Institut for Elektro- og Computerteknologi

Aarhus Universitets segl

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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Dahl, M. K., Hassan Hire, J., Zamani, M. & Moradi, F. (2024). Multimodal Temperature Sensing Using Electromechanical Impedance (EMI) for Structural Health Monitoring. IEEE Sensors Journal, 24(3), 3457-3464. https://doi.org/10.1109/JSEN.2023.3343779
Gheisarnejad Chirani, M. & Khooban, M. H. (2021). Multi-microgrids with a Frequency Regulation-Based V2G Technology: Systems Analysis, Modeling, and Control. I Design, Control, and Operation of Microgrids in Smart Grids: Power Systems (s. 1-26). Springer. https://doi.org/10.1007/978-3-030-64631-8_1
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
Tran, D. T., Yamac, M., Degerli, A., Gabbouj, M. & Iosifidis, A. (2021). Multilinear compressive learning. IEEE Transactions on Neural Networks and Learning Systems, 32(4), 1512-1524. Artikel 9070152. https://doi.org/10.1109/TNNLS.2020.2984831
Guven, Z. A., Mendes, E. & Baker, S. (2026). Multi-label text classification using prompting techniques via LLMs in Software Effort Estimation. IEEE Access, 14, 52753-52775. https://doi.org/10.1109/ACCESS.2026.3679475
Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. I 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (s. 1487-1491). IEEE. https://doi.org/10.23919/EUSIPCO55093.2022.9909957
Bakhtiarnia, A., Zhang, Q. & Iosifidis, A. (2021). Multi-Exit Vision Transformer for Dynamic Inference. I The 32nd British Machine Vision Conference https://www.semanticscholar.org/paper/Multi-Exit-Vision-Transformer-for-Dynamic-Inference-Bakhtiarnia-Zhang/26f61039857423c0aad2c44f0e7769cbb61246c9
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
Lechuga, M. M. L., Nørremark, M., Jorguseski, L., D'Acunto, L., Politis, C. & Palattella, M. R. (2023). Multi-Connectivity for Livestock Transport in Rural Areas. Afhandling præsenteret på 2023 Joint EuCNC & 6G Summit, Gothenburg, Sverige.
Kuldeep, G. & Zhang, Q. (2022). Multi-class privacy-preserving cloud computing based on compressive sensing for IoT. Journal of Information Security and Applications, 66, Artikel 103139. https://doi.org/10.1016/j.jisa.2022.103139
Sejersen, J. L. F., Sarabakha, A., Plagborg Bak Sørensen, K. & Høigaard Jensen, J. (2025). Multi-Agent Path Planning in Complex Environments using Gaussian Belief Propagation with Global Path Finding. 4359-4365. Afhandling præsenteret på 2025 IEEE International Conference on Robotics and Automation (ICRA) , Atlanta, Georgia, USA. https://doi.org/10.1109/ICRA55743.2025.11128006
Yildirim, B., Gheisarnejad Chirani, M., Temel Özdemir, M. T. Ö. & Khooban, M. H. (2024). Multi-agent fuzzy Q-learning-based PEM fuel cell air-feed system control. International Journal of Hydrogen Energy, 75, 354-362. https://doi.org/10.1016/j.ijhydene.2024.02.129
Nørremark, M., (2024). Muligheder for miljøeffektberegning af teknologier for pesticidreduktion i relation til økologisk jordbrug, Nr. 2024-0751020, 4 s., nov. 29, 2024. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug
Nørremark, M. (2024). Muligheder for mere sikker håndtering af kvæg ved teknologisk innovation. DCA - Nationalt Center for Fødevarer og Jordbrug.
Zhao, X. & Lucani Rötter, D. E. (Accepteret/In press). MUFFLe: Efficient Model Update Compression via Generalized Deduplication for Federated Learning. I IEEE International Conference on Edge Computing and Communications (EDGE) IEEE.
Kazemi, Z., Rask, J. K., Gomes, C., Yildiz, E. & Larsen, P. G. (2023). Movable factory—A systematic literature review of concepts, requirements, applications, and gaps. Journal of Manufacturing Systems, 69, 189-207. https://doi.org/10.1016/j.jmsy.2023.06.008
Sadiq, M. T., Yu, X., Yuan, Z., Aziz, M. Z., Rehman, N. U., Ding, W. & Xiao, G. (2022). Motor Imagery BCI Classification Based on Multivariate Variational Mode Decomposition. IEEE Transactions on Emerging Topics in Computational Intelligence, 6(5), 1177-1189. https://doi.org/10.1109/tetci.2022.3147030
Iraji, M., Dehghani, M., Mohammadi, M., Vafamand, N. & Boudjadar, J. (2021). Motor Current Signature Analysis Using Shapelet. I H. Selvaraj, G. Chmaj & D. Zydek (red.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (s. 23-33). Springer. https://doi.org/10.1007/978-3-030-65796-3_3
Shi, L. (2022). Motion Planning for Autonomous Aerial Robots. [Ph.d.-afhandling, Aarhus Universitet]. Aarhus Universitet.
Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arxiv.org. https://arxiv.org/abs/2212.00423
Wang, Z., Chen, L., Chen, H. & Rehman, N. U. (2023). Monthly ship price forecasting based on multivariate variational mode decomposition. Engineering Applications of Artificial Intelligence, 125, Artikel 106698. https://doi.org/10.1016/j.engappai.2023.106698
Alvarez Tunon, O., Brodskiy, Y. & Kayacan, E. (2024). Monocular visual simultaneous localization and mapping:(r) evolution from geometry to deep learning-based pipelines. IEEE Transactions on Artificial Intelligence, 5(5), 1990-2010. Artikel 3321032. https://doi.org/10.1109/TAI.2023.3321032
Hansen, S. T., Kamburjan, E. & Kazemi, Z. (2025). Monitoring Reconfigurable Simulation Scenarios in Co-simulated Digital Twins. I T. Margaria & B. Steffen (red.), Leveraging Applications of Formal Methods, Verification and Validation. Specification and Verification - 12th International Symposium, ISoLA 2024, Proceedings (s. 47-61). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-75390-9_4
Gheisarnejad Chirani, M., Mohammadzadeh, A. & Khooban, M. H. (2022). Model Predictive Control-Based Type-3 Fuzzy Estimator for Voltage Stabilization of DC Power Converters. IEEE Transactions on Industrial Electronics, 69(12), 13849-13858. https://doi.org/10.1109/TIE.2021.3134052
Salehi, Z., Karimaghaee, P. & Khooban, M. H. (2021). Model Order Reduction of Positive Real Systems Based on Mixed Gramian Balanced Truncation with Error Bounds. Circuits, Systems and Signal Processing, 40(11), 5309-5327. https://doi.org/10.1007/s00034-021-01734-5
Antonsen, M. M. (2025). Model-Mediated Teleoperation for Tactile Internet. [Ph.d.-afhandling, Aarhus Universitet].
Li, B., Fitzgerald, J. & Schultz, C. (2022). Modelling the impacts of crowds on occupants in the built environment—A static, rule-based approach to human perception and movement. Advanced Engineering Informatics, 51, Artikel 101452. https://doi.org/10.1016/j.aei.2021.101452
Kulik, T., Macedo, H. D., Talasila, P. & Larsen, P. G. (2021). Modelling the HUBCAP Sandbox Architecture In VDM: A Study In Security. I J. Fitzgerald, T. Oda & H. D. Macedo (red.), Proceedings of the 18th International Overture Workshop (s. 20-35) https://arxiv.org/pdf/2101.07261.pdf
Amer, A., Felsager, D., Brodskiy, Y. & Sarabakha, A. (2025). Modelling of Underwater Vehicles using Physics-Informed Neural Networks with Control. I International Joint Conference on Neural Networks, IJCNN 2025 - Proceedings IEEE. https://doi.org/10.1109/IJCNN64981.2025.11228873
Bochtis, D., Sørensen, C. A. G., Jørgensen, R. N. & Green, O. (2009). Modelling of material handling operations using controlled traffic. Biosystems Engineering, 103(4), 397-408. https://doi.org/10.1016/j.biosystemseng.2009.02.006
Abbiati, G., Gomes, C., Sandberg, M., Kazemi, Z., Hansen, S. T. & Larsen, P. G. (2024). Modelling for Digital Twins. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 89-127). Springer. https://doi.org/10.1007/978-3-031-66719-0_5
Böttjer, T., Sandberg, M., Larsen, P. G. & Macedo, H. D. (2021). Modelling an Injection Moulding Machine using the Vienna Development Method. I H. D. Macedo, C. Thule & K. Pierce (red.), Proceedings of the 19th International Overture Workshop (s. 51-65) https://arxiv.org/abs/2110.09371
Fathollahi, A., Dannesboe, C. & Andresen, B. (2026). Modelling and Experimental Investigation of the Power Conversion System for Solid Oxide Water Electrolysis. IET Conference Proceedings, 2025(45), 424-429. https://doi.org/10.1049/icp.2025.4334
Samboju, S. K., Tanjavooru, V. T., Zinsmeister, D. & Peric, V. S. (2021). Modeling of combined heat and power generation unit for dynamic analysis of integrated thermal-electric grids∗. I Proceedings of the 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems Artikel 11 Association for Computing Machinery. https://doi.org/10.1145/3470481.3472711
Hansen, S. T. & Ölveczky, P. C. (2022). Modeling, Algorithm Synthesis, and Instrumentation for Co-simulation in Maude. I K. Bae (red.), Rewriting Logic and Its Applications. WRLA 2022 (s. 130-150). Springer. https://doi.org/10.1007/978-3-031-12441-9_7
Oshnoei, S., Aghamohammadi, M. R. & Khooban, M. H. (2024). Model-Free Predictive Frequency Control Under Sensor and Actuator FDI Attacks. IEEE Transactions on Circuits and Systems II: Express Briefs, 71(4), 2434-2438. https://doi.org/10.1109/TCSII.2023.3339545
Feng, H., Gomes, C., Iosifidis, A. & Larsen, P. G. (2021). Model-based monitoring and state estimation for digital twins: The Kalman filter. I C. R. Martin, M. J. Blas & A. I. Psijas (red.), Annual Modeling and Simulation Conference (ANNSIM 2021) (s. 1-2)
Liu, J. (2020). Mobile Edge Computing in 5G. [Ph.d.-afhandling, Aarhus Universitet].
Banaei, M., Oloomi‐buygi, M., Raouf‐Sheybani, H. & Khooban, M. H. (2021). Mixed supply function‐Cournot equilibrium model of futures and day‐ahead electricity markets. IET Generation, Transmission & Distribution, 15(10), 1640-1654. https://doi.org/10.1049/gtd2.12123
Hageman, K., Feal, A., Gamba, J., Girish, A., Bleier, J., Lindorfer, M., Tapiador, J. & Vallina-Rodriguez, N. (2023). Mixed Signals: Analyzing Software Attribution Challenges in the Android Ecosystem. IEEE Transactions on Software Engineering, 49(4), 2964-2979. https://doi.org/10.1109/TSE.2023.3236582
Rezaeiyan, Y., Zamani, M., Shoaei, O. & Serdijn, W. A. (2018). Mixed-Signal IC With Pulse Width Modulation Wireless Telemetry for Implantable Cardiac Pacemakers in 0.18-μm CMOS. IEEE Transactions on Biomedical Circuits and Systems, 12(3), 589 - 600. https://doi.org/10.1109/TBCAS.2018.2819021
Salehi, Z., Karimaghaee, P. & Khooban, M. H. (2021). Mixed Positive-Bounded Balanced Truncation. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(7), 2488-2492. Artikel 9328872. https://doi.org/10.1109/TCSII.2021.3053160
Aubard, M., Quijano, S., Alvarez Tunon, O., Antal, L. & Brodskiy, Y. (2024). Mission Planning and Safety Assessment for Pipeline Inspection Using Autonomous Underwater Vehicles: A Framework based on Behavior Trees. I OCEANS 2024 - Singapore IEEE. https://doi.org/10.1109/OCEANS51537.2024.10682385
Macedo, H. D. & Touili, T. (2013). Mining Malware Specifications through Static Reachability Analysis.
Nielsen, L., Burihabwa, D., Schiavoni, V., Felber, P. & Lucani Rötter, D. E. (2021). MinervaFS: A User-Space File System for Generalised Deduplication. I International Symposium on Reliable Distributed Systems (SRDS) IEEE. https://doi.org/10.1109/SRDS53918.2021.00033
Alvarez Tunon, O., Kanner, H., Ribeiro Marnet, L., Pham, X. H., Sejersen, J. L. F., Brodskiy, Y. & Kayacan, E. (2023). MIMIR-UW: A Multipurpose Synthetic Dataset for Underwater Navigation and Inspection. I 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (s. 6141-6148). IEEE. https://doi.org/10.1109/IROS55552.2023.10341436
Nørremark, M., Kristensen, E. F., Jensen, M., Ottosen, C.-O., Petridis, A., Mendanha dos Santos, T., Melander, B. & Jensen, P. K. (2024). Miljøpositivliste for producentorganisationers driftsfonde til støtteberettigede teknologier til frugt- og grøntsagssektoren 2024. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug
Konnerup, D., Nørremark, M. & Jensen, M. (2022). Miljøpositivliste for producentorganisationers driftsfonde til støtteberettigede teknologier til frugt- og grøntsagssektoren 2022. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug
Adamsen, A. P. S., Nørremark, M., Hansen, M. J., Kai, P., Børsting, C. F., Brask, M. J., Ottosen, C.-O. & Kristensen, E. F. (2026). Miljø- og Klimateknologi 2026. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug
Nørremark, M., Adamsen, A. P. S., Brask, M. J., Børsting, C. F., Hansen, M. J., Kai, P. & Ottosen, C.-O. (2025). Miljø- og Klimateknologi 2025. DCA - Nationalt Center for Fødevarer og Jordbrug. Rådgivningsrapport fra DCA - Nationalt Center for Fødevarer og Jordbrug

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