Publikationer fra instituttet

Under publikationsliste finder du en samlet liste over de publikationer, som er lavet af medarbejdere ved Institut for Elektro- og Computerteknologi.

Publikationsliste

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Feng, H., Gomes, C., Gil Arboleda, S., Mikkelsen, P. H., Tola, D., Larsen, P. G. & Sandberg, M. (2022). Integration Of The Mape-K Loop In Digital Twins. I C. R. Martin, N. Emami, M. J. Blas & R. Rezaee (red.), Proceedings of the 2022 Annual Modeling and Simulation Conference, ANNSIM (s. 102-113). IEEE. https://doi.org/10.23919/ANNSIM55834.2022.9859489

Feng, H., Gomes, C., Sandberg, M., Thule, C., Lausdahl, K. & Larsen, P. G. (2021). Developing a Physical and Digital Twin: An Example Process Model. I Companion Proceedings - 24th International Conference on Model-Driven Engineering Languages and Systems, MODELS-C 2021 (s. 286-295). IEEE. https://doi.org/10.1109/MODELS-C53483.2021.00050

Feng, H., Gomes, C., Sandberg, M., Macedo, H. D. & Larsen, P. G. (2022). Under What Conditions Does a Digital Shadow Track a Periodic Linear Physical System? I A. Cerone, M. Autili, A. Bucaioni, C. Gomes, P. Graziani, M. Palmieri, M. Temperini & G. Venture (red.), Software Engineering and Formal Methods. SEFM 2021 Collocated Workshops - CIFMA, CoSim-CPS, OpenCERT, ASYDE, Revised Selected Papers (s. 143-155). Springer. https://doi.org/10.1007/978-3-031-12429-7_11

Feng, H. (2023). Digital Twin Engineering with an Application to an Incubator. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Fehér, M., Yazdani, N., Hansen, M. T., Vester, F. E. & Lucani Rötter, D. E. (2020). Smart Meter Data Compression using Generalized Deduplication. I 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings: Proceedings Artikel 9322393 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9322393

Fehér, M., Yazdani, N., Aranha, D. F., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2020). Side Channel Security of Smart Meter Data Compression Techniques. I 2020 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2020: Proceedings Artikel 9302931 IEEE. https://doi.org/10.1109/SmartGridComm47815.2020.9302931

Fehér, M., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2021). Exploiting DLMS/COSEM Data Compression To Learn Power Consumption Patterns. I 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids, SmartGridComm 2021 (s. 346-351). IEEE. https://doi.org/10.1109/SmartGridComm51999.2021.9632291

Fehér, M., Lucani Rötter, D. E., Hansen, M. T. & Vester, F. E. (2022). Stream Compression of DLMS Smart Meter Readings. I ICC 2022 - IEEE International Conference on Communications (s. 5517-5522). IEEE. https://doi.org/10.1109/ICC45855.2022.9838758

Fehér, M., Lucani Rötter, D. E. & Chatzigeorgiou, I. (2022). An Adaptive Column Compression Family for Self-Driving Databases. Afhandling præsenteret på Thirteenth International Workshop on Accelerating Analytics and Data Management Systems Using Modern Processor and Storage Architectures, Sydney, New South Wales, Australien. https://arxiv.org/abs/2209.02334

Fehér, M. (2023). On Compression for the Complete IoT Data Lifecycle: From Collection to Analytics. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Faurskov, T. S. S., Skov, L. N., Grinderslev, J. B., Kristensen, L. R., Bendtsen, J. M. H., Dahl, M. K., Kessler, T., Andersen, B. P., Kantor, I., Jørgensen, M. R. V., Ravnsbæk, D. B. & Jensen, T. R. (2026). Sample environment for operando solid-state battery characterization. Journal of Applied Crystallography, 59(2), 513-523. https://doi.org/10.1107/S1600576726000853

Faurby, C. F. D., Wang, Y., Paesani, S., Ruf, F., Volet, N., Heck, M., Wieck, A. D., Ludwig, A., Midolo, L. & Lodahl, P. (2023). Quantum-Dot Single-Photon Sources Processed on Silicon-Nitride Integrated Circuits. Afhandling præsenteret på Conference on Laser and Electro-Optics (CLEO) , San Jose, California, USA.

Fathollahidehkordi, A., Derakhshandeh, S. Y., Ghiasian, A. & Khooban, M. H. (2022). Utilization of dynamic wireless power transfer technology in multi-depot, multi-product delivery supply chain. Sustainable Energy, Grids and Networks, 32, Artikel 100836. https://doi.org/10.1016/j.segan.2022.100836

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Homayounzadeh, M. & Khooban, M. H. (2023). Optimal Design of Wireless Charging Electric Buses-Based Machine Learning: A Case Study of Nguyen-Dupuis Network. I E E E Transactions on Vehicular Technology, 72(7), 8449-8458. https://doi.org/10.1109/TVT.2023.3247838

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Andresen, B., Farsizadeh, H. & Khooban, M. H. (2023). Robust Artificial intelligence Controller for Stabilization of Full-Bridge Converters Feeding Constant Power Loads. IEEE Transactions on Circuits and Systems II: Express Briefs, 70(9), 3504-3508. https://doi.org/10.1109/TCSII.2023.3270751

Fathollahidehkordi, A., Gheisarnejad Chirani, M., Boudjadar, J., Derakhshandeh, S. Y. & Khooban, M. H. (2023). Multi-Criteria Design of Electric Transit Bus Based on Wireless Charging Infrastructure: A Case Study of Real Road Map in Wakefield. Automation , 4(3), 291-308. https://doi.org/10.3390/automation4030017

Fathollahidehkordi, A. & Andresen, B. (2023). Multi-Machine Power System Transient Stability Enhancement Utilizing a Fractional Order-Based Nonlinear Stabilizer. Fractal and Fractional, 7(11), 808. Artikel 808. https://doi.org/10.3390/fractalfract7110808

Fathollahi, A. & Andresen, B. (2024). Deep deterministic policy gradient for adaptive power system stabilization and voltage regulation. e-Prime - Advances in Electrical Engineering, Electronics and Energy, 9, Artikel 100675. https://doi.org/10.1016/j.prime.2024.100675

Fathollahi, A. & Andresen, B. (2024). Adaptive Fixed-Time Control strategy of Generator Excitation and Thyristor-Controlled Series Capacitor in Multi-Machine Energy Systems. IEEE Access, 12, 100316-100327. https://doi.org/10.1109/ACCESS.2024.3430199

Fathollahi, A. & Andresen, B. (2024). Enhancing Transient Stability in Multi-Machine Power Systems through a Model-Free Fractional-Order Excitation Stabilizer. Fractal and Fractional, 8(7), Artikel 419. https://doi.org/10.3390/fractalfract8070419

Fathollahi, A. (2024). Intelligent Control Framework for Improving Energy System Stability Through Deep Learning-Based Modal Optimization Scheme. Sustainability (Switzerland), 16(21), Artikel 9392. https://doi.org/10.3390/su16219392

Fathollahi, A. & Andresen, B. (2025). Power Quality Analysis and Improvement of Power-to-X Plants Using Digital Twins: A Practical Application in Denmark. IEEE Transactions on Energy Conversion, 40(3), 1909-1921. https://doi.org/10.1109/TEC.2025.3531113

Fathollahi, A. (2025). Machine Learning and Artificial Intelligence Techniques in Smart Grids Stability Analysis: A Review. Energies, 18(13), Artikel 3431. https://doi.org/10.3390/en18133431

Fathollahi, A., Nielsen, T. W., Andresen, B. & Dannesboe, C. (2025). Designing an IGBT-Based Active Front-End Rectifier with Voltage Oriented-based Control for Power-to-Hydrogen Electrolyzers. I Proceedings - 2025 IEEE 7th Global Power, Energy and Communication Conference, GPECOM 2025 (s. 69-74). IEEE. https://doi.org/10.1109/GPECOM65896.2025.11061927

Fathollahi, A., Gheisarnejad, M., Sharifzadeh, M., Laurendeau, E., Andresen, B. & Al-Haddad, K. (2026). On-Policy Machine Learning Based-Disturbance Rejection Control for Grid-Tied PEC9 Inverter Under Parameters Mismatch and Distorted Grid Voltage. IEEE Transactions on Emerging Topics in Computational Intelligence, 10(1), 1025-1037. https://doi.org/10.1109/TETCI.2025.3619574

Fathollahi, A., Sharifzadeh, M., Oshnoei, S., Gheisarnejad, M., Laurendeau, E. & Al-Haddad, K. (2025). Adaptive Fault-Tolerant Data-Driven Control of Multilevel PEC Inverter via Soft Reinforcement Learning Under Switching-Level Transition. I 2025 IEEE Energy Conversion Conference Congress and Exposition, ECCE 2025 IEEE. https://doi.org/10.1109/ECCE58356.2025.11259828

Farooq, W., Islam, S. U., Khan, M. A., Rehman, S., Gulzari, U. A. & Boudjadar, J. (2022). UGAVs-MDVR: A Cluster-Based Multicast Routing Protocol for Unmanned Ground and Aerial Vehicles Communication in VANET. Applied Sciences, 12(23), Artikel 11995. https://doi.org/10.3390/app122311995

Farkhani, S., Skovsen, S. K., Dyrmann, M., Nyholm Jørgensen, R. & Karstoft, H. (2021). Weed classification using explainable multi-resolution slot attention. Sensors, 21(20), Artikel 6705. https://doi.org/10.3390/s21206705

Farkhani, S. (2022). Soft Regression based on Sparse Unbalanced Labels. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Fares, H., Ronchini, M., Zamani, M., Farkhani, H. & Moradi, F. (2022). In the realm of hybrid Brain: Human Brain and AI. ArXiv. https://doi.org/10.48550/arXiv.2210.01461

Far Brusatori, M. & Volet, N. (2022). External optical feedback engineered to reduce and stabilize the linewidth of diode lasers. I V. S. Ilchenko, A. M. Armani & J. V. Sheldakova (red.), Laser Resonators, Microresonators, and Beam Control XXIV Artikel 119870D SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2609616

Far Brusatori, M., Klein, H. & Volet, N. (2023). Achieving High Stability of Dual-Wavelength U-Shaped Laser in the C-Band Using Optical Feedback. IEEE Photonics Technology Letters, 35(10), 573-576. https://doi.org/10.1109/lpt.2023.3264160

Far Brusatori, M., Klein, H. & Volet, N. (2022). Dual-wavelength laser in the C-band with narrow-linewidth reduced by optical feedback. Abstract fra IEEE Photonics Conference 2022. https://doi.org/10.1109/IPC53466.2022.9975567

Far Brusatori, M. (2023). Engineering Optical Feedback for Stable Diode Laser Performance. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.

Faraji, B., Gheisarnejad, M., Rouhollahi, K., Esfahani, Z. & Khooban, M. H. (2021). Machine Learning Approach based on Ultra-Local Model Control for Treating Cancer Pain. I E E E Sensors Journal, 21(6), 8245-8252. Artikel 9285309. https://doi.org/10.1109/JSEN.2020.3042937

Faraji, B., Gheisarnejad, M., Yalsavar, M. & Khooban, M. H. (2021). An Adaptive ADRC Control for Parkinson’s Patients Using Machine Learning. IEEE Sensors Journal, 21(6), 8670 - 8678. Artikel 9311650. https://doi.org/10.1109/JSEN.2020.3048588

Faraji, B., Gheisarnejad, M., Esfahani, Z. & Khooban, M. H. (2022). Smart Sensor Control for Rehabilitation in Parkinson's Patients. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(2), 267-275. https://doi.org/10.1109/TETCI.2020.3045483

Faraji, B., Paghaleh, S. M., Gheisarnejad, M., Khooban, M. H. & Senior Member, IEEE (2024). Simultaneous control of rigidity and hand tremor by adaptive fuzzy Q-learning. Communications in Nonlinear Science and Numerical Simulation, 130, Artikel 107670. https://doi.org/10.1016/j.cnsns.2023.107670

Fan, W., Haiyang, Y., Zhongda, Z., Xiaobo, Z., Yuzhang, Z. & Haiyan, W. (2025). ESTMST-ST: An End-to-End Soft Threshold and Multiloss Self-Distillation Based Swin Transformer for Underwater Acoustic Signal Recognition. IEEE Transactions on Geoscience and Remote Sensing, 63, Artikel 4200813. https://doi.org/10.1109/TGRS.2024.3520860

Falay, B., Wilfling, S., Alfalouji, Q., Exenberger, J., Schranz, T., Legaard, C. M., Leusbrock, I. & Schweiger, G. (2021). Coupling physical and machine learning models: case study of a single-family house. I Proceedings of 14th Modelica Conference 2021 (s. 335-341) https://doi.org/10.3384/ecp21181335

Evans, V. T., Gomes, C. & Lucani Rötter, D. E. (2025). Precision on Demand: Propositional Logic for Event-Trigger Threshold Regulation. IEEE Internet of Things Journal, 12(3), 2674-2689. https://doi.org/10.1109/JIOT.2024.3476922

Evans, V. T., Gomes, C. & Lucani Rötter, D. E. (2026). When Every Transmission Counts: Event-Trigger Threshold Regulation for STL Properties. IEEE Internet of Things Journal, 13(4), 7040-7051. https://doi.org/10.1109/JIOT.2025.3637893

Esterle, L., Gomes, C., Frasheri, M., Ejersbo, H., Tomforde, S. & Larsen, P. G. (2021). Digital twins for collaboration and self-integration. I E. El-Araby, V. Kalogeraki, D. Pianini, F. Lassabe, B. Porter, S. Ghahremani, I. Nunes, M. Bakhouya & S. Tomforde (red.), Proceedings - 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2021 (s. 172-177). IEEE. https://doi.org/10.1109/ACSOS-C52956.2021.00040

Esterle, L. (2022). Deep learning in multiagent systems. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 435-460). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00022-1

Esterle, L. & King, D. W. (2021). Loosening Control—A Hybrid Approach to Controlling Heterogeneous Swarms. ACM Transactions on Autonomous and Adaptive Systems, 16(2), Artikel 5. https://doi.org/10.1145/3502725

Esterle, L., Ejersbo, H., Frasheri, M., Gomes, C., Macedo, H. D. & Larsen, P. G. (2022). Digital Twins for Autonomous Intelligent Systems: From Development to Deployment. I Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022 (s. 53-54). IEEE. https://doi.org/10.1109/ACSOSC56246.2022.00028

Esterle, L., Montagna, S., Pianini, D., Aguzzi, G., Bellman, K. L., Ciatto, G., Contoli, C., Donati, M., Mariani, S., Rahmani, A., Savaglio, C., Storti, E., TaheriNejad, N., van der Sluis, O. & Wang, Z. (2024). MADTECC 2024: 1st Workshop on Medical Applications with Digital Twins and Edge-cloud Continuum - Welcome and Committees. I 2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (s. 30-31). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10502899

Esterle, L., Frasheri, M. & Larsen, P. G. (2024). Autonomous Reconfiguration Enabled by Digital Twins. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 345-362). Springer. https://doi.org/10.1007/978-3-031-66719-0_14

Esterle, L. (2022). Collaborative Systems: Learning and Working Together. CEUR Workshop Proceedings, 3461.

Esterle, L., Porter, B. & Woodcock, J. (2021). Verification and Uncertainties in Self-integrating System. I 2021 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion (ACSOS-C) (s. 220-225) https://doi.org/10.1109/ACSOS-C52956.2021.00050

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