Publications at Department of Electrical and Computer Engineering

Under publication list you can find a complete list of the publications that are written by employees at the Publications at Department of Electrical and Computer Engineering for example journal articles, books, reports etc.

The department also publishes technical reports which you can read more about under Technical reports.

Under PhD dissertations you will find the department's published PhD dissertations.

Publication list

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Chumachenko, K., Gabbouj, M. & Iosifidis, A. (2022). Object detection and tracking. In A. Iosifidis & A. Tefas (Eds.), Deep Learning for Robot Perception and Cognition (pp. 243-278). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00016-6

Wagner, S. R. (2021). Nye smarte teknologier er på vej – hvordan får almensektoren det bedste ud af dem? Maanedsskrift for Almen Praksis, 2021(Juni/juli), 470-478. https://www.maanedsskriftet.dk/mpl/2021/344/12755/

Kouvelas, N., Prasad, R. V., Yazdani, N. & Lucani Rötter, D. E. (2021). np-CECADA: Enhancing Ubiquitous Connectivity of LoRa Networks. In Proceedings - 2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems, MASS 2021 (pp. 374-382). IEEE. https://doi.org/10.1109/MASS52906.2021.00054

Vahdanjoo, M. & Grøn Sørensen, C. (2021). Novel Route Planning Method to Improve the Operational Efficiency of Capacitated Operations. Case: Application of Organic Fertilizer. AgriEngineering, 3(3), 458-477. https://doi.org/10.3390/agriengineering3030031

Lotfi, A., Maalandish, M., Aghaei, A. ., Samadian, A., Fathollahidehkordi, A., Hosseini, S. H. & Khooban, M. H. (2022). Novel multilevel inverter topology with low switch count. International Journal of Emerging Electric Power Systems. https://doi.org/10.1515/ijeeps-2022-0309

Kamal, T., Karabacak, M., Perić, V. S., Hassan, S. Z. & Fernández‐Ramírez, L. M. (2020). Novel improved adaptive neuro‐fuzzy control of inverter and supervisory energy management system of a microgrid. Energies, 13(18), Article 4721. https://doi.org/10.3390/en13184721

Noor, M. A., Benhassen, L. L., Kaspersen, A. E., Weiss, M. G., Hasenkam, J. M. & Johansen, P. (2023). Novel Expansible Aortic Annuloplasty Ring Exhibits Similar Characteristics as the Dacron Ring—an In Vitro Evaluation. Journal of Cardiovascular Translational Research, 16(5), 1144-52. https://doi.org/10.1007/s12265-023-10393-7

Nørremark, M., Hansen, M. J., Kai, P., Børsting, C. F., Ottosen, C-O. & Konnerup, D., (2023). Notat vedrørende miljø- og klimateknologier 2023 – del 1, No. 2023-0505187, 21 p., Jun 02, 2023. Rådgivningsnotat fra DCA - Nationalt Center for Fødevarer og Jordbrug

Dormann, F., Frisk, O., Andersen, L. N. & Pedersen, C. F. (2021). Not All Noise Is Accounted Equally: How Differentially Private Learning Benefits From Large Sampling Rates. In 2021 IEEE 31st International Workshop on Machine Learning for Signal Processing, MLSP 2021 IEEE. https://doi.org/10.1109/MLSP52302.2021.9596307

Hemakom, A., Ahrabian, A., Looney, D., Rehman, N. U. & Mandic, D. P. (2015). Nonuniformly sampled trivariate empirical mode decomposition. In 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) IEEE. https://doi.org/10.1109/icassp.2015.7178660

Abrazeh, S., Parvaresh, A., Mohseni, S-R., Jahanshahi Zeitouni, M., Gheisarnejad, M. & Khooban, M. H. (2021). Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines. IEEE/CAA Journal of Automatica Sinica, 8(3), 690-700. Article 9346074. https://doi.org/10.1109/JAS.2021.1003889

Johansen, K. W., Nielsen, R. O., Schultz, C. P. L. & Teizer, J. (2020). Non-monotonic Reasoning For Automated Progress Analysis Of Construction Operations. In N. Dawood , F. Pour Rahimian, S. Seyedzadeh & M. Sheikhkhoshkar (Eds.), Enabling the Development and Implementation of Digital Twins: Proceedings of the 20th International Conference on Construction Applications of Virtual Reality (pp. 292-303) https://www.researchgate.net/profile/Farzad-Pour-Rahimian/publication/344444905_Enabling_the_Development_and_Implementation_of_Digital_Twins_Proceedings_of_the_20th_International_Conference_on_Construction_Applications_of_Virtual_Reality/links/5fb3ec4445851518fdad5eab/Enabling-the-Development-and-Implementation-of-Digital-Twins-Proceedings-of-the-20th-International-Conference-on-Construction-Applications-of-Virtual-Reality.pdf

Guo, P., Peric, V. S. & Yuan, Z. (2022). Nodal Pricing Comparison between DCOPF and ACOPF: Case Studies for the Power Systems in Iceland and Germany. In E. Pashajavid, D. Kim, S. Rajakaruna & A. Abu-Siada (Eds.), Proceedings - 2022 IEEE Sustainable Power and Energy Conference, iSPEC 2022 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/iSPEC54162.2022.10032996

Bozorgasli, Z., Foroozan, H., Gheisarnejad Chirani, M. & Khooban, M. H. (2021). New Trends on Digital Twin-Based Blockchain Technology in Zero-Emission Ship Applications. Naval Engineers Journal, 133(3), 115-135. http://bt.e-ditionsbyfry.com/publication/?m=63540&i=721756&view=articleBrowser&article_id=4109541&ver=html5

Andresen, B., Gomes Guerreiro, G. M., Martin, F. & Yang, G. (2022). New pathways to future grid compliance for wind power plants. 115-121.

Dobbs, A. M., Ginn, D., Skovsen, S. K., Bagavathiannan, M. V., Mirsky, S. B., Reberg-Horton, C. S. & Leon, R. G. (2022). New directions in weed management and research using 3D imaging. Weed Science, 70(6), 641-647. https://doi.org/10.1017/wsc.2022.56

Yildirim, B., Razmi, P., Fathollahidehkordi, A., Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Neuromorphic deep learning frequency regulation in stand-alone microgrids. Applied Soft Computing, 144, Article 110418. https://doi.org/10.1016/j.asoc.2023.110418

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG: Bringing EEG music studies into the concert hall . Poster session presented at Rhythm Production and Perception Workshop 2021, Oslo, Norway.

Bliddal, H., Christensen, C. B., Møller, C., Vuust, P. & Kidmose, P. (2021). Neural correlates of beat perception measured using ear-EEG. Poster session presented at Advances and Perspectives in Auditory Neuroscience, United States.

Marandi, S. A., Sehat, H., Lucani Rötter, D. E., Mousavifar, S. & Jacobsen, R. H. (2021). Network Coding-based Data Storage and Retrieval for Kademlia. In 2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings Article 9448845 IEEE. https://doi.org/10.1109/VTC2021-Spring51267.2021.9448845

Ronchini, M., Rezaeiyan, Y., Zamani, M., Panuccio, G. & Moradi, F. (2022). NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials. ArXiv. https://doi.org/10.48550/arXiv.2210.10565

Ronchini, M., Rezaeiyan, Y., Zamani, M., Panuccio, G. & Moradi, F. (2023). NET-TEN: a silicon neuromorphic network for low-latency detection of seizures in local field potentials. Journal of Neural Engineering, 20(3), Article 036002. https://doi.org/10.1088/1741-2552/acd029

Naveed, K., Mukhtar, S. & Ur Rehman, N. (2021). Multivariate Signal Denoising Based on Generic Multivariate Detrended Fluctuation Analysis. In 2021 IEEE Statistical Signal Processing Workshop, SSP 2021 (pp. 441-445). IEEE. https://doi.org/10.1109/SSP49050.2021.9513823

Ahmed, M. U., Rehman, N., Looney, D., Rutkowski, T. M., Kidmose, P. & Mandic, D. P. (2012). Multivariate entropy analysis with data-driven scales. In 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3901-3904). IEEE. https://doi.org/10.1109/icassp.2012.6288770, https://doi.org/10.1109/ICASSP.2012.6288770

Shi, L., Hernandez Marcano, N. J. & Jacobsen, R. H. (2022). Multi-UAV Path Coordination through Generalized Potential Games. In 2022 8th International Conference on Automation, Robotics and Applications, ICARA 2022 (pp. 125-129). IEEE. https://doi.org/10.1109/ICARA55094.2022.9738578

Naveed, K., Shaukat, B., Ehsan, S., Mcdonald-Maier, K. D., Rehman, N. U. & Baghaie, A. (Ed.) (2019). Multiscale image denoising using goodness-of-fit test based on EDF statistics. PLOS ONE, 14(5), e0216197. https://doi.org/10.1371/journal.pone.0216197

Rehman, N. U., Naveed, K., Ehsan, S. & McDonald-Maier, K. (2016). Multi-scale image denoising based on goodness of fit (GOF) tests. In 2016 24th European Signal Processing Conference (EUSIPCO) IEEE. https://doi.org/10.1109/eusipco.2016.7760508

Gheisarnejad Chirani, M. & Khooban, M. H. (2021). Multi-microgrids with a Frequency Regulation-Based V2G Technology: Systems Analysis, Modeling, and Control. In Design, Control, and Operation of Microgrids in Smart Grids: Power Systems (pp. 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 Fractional, 7(11), 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. Article 9070152. https://doi.org/10.1109/TNNLS.2020.2984831

Shabani, M., Tran, D. T., Magris, M., Kanniainen, J. & Iosifidis, A. (2022). Multi-head Temporal Attention-Augmented Bilinear Network for Financial time series prediction. In 30th European Signal Processing Conference, EUSIPCO 2022 - Proceedings (pp. 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. In 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). https://doi.org/10.3390/automation4030017

Kuldeep, G. & Zhang, Q. (2022). Multi-class privacy-preserving cloud computing based on compressive sensing for IoT. Journal of Information Security and Applications, 66, Article 103139. https://doi.org/10.1016/j.jisa.2022.103139

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. In H. Selvaraj, G. Chmaj & D. Zydek (Eds.), Proceedings of the 27th International Conference on Systems Engineering, ICSEng 2020 (pp. 23-33). Springer. https://doi.org/10.1007/978-3-030-65796-3_3

Shi, L. (2022). Motion Planning for Autonomous Aerial Robots. Aarhus Universitet.

Bjerge, K., Frigaard, C. E. & Karstoft, H. (2022). Motion Informed Object Detection of Small Insects in Time-lapse Camera Recordings. arXiv.org.

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, Article 106698. https://doi.org/10.1016/j.engappai.2023.106698

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

Perić, V. S., Bogodorova, T., Mete, A. N. & Vanfretti, L. (2015). Model order selection for probing-based power system mode estimation. In 2015 IEEE Power and Energy Conference at Illinois, PECI 2015 Article 7064883 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PECI.2015.7064883

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

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, Article 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. In J. Fitzgerald, T. Oda & H. D. Macedo (Eds.), Proceedings of the 18th International Overture Workshop (pp. 20-35) https://arxiv.org/pdf/2101.07261.pdf

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

Böttjer, T., Sandberg, M., Larsen, P. G. & Macedo, H. D. (2021). Modelling an Injection Moulding Machine using the Vienna Development Method. In H. D. Macedo, C. Thule & K. Pierce (Eds.), Proceedings of the 19th International Overture Workshop (pp. 51-65) https://arxiv.org/abs/2110.09371

Shreya, S. & Kaushik, B. K. (2019). Modeling of Voltage-Controlled Spin–Orbit Torque MRAM for Multilevel Switching Application. IEEE Transactions on Electron Devices, 67(1), 90. Article 19312204. https://doi.org/0.1109/TED.2019.2951684

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∗. In 9th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, MSCPES 2021, Held as part of the Cyber-Physical Systems and Internet-of-Things Week, Proceedings Article 3472711 Association for Computing Machinery, Inc. https://doi.org/10.1145/3470481.3472711

Hansen, S. T. & Ölveczky, P. C. (2022). Modeling, Algorithm Synthesis, and Instrumentation for Co-simulation in Maude. In K. Bae (Ed.), Rewriting Logic and Its Applications. WRLA 2022 (pp. 130-150). Springer. https://doi.org/10.1007/978-3-031-12441-9_7

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Technical reports

Department of Electrical and Computer Engineering publishes technical reports covering our research areas.

With the reports, we wish to communicate the newest knowledge and research to society ahead of and during the publication process which can take up to a year.

Read the technical reports by following the link below:

Technical Report Department of Electrical and Computer Engineering

PhD dissertations

At the Department of Electrical and Computer Engineering, PhD dissertations are published via Aarhus University Library's/State and University Library's online E-books platform that is open access. You can find the published dissertations by following the link below.

PhD dissertations at Department of Electrical and Computer Engineering

AU Engineering Profile

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Revised 10.08.2023

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