bernard, Ecole Centrale de Nantes

Authentication of GOOSE Messages under Timing Constraints in IEC 61850 Substations
Elbez, G.; Keller, H. B.; Hagenmeyer, V.
2019. 6th International Symposium for ICS & SCADA Cyber Security Research 2019 (ICS-CSR), BCS Learning & Development. doi:10.14236/ewic/icscsr19.17

Feature Space Exploration for Motion Classification Based on Multi-Modal Sensor Data for Lower Limb Exoskeletons
Daab, T.; Patzer, I.; Mikut, R.; Asfour, T.
2019. 2019 IEEE-RAS 19th International Conference on Humanoid Robots (Humanoids), 636–643, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/Humanoids43949.2019.9035014

A New Communication Concept for Efficient Configuration of Energy Systems Integration Co-Simulation
Erdmann, A.; Çakmak, H. K.; Kuhnapfel, U.; Hagenmeyer, V.
2019. 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT), 8 Seiten, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/DS-RT47707.2019.8958665

Feasibility vs. Optimality in Distributed AC OPF: A Case Study Considering ADMM and ALADIN
Engelmann, A.; Faulwasser, T.
2019. Advances in Energy System Optimization – Proceedings of the 2nd International Symposium on Energy System Optimization. Ed.: V. Bertsch, 3–12, Springer International Publishing. doi:10.1007/978-3-030-32157-4_1

A parallel decomposition cheme for solving long-horizon optimal control problems [in press]
Shin, S.; Faulwasser, T.; Zanon, M.; Zavala; V.M.
2019. 58th Conference on Decision and Control (CDC 2019), Nice, France, December 11th-13th 2019, Institute of Electrical and Electronics Engineers (IEEE)

Modeling and Force Control of a Terramechanical Wheel-Soil Contact for a Robotic Manipulator used in the Planetary Rover Design Process
Wachter, J.; Mikut, R.; Buse, F.
2019. 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 560–565, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/IROS40897.2019.8967900

On Calendar-Based Scheduling for User-Friendly Charging of Plug-In Electric Vehicles
Schwenk, K.; Faix, M.; Mikut, R.; Hagenmeyer, V.; Appino, R. R.
2019. 2nd IEEE Connected and Automated Vehicles Symposium, CAVS 2019, Honolulu, United States, 22nd - 23rd September 2019, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/CAVS.2019.8887782

Facilitating and Managing Machine Learning and Data Analysis Tasks in Big Data Environments using Web and Microservice Technologies
Shahoud, S.; Gunnarsdottir, S.; Khalloof, H.; Düpmeier, C.; Hagenmeyer, V.
2019. 11th International Conference on Management of Digital EcoSystems, MEDES. doi:10.1145/3297662.3365807

Superlinear Speedup of Parallel Population-Based Metaheuristics: A Microservices and Container Virtualization Approach
Khalloof, H.; Ostheimer, P.; Jakob, W.; Shahoud, S.; Düpmeier, C.; Hagenmeyer, V.
2019. Intelligent Data Engineering and Automated Learning. Ed.: Hujun Yin, 386–393, Springer. doi:10.1007/978-3-030-33607-3_42

A distributed Modular Scalable and Generic Framework for Parallelizing Population Based Metaheuristics
Khalloof, H.; Ostheimer, P.; Jakob, W.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2019. 13th International Conference on Parallel Processing and Applied Mathematics (PPAM 2019), Bialystok, PL, September 8-11, 2019, Springer

Advanced Ceramic Breeder Pebble Production: Controlling the Pebble Size Distribution
Leys, O.; Waibel, P.; Matthes, J.; Knitter, R.
2019. Proceedings of the 20th International Workshop on Ceramic Breeder Blanket Interactions (CBBI-20) : September 18-20, 2019, KIT, Germany. Ed.: Regina Knitter, 13–19, Karlsruher Institut für Technologie (KIT)

Power Quality in Smart Distribution Systems with Electric Battery, Large Loads and PV Generation
Munoz Ortiz, M.; Petersen, I.; Mikut, R.; Landsverk, H.; Simonsen, S. H.
2019. Proceedings of the 13th International Renewable Energy Storage Conference 2019 (IRES 2019). Ed.: C. Trimborn, 97–108

Evaluation of Features for Change Detection in Unstructured Image Data
Münke, F. R.; Bartschat, A.; Chen, Y.; Mikut, R.; Reischl, M.
2019. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. Ed.: F. Hoffmann, E. Hüllermeier, R. Mikut, 1–23, KIT Scientific Publishing

A Comparison of Economic MPC Formulations for Thermal Building Control
Zwickel, P.; Engelmann, A.; Gröll, L.; Hagenmeyer, V.; Sauer, D.; Faulwasser, T.
2019. 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, RO, September 29 - October 2, 2019, Article no: 8905593, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEurope.2019.8905593

Influence of Synthetic Label Image Object Properties on GAN Supported Segmentation Pipelines
Böhland, M.; Scherr, T.; Bartschat, A.; Mikut, R.; Reischl, M.
2019. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. Ed.: F. Hoffmann, E. Hüllermeier, R. Mikut, 289–309, KIT Scientific Publishing

Data-driven charging strategies for grid-beneficial, customer-oriented and battery-preserving electric mobility
Schwenk, K.; Harr, T.; Großmann, R.; Appino, R. R.; Hagenmeyer, V.; Mikut, R.
2019. Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019. Ed.: F. Hoffmann, E. Hüllermeier, R. Mikut, 73–93, KIT Scientific Publishing

Relative Gain Array and Singular Value Analysis to Improve the Control in a Biomass Pyrolysis Process
Hofmann, J.; Holz, H.-C.; Gröll, L.
2019. 2019 IEEE 15th International Conference on Control and Automation (ICCA 2019), Edinburgh, UK, July 16-19, 2019, 596–603, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICCA.2019.8900025

Detection and Localization of Manipulated Smart Meters Using Super State Hidden Markov Models
Gabriel, R.; Matthes, J.; Keller, H. B.; Hagenmeyer, V.
2019. 2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm), Beijing, China, 21-23 Oct. 2019, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm.2019.8909702

Semantic CIM2Matpower: Ontology-Based Network Topology Processor and Converter for CIM Node-Breaker Models
Schumilin, A.; Cakmak, H. K.; Stucky, K.-U.; Duepmeier, C.; Hagenmeyer, V.
2019. Proceedings of the 7th International Conference on Smart Energy Grid Engineering (SEGE 2019), Ottawa, CDN, August 12-14, 2018, 31–36, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE.2019.8859820

Exploiting Unused Capacity in the Grid
Priebe, J.; Wehbring, N.; Chang, H.; Moser, A.; Cakmak, H. K.; Kühnapfel, U.; Hagenmeyer, V.
2019. 2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia), Chengdu, China, 21-24 May 2019, 451–456, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGT-Asia.2019.8880909

Total Cost of Ownership for different state of the art FDM Machines
Fauth, J.; Elkaseer, A.; Scholz, S. G.
2019. Sustainable Design and Manufacturing 2019 : Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19) - Budapest, Hungary, 4 - 5 July 2019. Ed.: P. Ball, 351–361, Springer

Automated Extraction of Domain-Specific Information from Scientific Publications
Kief, P.; Marquardt, C.; Nau, K.; Scholz, S.; Schmidt, A.
2019. 8th International Conference on Data Analytics, Porto, P, September 22-26, 2019

Domain is of the Essence: Data Deployment for City-Scale Multi-Camera Vehicle Re-Identification
Schutera, M.; Hafner, F. M.; Vogt, H.; Abhau, J.; Reischl, M.
2019. International Workshop on Traffic and Street Surveillance for Safety and Security: in conjuction with IEEE AVSS 2019, September 21th, Taipei, Taiwan, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/AVSS.2019.8909858

Diagnosespektrum somatischer Komorbiditäten und psychische Belastung bei unterschiedlichen AVEM Mustern in der Psychosomatischen Rehabilitation
Wittmann, C.; Reischl, M.; Käfer, M.; Köllner, V.
2019. Deutscher Kongress für Psychosomatische Medizin und Psychotherapie, Berlin, 20.-22.03.2019. doi:10.13140/RG.2.2.34331.31521

Towards Classification of Technical Sound Events with Deep Learning Models
Rieder, C.; German, M.; Scherer, K.-P.
2019. Wissensmanagement in digitalen Arbeitswelten – Aktuelle Ansätze und Perspektiven (Knowledge Management in Digital Work - Environments State-of-the-Art and Outlook) - Proceedings, 10. Konferenz Professionelles Wissensmanagement, 18. - 20.03.2019, Potsdam, Germany. Ed.: P. Heisig, 297–302, FHP Verlag

Application of image-based process parameters for analyzing multi-fuel burners
Vogelbacher, M.; Waibel, P.; Matthes, J.; Keller, H. B.
2019. 9th European Combustion Meeting (ECM 2019), Lisboa, P, April 14-17, 2019

Heuristics for Transmission Expansion Planning in Low-Carbon Energy System Models
Neumann, F.; Brown, T.
2019. 16th International Conference on the European Energy Market (EEM 19), 18 - 20 September 2019, Ljubljana, Slovenia, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM.2019.8916411

Image-based analysis of flames in industrial afterburner chambers using geometric constraints
Waibel, P.; Matthes, J.; Vogelbacher, M.; Gröll, L.; Keller, H. B.
2019. 9th European Combustion Meeting : (ECM 2019), 14-17 April 2019, Lisboa, Portugal

A new camera-based flame stability measure for non-oscillating and oscillating combustion [in press]
Matthes, J.; Waibel, P.; Vogelbacher, M.; Gehrmann, H.-J.; Keller, H. B.
2019. 9th European Combustion Meeting : (ECM 2019), 14-17 April 2019, Lisboa, Portugal

A new camera-based method for measuring the flame stability of non-oscillating and oscillating combustions
Matthes, J.; Waibel, P.; Vogelbacher, M.; Gehrmann, H.-J.; Keller, H. B.
2019. 9th European Combustion Meeting : (ECM 2019), 14-17 April 2019, Lisboa, Portugal

A hybrid analysis approach for transient stability assessment in power systems
Kyesswa, M.; Cakmak, H. K.; Gröll, L.; Kuhnapfel, U.; Hagenmeyer, V.
2019. 2019 IEEE Milan PowerTech, 23-27 June 2019, Milan, Italy, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PTC.2019.8810745

Optimal adaptive power flow linearizations: Expected error minimization using polynomial chaos expansion
Mühlpfordt, T.; Hagenmeyer, V.; Molzahn, D. K.; Misra, S.
2019. 2019 IEEE Milan PowerTech, 23-27 June 2019, Milan, Italy, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PTC.2019.8810681

A method for sizing centralised energy storage systems using standard patterns
Karrari, S.; Ludwig, N.; Hagenmeyer, V.; Noe, M.
2019. 2019 IEEE Milan PowerTech, 23-27 June 2019, Milan, Italy, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PTC.2019.8810658

Decomposition-based methods for optimization of time-dependent problems
Engelmann, A.; Faulwasser, T.
2019. 6th International conference on Continuous Optimization (ICCOPT 2019), Berlin, 5.-8. August 2019

Determination of Feasible Power Variability Ranges in Active Distribution Networks with Uncertain Generation and Demand
Noto, G.; Hagenmeyer, V.; Appino, R. R.; Chicco, G.
2019. IEEE Milan PowerTech, Milan, Italy, 23-27 June 2019: proceedings, 1–6, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PTC.2019.8810592

Automated fabrication of multi-layer printed electronic circuits using a novel vector ink-jet printing process control and surface mounting of discrete components [in press]
Gengenbach, U.; Ungerer, M.; Koker, L.; Reichert, K.-M.; Stiller, P.; Huang, C.; Hagenmeyer, V.
2019. Joint Conference - 8th IFAC Symposium on Mechatronic Systems - 11th Symposium on Nonlinear Control Systems, September 4-6, 2019, Vienna, Austria

Building Energy Simulations at Urban Scale Based on Standardised Data Models [in press]
Geiger, A.; Benner, J.; Häfele, K.-H.; Hagenmeyer, V.
2019. Proceedings of Building Simulation 2019: 16th Conference of IBPSA. Ed.: V. Corrado, International Building Performance Simulation Association (IBPSA)

Ein Microservice für die Abstraktion von Suchmaschinen
Schlachter, T.; Schmitt, C.; Wagner, H.
2019. EuroInfo - environmental informatics : computational sustainability: ICT methods to achieve the UN sustainable development goals : adjunct proceedings of the 33rd edition of the EnviroInfo - the long standing and established international and interdisciplinary conference series on leading environmental information and communication technologies : Kassel, September 23-26, 2019. Hrsg.: R. Schaldach, 143–150, Shaker Verlag

Prediction of Dimensional Error in Down-Facing Surfaces for Laser Powder Bed Fusion Parts [in press]
Charles, A. P.; Elkaseer, A.; Hagenmeyer, V.; Scholz, S.
2019. 3RD World Congress on Micro and Nano Manufacturing, Raleigh WCMNM 2019, North Carolina, USA, 10th - 12th September

FDM Process Optimisation for Low Surface Roughness and Energy Consumption
Elkaseer, A.; Schneider, S.; Scholz, S.
2019. 3RD World Congress on Micro and Nano Manufacturing, Raleigh WCMNM 2019, North Carolina, USA, 10th - 12th September

ANN-based modelling of dimensional accuracy in L-PBF
Charles, A. P.; Elkaseer, A.; Salem, M.
2019. Conference Proceedings - Special Interest Group : Advancing Precision in Additive Manufacturing 2019, 16th - 18th September 2019, Nantes, France, European Society for Precision Engineering and Nanotechnology (euspen)

Potential and Challenges of Inkjet-Printing for Wearable Medical Devices [in press]
Koker, L.; Mansour, M.; Ungerer, M.; Reichert, K.-M.; Stiller, P.; Gegenbach, U.
2019. BMT 2019 : 53th Annual Conference of the German Society for Biomedical Engineering : 25. - 26. September 2019, Frankfurt am Main. Ed.: J. Haueisen

Design of aspheric rotation optics
Sieber, I.
2019. Frontiers in Optics + Laser Science APS/DLS, Washington, DC, September 13-17, 2019, FM4C.3, Optica Publishing Group (OSA). doi:10.1364/FIO.2019.FM4C.3

Synchronized continuous high-rate time-series recording in distribution grids for accurate evaluation
Jumar, R.; Maaß, H.; Kühnapfel, U.; Hagenmeyer, V.
2019. 2019 International Conference on Smart Grid Synchronized Measurements and Analytics, SGSMA 2019; Texas A and M UniversityCollege Station; United States; 20 May 2019 through 23 May 2019, Art.-Nr.: 8784664, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SGSMA.2019.8784664

Concept for a Permanent, Non-Invasive Blood Pressure Measurement in the Ear
Zeilfelder, J.; Diehl, M.; Pylatiuk, C.; Stork, W.
2019. Proceedings 2019 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI), Chicago, IL, USA, 19-22 May 2019, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/BHI.2019.8834671

A Study on the Modeling and Simulation of Bio-inspired Hedgehog Spines Structures for More Efficient Use Digital Manufacturing Processes
O’Sullivan, R.; Rees, A.; Griffiths, C. A.; Wadlinger, J.
2019. Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19), Budapest, Ungarn, 4 - 5 Juli 2019. Ed.: P. Ball, 375–385, Springer. doi:10.1007/978-981-13-9271-9_31

Industrial demand-side flexibility: A benchmark data set
Ludwig, N.; Barth, L.; Wagner, D.; Hagenmeyer, V.
2019. Proceedings of the Tenth ACM International Conference on Future Energy Systems - e-Energy ’19, Phoenix, AZ, USA, June 25 - 28, 2019, 460–473, Association for Computing Machinery (ACM). doi:10.1145/3307772.3331021

Internet of Things Solution for Non-invasive Vital Data Acquisition: A Step Towards Smart Healthcare System
Salem, M.; El-Maddah, I.; Youssef, K.; Mohamed, H.
2019. Sustainable Design and Manufacturing 2019 : Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19). Ed.: P. Ball, 387–397, Springer Nature. doi:10.1007/978-981-13-9271-9_32

Robust phase unwrapping based on non-coprime fringe pattern periods for deflectometry measurements
Allgeier, S.; Gengenbach, U.; Köhler, B.; Reichert, K.-M.; Hagenmeyer, V.
2019. Automated Visual Inspection and Machine Vision III - SPIE Optical Metrology, 2019, Munich, Germany, 24-27 JUNE 2019. Ed.: J. Beyerer, F. Puente León, 1106103, Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2523564

On the Assessment of Thermo-mechanical Degradability of Multi-recycled ABS Polymer for 3D Printing Applications
Charles, A. P.; Bassan, P. M.; Mueller, T.; Elkaseer, A.; Scholz, S. G.
2019. Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19), Budapest, Ungarn, 4 - 5 Juli 2019. Ed.: P. Ball, 363–373, Springer. doi:10.1007/978-981-13-9271-9_30

Safe by Design in 3D printing
Nau, K.; Scholz, S. G.
2019. Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19), Budapest, Ungarn, 4 - 5 Juli 2019. Ed.: P. Ball, 341–350, Springer. doi:10.1007/978-981-13-9271-9_28

Total Cost of Ownership for Different State of the Art FDM Machines (3D Printers)
Fauth, J.; Elkaseer, A.; Scholz, S. G.
2019. Proceedings of the 6th International Conference on Sustainable Design and Manufacturing (KES-SDM 19), Budapest, Ungarn, 4 - 5 Juli 2019. Ed.: P. Ball, 351–361, Springer. doi:10.1007/978-981-13-9271-9_29

Assessment of a scheduling strategy for dispatching prosumption of an industrial campus
Remo Appino, R.; Ángel González Ordiano, J.; Munze, N.; Mikut, R.; Faulwasser, T.; Hagenmeyer, V.
2019. Internationaler ETG-Kongress 2019 : das Gesamtsystem im Fokus der Energiewende, 8. – 9. Mai 2019, Neckar Forum, Esslingen am Neckar. Hrsg.: C. Rehtanz, 289–294, VDE Verlag

Design-for-manufacture of high-resolution 3D printed rotation optics
Sieber, I.; Moser, D.; Gengenbach, U.
2019. Optical Fabrication and Testing 2019. Design and Fabrication Congress 2019, Washington, DC, June 10-12, 2019, JW3A.2, Optica Publishing Group (OSA). doi:10.1364/FREEFORM.2019.JW3A.2

Powerful data analysis and composition with the UNIX-shell
Schmidt, A.; Scholz, S.
2019. Web Engineering: 19th International Conference on Web Engineering, ICWE 2019; Daejeon; South Korea; 11 June 2019 through 14 June 2019. Ed.: M. Bakaev, 582–585, Springer Nature. doi:10.1007/978-3-030-19274-7_49

Open Source 3-Phase Function Generator for Smart Grid Experiments and Monitoring Device Testing
Jumar, R.; Erdmann, A.; Maaß, H.; Kühnapfel, U.; Hagenmeyer, V.
2019. 2nd International Colloquium on Smart Grid Metrology (SMAGRIMET), Split, Croatia, 9-12 April 2019, 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/SMAGRIMET.2019.8720387

Implementierung eines Werkzeuges zur Interpretation von Versorgungsnetzen aus dem Programmsystem STANET
Riester, M.; Geiger, A.
2019. REAL CORP 2019. Ed.: M. Schrenk, Karlsruher Institut für Technologie (KIT)

Machine learning aided phase retrieval algorithm for beam splitting with an LCoS-SLM
Mikhaylov, D.; Zhou, B.; Kiedrowski, T.; Mikut, R.; Lasagni, A. F.
2019. Laser Resonators, Microresonators, and Beam Control XXI. Ed.: A.V. Kudryashov, 10 S., Society of Photo-optical Instrumentation Engineers (SPIE). doi:10.1117/12.2508673

Context-Aware Visualization of Entity-Entity Relationships in a Document Corpus
Schmidt, A.; Kief, P.; Scholz, S.
2019. Databases Theory and Applications : 30th Australasian Database Conference, ADC 2019, Sydney, AUS, January 29 – February 1, 2019, Proceedings. Ed.: L. Chang, 135–138, Springer. doi:10.1007/978-3-030-12079-5_10

Breakthrough in permanent cooling of instrumentation electronics - Results of systematic experimental & Analytical refrigerant selection, dynamic seals evaluation and robust engine design
Holbein, B.
2019. Geothermal Resources Council 2018 Annual Meeting: Geothermal’s Role in Today’s Energy Market, GRC 2018; Peppermill Resort Spa CasinoReno; United States; 14 October 2018 through 17 October 2018, 1948–1960, Geothermal Resources Council

Definition von Flexibilität in einem zellulär geprägten Energiesystem
Lehmann, N.; Kraft, E.; Duepmeier, C.; Mauser, I.; Förderer, K.; Sauer, D.
2019. Zukünftige Stromnetze 2019 : 30./31. Januar 2019 in Berlin, 459–469, Conexio

6. HSN-Fachsymposium Innovative Sensorik, verteilte Sensorsysteme, neue Technologien und anwendungsfelder
Keller, H. B.; Seifert, R. (Eds.)
2019. Karlsruher Institut für Technologie (KIT)

Proceedings - 29. Workshop Computational Intelligence, Dortmund, 28. - 29. November 2019
Hoffmann, F.; Hüllermeier, E.; Mikut, R. (Eds.)
2019. KIT Scientific Publishing. doi:10.5445/KSP/1000098736

Smart Energy Grid der Zukunft - Securityprobleme und Lösungsansätze
Keller, H. B.
2019. FORUM46 – Interdisziplinäres Forum für Europa e. V

Energy Models
Hörsch, J.
2019

Benchmark Dataset for "Industrial Demand-Side Flexibility: A Benchmark Data Set"
Ludwig, N.; Barth, L.; Wagner, D.; Hagenmeyer, V.
2019. doi:10.5445/IR/1000094324

Analyzing the Enron Corpus with the Shell
Schmidt, A.
2019

Ausblick und Schlussbemerkung
Weissenbach, K.; Föll, J.
2018. UIS BW, Umweltinformationssystem Baden-Württemberg, F+E-Vorhaben INOVUM, Innovative Umweltinformationssysteme. Phase II 2016/18. Hrsg.: K. Weissenbach, 105–108, KIT Scientific Publishing. doi:10.5445/IR/1000086932

Luftmessdaten. Komponenten und Dienste für die Verarbeitung und Präsentation von Messdaten am Beispiel des Webauftritts Luft
Schlachter, T.; Braun, E.; Schmitt, C.; Schillinger, W.; Lutz-Holzhauer, C.; Nadberezny, D.; Müller, H.; Grodt, D.; Koch, L.
2018. UIS BW, Umweltinformationssystem Baden-Württemberg, F+E-Vorhaben INOVUM, Innovative Umweltinformationssysteme. Phase II 2016/18. . Hrsg.: K. Weissenbach, 91–104, KIT Scientific Publishing. doi:10.5445/IR/1000086930

LUPO Landesumweltportale als modularisierte, verteilte Anwendung
Schlachter, T.; Greceanu, C.; Grieß, C.; Schmitt, C.; Schillinger, W.; Tauber, M.; Hänig, K.; Koch, L.; Niemeier, R.
2018. UIS BW, Umweltinformationssystem Baden-Württemberg, F+E-Vorhaben INOVUM, Innovative Umweltinformationssysteme. Phase II 2016/18. Hrsg.: K. Weissenbach, 51–61, KIT Scientific Publishing. doi:10.5445/IR/1000086928

LUPO mobil Intelligente Umweltassistenten im Rahmen der LUPO-Kooperation für mobile Anwendungen
Koch, L.; Hänig, K.; Hibbeler, C.; Schlachter, T.; Schillinger, W.; Scherrer, M.; Becker, J.; Weissenbach, K.; Föll, J.
2018. UIS BW, Umweltinformationssystem Baden-Württemberg, F+E-Vorhaben INOVUM, Innovative Umweltinformationssysteme. Phase II 2016/18. . Hrsg.: K. Weissenbach, 41–50, KIT Scientific Publishing. doi:10.5445/IR/1000086707

Technical Safety – An Attribute of Quality : An Interdisciplinary Approach and Guideline
Keller, H.; Pilz, W.-D.; Schulz-Forberg, B.; Langenbach, C.
2018. Springer. doi:10.1007/978-3-319-68625-7

Interactive and Quantitative Knowledge-Discovery in Large-Scale 3D Tracking Data. PhD dissertation
Schott, B.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000088877

Ein neues Konzept für die semantische Suche in heterogenen Informationssystemen zu Fragestellungen aus Umwelt und Energie. PhD dissertation
Schlachter, T.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000087829

Eine neue Methode zur kamerabasierten Analyse von Mehrstoffbrennern in industriellen Verbrennungsprozessen. PhD dissertation
Vogelbacher, M.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000086871

Design and Development of Imaging Platforms for Phenotypic Characterization of Early Zebrafish. PhD dissertation
Marcato, D.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000085054

Konzept zur datengetriebenen Analyse und Modellierung des preisbeeinflussten Verbrauchsverhaltens. PhD dissertation
Waczowicz, S.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000081003

Eine neue Methode zum robusten Entwurf von Regressionsmodellen bei beschränkter Rohdatenqualität. PhD dissertation
Doneit, W.
2018. Karlsruher Institut für Technologie (KIT). doi:10.5445/IR/1000080577

Insecurity of A Key-Policy Attribute Based Encryption Scheme With Equality Test
Liao, Y.; Chen, H.; Li, F.; Jiang, S.; Zhou, S.; Ramadan, M.
2018. IEEE Access, 6, 10189–10196. doi:10.1109/ACCESS.2018.2808944

Cross-sectional image quality improvements in 3D corneal confocal laser scanning microscopy
Bohn, S.; Sperlich, K.; Prakasam, R.; Allgeier, S.; Reichert, K.-M.; Bartschat, A.; Stolz, H.; Guthoff, R.; Köhler, B.; Mikut, R.; Stachs, O.
2018. Der Ophthalmologe, 115 (Suppl 1), 74

Comparison of Machine Learning Approaches for Time-series-based Quality Monitoring of Resistance Spot Welding (RSW)
Zhou, B.; Pychynski, T.; Reischl, M.; Mikut, R.
2018. Archives of Data Science, Series A (Online First), 5 (1), A13, 17 S. online. doi:10.5445/KSP/1000087327/13

Vision digitale Zukunft. Cyber Security Problematik und Lösungsansätze
Keller, H. B.
2018. Sicherheit + Management, 27 (11), 60–62

Design studies of varifocal rotation optics
Sieber, I.; Stiller, P.; Gengenbach, U.
2018. Optical engineering, 57 (12), 125102/1–7. doi:10.1117/1.OE.57.12.125102

Systems Genetics Approach to Study Congenital Heart Disease in a Fish Model
Gierten, J.; Loosli, F.; Gehrig, J.; Pylatiuk, C.; Fitzgerald, T.; Birney, E.; Wittbrodt, J.; Gorenflo, M.
2018. The thoracic and cardiovascular surgeon, 66 (S02). doi:10.1055/s-0038-1628326

Nonlinear dynamics, optimization and control of distributed energy systems. 661.WE-Heraeus-Seminar
Faulwasser, T.; Knebel, J.; Robinius, M.; Witthaut, D.
2018. Physik-Journal, 17 (5), 62

Credit Cycles and Monetary Policy in a Model with Regime Switches
Faulwasser, T.; Gross, M.; Semmler, W.
2018. SSRN eLibrary, 54 Seiten. doi:10.2139/ssrn.3288763

Optimal Power Flow Subject to Non-Gaussian Stochastic Uncertainties: An L²-based Approach
Mühlpfordt, T.; Faulwasser, T.; Hagenmeyer, V.
2018. Proceedings in applied mathematics and mechanics, 18 (1, SI), e201800371. doi:10.1002/pamm.201800371

Mixed-Integer vs. Real-Valued Formulations of Battery Scheduling Problems
Murray, A.; Faulwasser, T.; Hagenmeyer, V.
2018. IFAC-PapersOnLine, 51 (28), 350–355. doi:10.1016/j.ifacol.2018.11.727

Hierarchical Distributed Mixed-Integer Optimization for Reactive Power Dispatch
Murray, A.; Engelmann, A.; Hagenmeyer, V.; Faulwasser, T.
2018. IFAC-PapersOnLine, 51 (28), 368–373. doi:10.1016/j.ifacol.2018.11.730

Optimierung in der Automatisierungstechnik
Graichen, K.; Gröll, L.
2018. Automatisierungstechnik, 66 (11), 875–876. doi:10.1515/auto-2018-0122

Reliable Dispatch of Renewable Generation via Charging of Time-varying PEV Populations
Appino, R. R.; Munoz-Ortiz, M.; Gonzalez Ordiano, J. A.; Mikut, R.; Hagenmeyer, V.; Faulwasser, T.
2018. IEEE transactions on power systems, 34 (2), 1558–1568. doi:10.1109/TPWRS.2018.2873409

Author Correction: 3D biodegradable scaffolds of polycaprolactone with silicate-containing hydroxyapatite microparticles for bone tissue engineering: high-resolution tomography and in vitro study
Shkarina, S.; Shkarin, R.; Weinhardt, V.; Melnik, E.; Vacun, G.; Kluger, P. J.; Loza, K.; Epple, M.; Ivlev, S. I.; Baumbach, T.; Surmeneva, M. A.; Surmenev, R. A.
2018. Scientific reports, 8 (1), Article No 17589. doi:10.1038/s41598-018-35952-w

Therapeutic Chemical Screen Identifies Phosphatase Inhibitors to Reconstitute PKB Phosphorylation and Cardiac Contractility in ILK-Deficient Zebrafish
Pott, A.; Shahid, M.; Köhler, D.; Pylatiuk, C.; Weinmann, K.; Just, S.; Rottbauer, W.
2018. Biomolecules, 8 (4), Art. Nr.: 153. doi:10.3390/biom8040153

Metrology data-based simulation of freeform optics
Sieber, I.; Yi, A. Y.; Gengenbach, U.
2018. Applied Sciences, 8 (12), Art. Nr.: 2338. doi:10.3390/app8122338

Asymptotic Stability of Economic NMPC: The Importance of Adjoints
Faulwasser, T.; Zanon, M.
2018. IFAC-PapersOnLine, 51 (20), 157–168. doi:10.1016/j.ifacol.2018.11.009

Klassifikation von Optimierungsproblemen
Gröll, L.
2018. Automatisierungstechnik, 66 (11), 903–927. doi:10.1515/auto-2018-0081

Reflection on boon and bane of Water Absorbing Components in Active Implants during Package Testing and Operation
Koker, L.; Gengenbach, U.; Bretthauer, G.
2018. Current directions in biomedical engineering, 4 (1), 319–322. doi:10.1515/cdbme-2018-0077

Reflection on boon and bane of Water Absorbing Components in Active Implants during Operation and Package Testing
Koker, L.; Gengenbach, U.; Bretthauer, G.
2018. Biomedical engineering, 63 (S1), S218

Effect of low-temperature plasma treatment of electrospun polycaprolactone fibrous scaffolds on calcium carbonate mineralisation
Ivanova, A. A.; Syromotina, D. S.; Shkarina, S. N.; Shkarin, R.; Cecilia, A.; Weinhardt, V.; Baumbach, T.; Saveleva, M. S.; Gorin, D. A.; Douglas, T. E. L.; Parakhonskiy, B. V.; Skirtach, A. G.; Cools, P.; De Geyter, N.; Morent, R.; Oehr, C.; Surmeneva, M. A.; Surmenev, R. A.
2018. RSC Advances, 8 (68), 39106–39114. doi:10.1039/c8ra07386d

Quantification of environmental influences and interferences affecting an active lens implant
Koker, L.; Stoll. Matthias; Gengenbach, U.; Bretthauer, G.
2018. Biomedical engineering, 63 (S1), S347

Principal flow patterns across renewable electricity networks
Hofmann, F.; Schäfer, M.; Brown, T.; Hörsch, J.; Schramm, S.; Greiner, M.
2018. epl, 124 (1), Article No.18005. doi:10.1209/0295-5075/124/18005

Quantitative morphometric analysis of adult teleost fish by X-ray computed tomography
Weinhardt, V.; Shkarin, R.; Wernet, T.; Wittbrodt, J.; Baumbach, T.; Loosli, F.
2018. Scientific reports, 8 (1), Art. Nr.: 16531. doi:10.1038/s41598-018-34848-z

Characterization of Road Condition with Data Mining Based on Measured Kinematic Vehicle Parameters
Masino, J.; Thumm, J.; Levasseur, G.; Frey, M.; Gauterin, F.; Mikut, R.; Reischl, M.
2018. Journal of advanced transportation, 2018, Article: 8647607. doi:10.1155/2018/8647607

Analysis of focus shift speed for in vivo 3D corneal confocal microscopy
Allgeier, S.; Bartschat, A.; Bohn, S.; Reichert, K.-M.; Sperlich, K.; Mikut, R.; Stachs, O.; Köhler, B.
2018. Biomedical engineering, 63 (s1), S192. doi:10.1515/bmt-2018-6037

Corneal Subbasal Nerve Plexus Changes in Severe Diabetic Charcot Foot Deformity: A Pilot Study in Search for a DNOAP Biomarker
Herlyn, A.; Prakasam, R. K.; Peschel, S.; Allgeier, S.; Köhler, B.; Winter, K.; Guthoff, R. F.; Mittlmeier, T.; Stachs, O.
2018. Journal of diabetes research, 2018, Art. Nr.: 5910639. doi:10.1155/2018/5910639

Wear behaviour of grey cast iron with the presence of copper addition
Abdou, S.; Elkaseer, A.; Kouta, H.; Abu Qudeiri, J.
2018. Advances in mechanical engineering, 10 (10), 1–8. doi:10.1177/1687814018804741

Adaptation strategies for tracking constraints under plant-model mismatch
Singhal, M.; Faulwasser, T.; Bonvin, D.
2018. IFAC-PapersOnLine, 51 (18), 833–838. doi:10.1016/j.ifacol.2018.09.254

A generalized framework for chance-constrained optimal power flow
Mühlpfordt, T.; Faulwasser, T.; Hagenmeyer, V.
2018. Sustainable energy, grids and networks, 16, 231–242. doi:10.1016/j.segan.2018.08.002

PyPSA-Eur: An open optimisation model of the European transmission system
Hörsch, J.; Hofmann, F.; Schlachtberger, D.; Brown, T.
2018. Energy strategy reviews, 22, 207–215. doi:10.1016/j.esr.2018.08.012

The impact of climate change on a cost-optimal highly renewable European electricity network
Schlott, M.; Kies, A.; Brown, T.; Schramm, S.; Greiner, M.
2018. Applied energy, 230, 1645–1659. doi:10.1016/j.apenergy.2018.09.084

Cost optimal scenarios of a future highly renewable European electricity system: Exploring the influence of weather data, cost parameters and policy constraints
Schlachtberger, D. P.; Brown, T.; Schäfer, M.; Schramm, S.; Greiner, M.
2018. Energy, 163, 100–114. doi:10.1016/j.energy.2018.08.070

A hybrid auricular control system: direct, simultaneous, and proportional myoelectric control of two degrees of freedom in prosthetic hands
Schmalfuss, L.; Hahne, J.; Farina, D.; Hewitt, M.; Kogut, A.; Doneit, W.; Reischl, M.; Rupp, R.; Liebetanz, D.
2018. Journal of neural engineering, 15 (5), 056028. doi:10.1088/1741-2552/aad727

Distinct amino acid motifs carrying multiple positive charges regulate membrane targeting of dysferlin and MG53
Zhou, L.; Middel, V.; Reischl, M.; Strähle, U.; Nienhaus, G. U.
2018. PLoS one, 13 (8), e0202052. doi:10.1371/journal.pone.0202052

Comparison of lossless compression schemes for high rate electrical grid time series for smart grid monitoring and analysis
Jumar, R.; Maaß, H.; Hagenmeyer, V.
2018. Computers & electrical engineering, 71, 465–476. doi:10.1016/j.compeleceng.2018.07.008

Wnt/PCP controls spreading of Wnt/β-catenin signals by cytonemes in vertebrates
Mattes, B.; Dang, Y.; Greicius, G.; Kaufmann, L. T.; Prunsche, B.; Rosenbauer, J.; Stegmaier, J.; Mikut, R.; Özbek, S.; Nienhaus, G. U.; Schug, A.; Virshup, D. M.; Scholpp, S.
2018. eLife, 7, Article No. e36953. doi:10.7554/eLife.36953

Droplet microarray: Miniaturized platform for rapid formation and high-throughput screening of embryoid bodies
Tronser, T.; Demir, K.; Reischl, M.; Bastmeyer, M.; Levkin, P. A.
2018. Lab on a chip, 18 (15), 2257–2269. doi:10.1039/c8lc00450a

Cortical representation of auricular muscles in humans: A robot-controlled TMS mapping and fMRI study
Meincke, J.; Hewitt, M.; Reischl, M.; Rupp, R.; Schmidt-Samoa, C.; Liebetanz, D.
2018. PLoS one, 13 (7), e0201277. doi:10.1371/journal.pone.0201277

Optimal power flow: An introduction to predictive, distributed and stochastic control challenges
Faulwasser, T.; Engelmann, A.; Mühlpfordt, T.; Hagenmeyer, V.
2018. Automatisierungstechnik, 66 (7), 573–589. doi:10.1515/auto-2018-0040

Investigation on refrigerant transport by capillary effect with fleeces in an evaporator for a high temperature cooling machine [Étude sur le transport de frigorigène par effet de capillarité avec des molletons dans un évaporateur pour une machine de refroidissement à haute température]
Holbein, B.; Schulenberg, T.
2018. International journal of refrigeration, 93, 18–28. doi:10.1016/j.ijrefrig.2018.05.036

Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system
Brown, T.; Schlachtberger, D.; Kies, A.; Schramm, S.; Greiner, M.
2018. Energy, 160, 720–739. doi:10.1016/j.energy.2018.06.222

Third-generation in situ hybridization chain reaction: Multiplexed, quantitative, sensitive, versatile, robust
Choi, H. M. T.; Schwarzkopf, M.; Fornace, M. E.; Acharya, A.; Artavanis, G.; Stegmaier, J.; Cunha, A.; Pierce, N. A.
2018. Development <Cambridge>, 145 (12), Art. Nr.: dev165753. doi:10.1242/dev.165753

Characterisation of high-temperature jet break-up for ceramic sphere production
Leys, O.; Waibel, P.; Matthes, J.; Keller, H.; Knitter, R.
2018. The international journal of advanced manufacturing technology, 98 (9–12), 2311–2318. doi:10.1007/s00170-018-2378-y

Slit lamp microscopy on a cellular level using in vivo confocal laser scanning microscopy
Bohn, S.; Sperlich, K.; Kala Praksam, R.; Allgeier, S.; Reichert, K.-M.; Bartschat, A.; Stolz, H.; Guthoff, R. F.; Köhler, B.; Mikut, R.; Stachs, O.
2018. Investigative ophthalmology & visual science, 59 (9), 3439

Replication of Overmolded Orthopedic Implants with a Functionalized Thin Layer of Biodegradable Polymer
Elkaseer, A.; Mueller, T.; Azcarate, S.; Philipp-Pichler, M.; Wilfinger, T.; Wittner, W.; Prantl, M.; Sampaio, D.; Hagenmeyer, V.; Scholz, S.
2018. Polymers, 10 (7), Article: 707. doi:10.3390/polym10070707

A distributed feasible-side convergent modifier-adaptation scheme for interconnected systems, with application to gas-compressor stations
Milosavljevic, P.; Schneider, R.; Cortinovis, A.; Faulwasser, T.; Bonvin, D.
2018. Computers & chemical engineering, 115, 474–486. doi:10.1016/j.compchemeng.2018.05.006

MPC-DICE: An open-source Matlab implementation of receding horizon solutions to DICE
Faulwasser, T.; Kellett, C. M.; Weller, S. R.
2018. IFAC-PapersOnLine, 51 (5), 120–125. doi:10.1016/j.ifacol.2018.06.221

Towards a FAIR-DICE IAM: Combining DICE and FAIR Models
Faulwasser, T.; Nydestedt, R.; Kellett, C. M.; Weller, S. R.
2018. IFAC-PapersOnLine, 51 (5), 126–131. doi:10.1016/j.ifacol.2018.06.222

3D biodegradable scaffolds of polycaprolactone with silicate-containing hydroxyapatite microparticles for bone tissue engineering: high-resolution tomography and in vitro study
Shkarina, S.; Shkarin, R.; Weinhardt, V.; Melnik, E.; Vacun, G.; Kluger, P.; Loza, K.; Epple, M.; Ivlev, S. I.; Baumbach, T.; Surmeneva, M. A.; Surmenev, R. A.
2018. Scientific reports, 8 (1), Article: 8907. doi:10.1038/s41598-018-27097-7

Response to ‘Burden of proof: A comprehensive review of the feasibility of 100% renewable-electricity systems’
Brown, T. W.; Bischof-Niemz, T.; Blok, K.; Breyer, C.; Lund, H.; Mathiesen, B. V.
2018. Renewable & sustainable energy reviews, 92, 834–847. doi:10.1016/j.rser.2018.04.113

3D confocal laser-scanning microscopy for large-area imaging of the corneal subbasal nerve plexus
Allgeier, S.; Bartschat, A.; Bohn, S.; Peschel, S.; Reichert, K.-M.; Sperlich, K.; Walckling, M.; Hagenmeyer, V.; Mikut, R.; Stachs, O.; Köhler, B.
2018. Scientific reports, 8 (1), Article Number 7468. doi:10.1038/s41598-018-25915-6

Active directional modifier adaptation for real-time optimization
Singhal, M.; Marchetti, A. G.; Faulwasser, T.; Bonvin, D.
2018. Computers & chemical engineering, 115, 246–261. doi:10.1016/j.compchemeng.2018.02.016

Cellular in vivo 3D imaging of the cornea by confocal laser scanning microscopy
Bohn, S.; Sperlich, K.; Allgeier, S.; Bartschat, A.; Prakasam, R.; Reichert, K.-M.; Stolz, H.; Guthoff, R.; Mikut, R.; Köhler, B.; Stachs, O.
2018. Biomedical optics express, 9 (6), 2511–2525. doi:10.1364/BOE.9.002511

Wide-field corneal subbasal nerve plexus mosaics in age-controlled healthy and type 2 diabetes populations
Lagali, N. S.; Allgeier, S.; Guimarães, P.; Badian, R. A.; Ruggeri, A.; Köhler, B.; Utheim, T. P.; Peebo, B.; Peterson, M.; Dahlin, L. B.; Rolandsson, O.
2018. Scientific data, 5, Art.Nr. 180075. doi:10.1038/sdata.2018.75

Multimodal Hierarchical Imaging of Serial Sections for Finding Specific Cellular Targets within Large Volumes
Wacker, I. U.; Veith, L.; Spomer, W.; Hofmann, A.; Thaler, M.; Hillmer, S.; Gengenbach, U.; Schröder, R. R.
2018. Journal of visualized experiments, 2018 (133), Art.Nr. e57059. doi:10.3791/57059

EmbryoMiner : A new framework for interactive knowledge discovery in large-scale cell tracking data of developing embryos
Schott, B.; Traub, M.; Schlagenhauf, C.; Takamiya, M.; Antritter, T.; Bartschat, A.; Löffler, K.; Blessing, D.; Otte, J. C.; Kobitski, A. Y.; Nienhaus, G. U.; Strähle, U.; Mikut, R.; Stegmaier, J.
2018. PLoS Computational Biology, 14 (4), e1006128. doi:10.1371/journal.pcbi.1006128

In situ 3D nanoprinting of free-form coupling elements for hybrid photonic integration
Dietrich, P.-I.; Blaicher, M.; Reuter, I.; Billah, M.; Hoose, T.; Hofmann, A.; Caer, C.; Dangel, R.; Offrein, B.; Troppenz, U.; Moehrle, M.; Freude, W.; Koos, C.
2018. Nature photonics, 12 (4), 241–247. doi:10.1038/s41566-018-0133-4

Zebrafish: A Pharmacogenetic Model for Anesthesia
Bedell, V.; Buglo, E.; Marcato, D.; Pylatiuk, C.; Mikut, R.; Stegmaier, J.; Scudder, W.; Wray, M.; Züchner, S.; Strähle, U.; Peravali, R.; Dallman, J. E.
2018. Methods in enzymology, 602, 189–209. doi:10.1016/bs.mie.2018.02.004

The DaNa2.0 Knowledge Base Nanomaterials - An Important Measure Accompanying Nanomaterials Development
Krug, H.; Bohmer, N.; Kühnel, D.; Marquardt, C.; Nau, K.; Steinbach, C.
2018. Nanomaterials, 8 (4), 204. doi:10.3390/nano8040204

Kontextsensitive Vorschläge für eine semantische Suchmaschine
Schmidt, A.
2018. Forschung aktuell, 2018, 64–66

Simultaneous Analysis of Sensor Data for Breath Control in Respiratory Air
Seifert, R.; Conrad, T.; Peter, J.; Keller, H.
2018. Chemosensors, 6 (2), 15. doi:10.3390/chemosensors6020015

Rotor-angle versus voltage instability in the third-order model for synchronous generators
Sharafutdinov, K.; Rydin Gorjão, L.; Matthiae, M.; Faulwasser, T.; Witthaut, D.
2018. Chaos, 28 (3), Art.Nr. 033117. doi:10.1063/1.5002889

Experimental analysis of spallation particle trajectories in an arc-jet environment
Bailey, S. C. C.; Bauer, D.; Panerai, F.; Splinter, S. C.; Danehy, P. M.; Hardy, J. M.; Martin, A.
2018. Experimental thermal and fluid science, 93, 319–325. doi:10.1016/j.expthermflusci.2018.01.005

Concept and benchmark results for Big Data energy forecasting based on Apache Spark
González Ordiano, J. Á.; Bartschat, A.; Ludwig, N.; Braun, E.; Waczowicz, S.; Renkamp, N.; Peter, N.; Düpmeier, C.; Mikut, R.; Hagenmeyer, V.
2018. Journal of Big Data, 5 (1), Art.Nr. 11. doi:10.1186/s40537-018-0119-6

Electric discharge machining of titanium and its alloys : review
Abu Qudeiri, J. E.; Mourad, A.-H. I.; Ziout, A.; Abidi, M. H.; Elkaseer, A.
2018. The international journal of advanced manufacturing technology, 96 (1-4), 1319–1339. doi:10.1007/s00170-018-1574-0

The Energy Application Domain Extension for CityGML: enhancing interoperability for urban energy simulations
Agugiaro, G.; Benner, J.; Cipriano, P.; Nouvel, R.
2018. Open geospatial data, software and standards, 3 (1), 2. doi:10.1186/s40965-018-0042-y

Economic MPC without terminal constraints: Gradient-correcting end penalties enforce asymptotic stability
Zanon, M.; Faulwasser, T.
2018. Journal of process control, 63, 1–14. doi:10.1016/j.jprocont.2017.12.005

Robust label-free biosensing using microdisk laser arrays with on-chip references
Wondimu, S. F.; Hippler, M.; Hussal, C.; Hofmann, A.; Krämmer, S.; Lahann, J.; Kalt, H.; Freude, W.; Koos, C.
2018. Optics express, 26 (3), 3161–3173. doi:10.1364/OE.26.003161

Mobile Sensor System AGaMon for Breath Control: Numerical Signal Analysis of Ternary Gas Mixtures and First Field Tests
Seifert, R.; Conrad, T.; Peter, J.; Keller, H. B.
2018. Sensors & transducers, 219 (1), 9–16

Image-Based Characterization of Alternative Fuel Combustion With Multifuel Burners
Vogelbacher, M.; Waibel, P.; Matthes, J.; Keller, H. B.
2018. IEEE transactions on industrial informatics, 14 (2), 588–597. doi:10.1109/TII.2017.2742533

Economic Nonlinear Model Predictive Control
Faulwasser, T.; Grüne, L.; Müller, M. A.
2018. Foundations and trends in systems and control, 5 (1), 224–409. doi:10.1561/2600000014

Abrasive jet drilling of glass sheets: Effect and optimisation of process parameters on kerf taper
Nassef, A.; Elkaseer, A.; Abdelnasser, E. S.; Negm, M.; Qudeiri, J. A.
2018. Advances in mechanical engineering, 10 (1), 1–10. doi:10.1177/1687814017748435

Quality management and improvement for geothermal energy projects using the platform-based tool development technology − ZWERG
Holbein, B.; Dietze, S.; Hurst, F.; Isele, J.; Spatafora, L.; Wiegel, F.; Hagenmeyer, V.
2018. Geothermics, 71, 320–330. doi:10.1016/j.geothermics.2017.10.010

Entwurf robuster optischer Systeme am Beispiel des Künstlichen Akkommodationssystems
Sieber, I.
2018. Automatisierungstechnik, 66 (1), 19–29. doi:10.1515/auto-2017-0074

Fully Automated Pipetting Sorting System for Different Morphological Phenotypes of Zebrafish Embryos
Breitwieser, H.; Dickmeis, T.; Vogt, M.; Ferg, M.; Pylatiuk, C.
2018. SLAS TECHNOLOGY: Translating Life Sciences Innovation, 23 (2), 128–133. doi:10.1177/2472630317745780

Nanopartikel: alles ganz unbedenklich?
Nau, K.; Steinbach, C.; Krug, H.; Kühnel, D.; Bohmer, N.
2018. Die Furche, (04.01.2018)

The corneal subbasal nerve plexus and thickness of the retinal layers in pediatric type 1 diabetes and matched controls
Götze, A.; Keyserlingk, S. von; Peschel, S.; Jacoby, U.; Schreiver, C.; Köhler, B.; Allgeier, S.; Winter, K.; Röhlig, M.; Jünemann, A.; Guthoff, R.; Stachs, O.; Fischer, D.-C.
2018. Scientific reports, 8 (1), Art.Nr. 14. doi:10.1038/s41598-017-18284-z

Hierarchical Distributed ADMM for Predictive Control with Applications in Power Networks
Braun, P.; Faulwasser, T.; Grüne, L.; Kellett, C. M.; Weller, S. R.; Worthmann, K.
2018. IFAC Journal of Systems and Control, 3, 10–22. doi:10.1016/j.ifacsc.2018.01.001

Comments on Truncation Errors for Polynomial Chaos Expansions
Mühlpfordt, T.; Findeisen, R.; Hagenmeyer, V.; Faulwasser, T.
2018. IEEE Control Systems Letters, 2 (1), 169–174. doi:10.1109/LCSYS.2017.2778138

On the use of probabilistic forecasts in scheduling of renewable energy sources coupled to storages
Appino, R. R.; González Ordiano, J. Á.; Mikut, R.; Faulwasser, T.; Hagenmeyer, V.
2018. Applied energy, 210, 207–1218. doi:10.1016/j.apenergy.2017.08.133

A comprehensive modelling framework for demand side flexibility in smart grids
Barth, L.; Ludwig, N.; Mengelkamp, E.; Staudt, P.
2018. Computer science - research and development, 33 (1-2), 13–23. doi:10.1007/s00450-017-0343-x

Optimal Control - Applications and Methods. Special Issue - MPC for Energy Systems: Economic and Distributed Approaches. Vol.39 Issue 1
Faulwasser, T. (Ed.)
2018. doi:10.1002/oca.2406

Expert vs. novice comparison for walking and running using three-dimensional uncontrolled manifold-approach
Möhler, F.; Marahrens, S.; Ringhof, S.; Mikut, R.; Stein, T.
2018. 23rd Annual Congress of the European College of Sport Science. Dublin, Ireland, July 04 - July 07, 2018 - Book of Abstracts. Ed.: M. Murphy, 236, European College of Sport Science (ECSS)

A Cost-efficient Software Testbed for Cyber-Physical Security in IEC 61850-based Substations
Elbez, G.; Keller, H. B.; Hagenmeyer, V.
2018. 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2018; Aalborg; Denmark; 29 October 2018 through 31 October 2018, Art. Nr.: 8587456, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SmartGridComm.2018.8587456

Distributed traffic light control at uncoupled intersections with real-world topology by deep reinforcement learning [in press]
Schutera, M.; Goby, N.; Smolarek, S.; Reischl, M.
2018. Accepted to 32nd Annual Conference on Neural Information Processing Systems (NIPS), Montreal, CDN, December 3-8, 2018

Automatisierte Generierung eines 3D-Baumkatasters am Beispiel des KIT Campus Nord
Kunz, D.; Geiger, A.
2018. 30.Forum Bauinformatik : von jungen Forschenden für junge Forschende. Hrsg.: M. Steiner, 217–224, Bauhaus-Universität Weimar

Automated Versatile DIY Microscope Platform
Pylatiuk, C.; Vogt, M.; Scheikl, P.; Gottwald, and E.
2018. 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 5310–5312, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EMBC.2018.8513465

Multivalent neighborhood heat grid including power-to-heat & shared storage concept
Holbein, B.; Isele, J.; Spatafora, L.; Wiegel, F.; Hagenmeyer, V.
2018. Grand Renewable Energy 2018 International Conference and Exhibition, Pacifico Yokohama, J, June 17-22, 2018. Proceedings on DVD

Transfer learning versus multi-agent learning regarding distributed decision-making in highway traffic
Schutera, M.; Goby, N.; Neumann, D.; Reischl, M.
2018. Proceedings of the Tenth International Workshop on Agents in Traffic and Transportation (ATT 2018) co-located with with the Federated Artificial Intelligence Meeting, including ECAI/IJCAI, AAMAS and ICML 2018 conferences (FAIM 2018), Stockholm, Sweden, July 14, 2018. Ed.: A.L.C. Bazzan, 57–62

ReCal - an innovative mathematical procedure to determine the data of timely recalibration for sensor systems with metal oxide gas sensors
Seifert, R.; Keller, H. B.
2018. SENSORDEVIES 2018 : The 9th International Conference on Sensor Device Technologies and Applications. Ed.: P.E. Cruvinel, 181–184, International Academy, Research, and Industry Association (IARIA)

Real-Time optimization of Uncertain Process Systems via Modifier Adaptation and Gaussian Processes
Avila Ferreira, T. de; Shukla, H. A.; Faulwasser, T.; Jones, C. N.; Bonvin, D.
2018. European Control Conference (ECC18), Limassol, CY, June 12-15, 2018, 465–470, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/ECC.2018.8550397

Optimal Load Sharing for Serial Compressors via Modifier Adaptation
Milosavljevic, P.; Cortinovis, A.; Schneider, R.; Faulwasser, T.; Mercangoz, M.; Bonvin, D.
2018. Proceedings European Control Conference (ECC18), Limassol, CY, June 12-15, 2018, 2306–2311, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/ECC.2018.8550102

A generic distributed microservices and container based framework for metaheuristic optimization
Khalloof, H.; Jakob, W.; Liu, J.; Braun, E.; Shahoud, S.; Duepmeier, C.; Hagenmeyer, V.
2018. Proceedings of the Genetic and Evolutionary Conference Companion, Kyoto, J, July 15-19, 2018, 1363–1370, Association for Computing Machinery (ACM). doi:10.1145/3205651.3208253

An integrated workflow to automatically fabricate flexible electronics by functional printing and SMT component mounting
Gengenbach, U.; Ungerer, M.; Aytac, E.; Koker, L.; Reichert, K. M.; Stiller, P.; Hagenmeyer, V.
2018. Proceedings of the 14th International Conference on Automation Science and Engineering (CASE), Paper ThCT4.4. doi:10.1109/COASE.2018.8560456

Digital Detection and Correction of Errors in As-built Parts: a Step Towards Automated Quality Control of Additive Manufacturing
Elkaseer, A.; Mueller, T.; Charles, A. P.; Scholz, S.
2018. World Congress on Micro and Nano Manufacturing. Ed.: J. Valentincic, 389–392, Research Publishing. doi:10.3850/978-981-11-2728-1_58

Interactive search and exploration of entity-entity relationships in a huge document corpus
Schmidt, A.; Scholz, S.
2018. 10th International Conference on Advances in Databases, Knowledge, and Data Applications. Ed.: A. Schmidt, International Academy, Research, and Industry Association (IARIA)

Cross-Media Mesh Networks for Smart Home and Smart Grid Applications
Wiegel, F.; Hagenmeyer, V.; Oberschmidt, G.
2018. 2018 the 6th IEEE International Conference on Smart Energy Grid Engineering (SEGE), 205–211, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEGE.2018.8499305

A knowledge-based decision support system for micro and nano manufacturing process chains
Müller, T.; Hagenmeyer, V.; Schmidt, A.; Scholz, S.; Elkaseer, A.
2018. Euromicro Conference on Software Engineering and Advanced Applications 2018 (SEAA 2018), Prague, CZ, August 29-31, 2018. Ed.: T. Bures, 314–320, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEAA.2018.00058

Infrared measurements and estimation of temperature in the restrictive scope of an industrial cement plant
Gabriel, R.; Keller, S.; Matthes, J.; Waibel, P.; Keller, H. B.; Hinz, S.
2018. 2018 ISPRS Technical Commission I Midterm Symposium on Innovative Sensing - From Sensors to Methods and Applications; Karlsruhe; Germany; 10 October 2018 through 12 October 2018, 53–60, Curran. doi:10.5194/isprs-annals-IV-1-53-2018

Knowledge-based decision support with self-learning methods
Scherer, K. P.; Rieder, C.; Germann, M.; Baumeister, J.; Plehn, S.
2018. ADVCOMP 2018 : 12th International Conference on Advanced Engineering Computing and Application Sciences Athinai, GR, November 18-22, 2018. Ed.: C.P. Rückemann, 16–17, International Academy, Research, and Industry Association (IARIA)

A Consistent View of the Smart Grid: Bridging the Gap between IEC CIM and IEC 61850
Schumilin, A.; Duepmeier, C.; Stucky, K.-U.; Hagenmeyer, V.
2018. 44th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), Praha, CZ, August 29–31, 2018, 321–325, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/SEAA.2018.00059

A new classification of attacks against the cyber-physical security of smart grids
Elbez, G.; Keller, H. B.; Hagenmeyer, V.
2018. ARES 2018: International Conference on Availability, Reliability and Security, August 27–30, 2018, Hamburg, Germany., Art.-Nr. 63, Association for Computing Machinery (ACM). doi:10.1145/3230833.3234689

Flow-based analysis of storage usage in a low-carbon european electricity scenario
Tranberg, B.; Schafer, M.; Brown, T.; Horsch, J.; Greiner, M.
2018. 15th International Conference on the European Energy Market, EEM 2018; Lodz; Poland; 27 June 2018 through 29 June 2018, Art. Nr.: 8469951, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM.2018.8469951

Efficient Coupling Interfaces in Photonic Systems Enabled by Printed Freeform Micro-Optics
Koos, C.; Freude, W.; Randel, S.; Dietrich, P.-I.; Blaicher, M.; Xu, Y.; Billah, M. R.; Hoose, T.; Trappen, M.; Hofmann, A.
2018. 20th International Conference on Transparent Optical Networks, ICTON 2018; Bucharest; Romania; 1 July 2018 through 5 July 2018, Art. Nr.: 8473851, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICTON.2018.8473851

Best Practices in Deep Learning-Based Segmentation of Microscopy Images
Scherr, T.; Bartschat, A.; Reischl, M.; Stegmaier, J.; Mikut, R.
2018. Proceedings - 28. Workshop Computational Intelligence, Dortmund, 29. - 30. November 2018. Ed.: F. Hoffmann, 175–195, KIT Scientific Publishing. doi:10.5445/IR/1000087734

Robustness of Deep Learning Architectures with Respect to Training Data Variation
Bartschat, A.; Unger, T.; Scherr, T.; Stegmaier, J.; Mikut, R.; Reischl, M.
2018. Proceedings - 28. Workshop Computational Intelligence, Dortmund, 29. - 30. November 2018. Ed.: F. Hoffmann, 129–138, KIT Scientific Publishing. doi:10.5445/IR/1000087724

The Price of Uncertainty: Chance-Constrained OPF vs. in-Hindsight OPF
Mühlpfordt, T.; Hagenmeyer, V.; Faulwasser, T.
2018. 2018 Power Systems Computation Conference (PSCC), Dublin, IRL, June 11-15, 2018, 1–7, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/PSCC.2018.8442162

On the creation of quantile regression based scenario and parametric probabilistic forecasts in the context of energy forecasting
González Ordiano, J. Á.; Remo Appino, R.; Faulwasser, T.; Hagenmeyer, V.; Mikut, R.
2018. International Symposium on Forecasting (ISF 2018), Boulder, CO, June 16-20, 2018. Conference Proceedings

Effect of process parameters on dimensional accuracy of down-facing surfaces in selective laser melting of TI6AL4V
Charles, A. P.; Elkaseer, A.; Mueller, T.; Thijs, L.; Hagenmeyer, V.; Scholz, S.
2018. Advancing Precision in Additive Manufacturing : 2018 ASPE and euspen Summer Topical Meeting, Berkeley, CA, Jube 22-25, 2018, ASPE

Precision additive metal manufacturing
Witvrouw, A.; Metelkova, J.; Ranjan, R.; Bayat, M.; De Baere, D.; Moshiri, M.; Tosello, G.; Solheid, J.; Charles, A. P.; Scholz, S.; Baier, M.; Carmignato, S.; Stavroulakis, P.; Shaheen, A.; Thijs, L.
2018. Advancing Precision in Additive Manufacturing : 2018 ASPE and euspen Summer Topical Meeting, Berkeley, CA, Jube 22-25, 2018, 18–23, ASPE

Storage scheduling with stochastic uncertainties: Feasibility and cost of imbalances
Appino, R. R.; Ordiano, J. A. G.; Mikut, R.; Hagenmeyer, V.; Faulwasser, T.
2018. 20th Power Systems Computation Conference, PSCC 2018; University College DublinDublin; Ireland; 11 June 2018 through 15 June 2018, Art. Nr.: 8442529, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/PSCC.2018.8442529

A Study of the Factors Influencing Generated Surface Roughness of Downfacing Surfaces in Selective Laser Melting
Charles, A. P.; Elkaseer, A.; Müller, T.; Thijs, L.; Torge, M.; Hagenmeyer, V.; Scholz, S.
2018. World Congress on Micro and Nano Manufacturing, Portoroz, SLO, September 18-20, 2018, 327–330, Research Publishing. doi:10.3850/978-981-11-2728-1_57

Smart modular reconfigurable fully-digital manufacturing system with a knowledge-based framework: example of a fabrication of microfluidic chips
Scholz, S.; Elkaseer, A.; Müller, T.; Gengenbach, U.; Hagenmeyer, V.
2018. Proceedings of the 14th IEEE International Conference on Automation Science and Engineering (CASE), München, August 20-24, 2018, 1012–1017, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/COASE.2018.8560405

Auction Design to Use Flexibility Potentials in the Energy - Intensive Industry
Ludwig, N.; Mikut, R.; Hagenmeyer, V.
2018. 15th International Conference on the European Energy Market (EEM), Lodz, Poland, 27–29 June 2018, 1–5, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/EEM.2018.8470003

A Generic and Highly Scalable Framework for the Automation and Execution of Scientific Data Processing and Simulation Workflows
Liu, J.; Braun, E.; Dupmeier, C.; Kuckertz, P.; Ryberg, D. S.; Robinius, M.; Stolten, D.; Hagenmeyer, V.
2018. 2018 IEEE International Conference on Software Architecture (ICSA), Seattle, WA, April 30 - May 4, 2018, 145–155, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ICSA.2018.00024

Distributed Stochastic AC Optimal Power Flow based on Polynomial Chaos Expansion
Engelmann, A.; Mühlpfordt, T.; Jiang, Y.; Houska, B.; Faulwasser, T.
2018. 2018 Annual American Control Conference (ACC), Milwaukee, WI, USA, 27-29 June 2018, 6188–6193, Institute of Electrical and Electronics Engineers (IEEE). doi:10.23919/ACC.2018.8431090

Engineering Smart Market Platforms for Market Based Congestion Management
Huber, J.; Köppl, S.; Klempp, N.; Schutz, M.; Heilmann, E.
2018. 9th ACM International Conference on Future Energy Systems (e-Energy), Karlsruhe, Germany, 12 - 15 June 2018, 544–549, Association for Computing Machinery (ACM). doi:10.1145/3208903.3214349

Prüfung von openBIM Gebäudemodellen für die thermische Gebäudesimulation
Geiger, A.; Hagenmeyer, V.
2018. BauSIM2018 - 7. Deutsch-Österreichische IBPSA-Konferenz : Tagungsband. Hrsg.: P. von Both, 578–585, Karlsruher Institut für Technologie (KIT)

Thermal Energy Simulation of Buildings based on the CityGML Energy Application Domain Extension
Geiger, A.; Benner, J.; Häfele, K.-H.; Hagenmeyer, V.
2018. BauSIM2018 - 7. Deutsch-Österreichische IBPSA-Konferenz : Tagungsband. Hrsg.: P. von Both, 295–302, Karlsruher Institut für Technologie (KIT)