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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Benos, L., Grøn Sørensen, C. & Bochtis, D. (2022). Field Deployment of Robotic Systems for Agriculture in Light of Key Safety, Labor, Ethics and Legislation Issues. Current Robotics Reports, 3(2), 49-56. https://doi.org/10.1007/s43154-022-00074-9

Domini, D., Aguzzi, G., Esterle, L. & Viroli, M. (2024). Field-Based Coordination for Federated Learning. I I. Castellani & F. Tiezzi (red.), Coordination Models and Languages - 26th IFIP WG 6.1 International Conference, COORDINATION 2024, Held as Part of the 19th International Federated Conference on Distributed Computing Techniques, DisCoTec 2024, Proceedings (s. 56-74). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-62697-5_4

Bjerge, K., Bodesheim, P. & Karstoft, H. (2024). Few-Shot Learning with Novelty Detection. 340-363. Afhandling præsenteret på DeLTA 2024 - 5th International Conference on Deep Learning Theory and Applications. https://doi.org/10.1007/978-3-031-66694-0_21

Chumachenko, K., Iosifidis, A. & Gabbouj, M. (2022). Feedforward Neural Networks Initialization based on Discriminant Learning. Neural Networks, 146, 220-229. https://doi.org/10.1016/j.neunet.2021.11.020

Ding, Y., Zhang, S., Fan, B., Sun, W., Liao, Y. & Zhou, P. Y. (2024). FedLoCA: Low-Rank Coordinated Adaptation with Knowledge Decoupling for Federated Recommendations. I RecSys '24: Proceedings of the 18th ACM Conference on Recommender Systems (s. 690-700). Association for Computing Machinery. https://doi.org/10.1145/3640457.3688112

Khaleghi, A., Oshnoei, S. & Mirzajani, S. (2025). Federated Learning Detection of Cyberattacks on Virtual Synchronous Machines Under Grid-Forming Control Using Physics-Informed LSTM. Fractal and Fractional, 9(9), Artikel 569. https://doi.org/10.3390/fractalfract9090569

Larsen, P. G., Fitzgerald, J., Woodcock, J., Gamble, C., Payne, R. & Pierce, K. (2018). Features of Integrated Model-Based Co-modelling and Co-simulation Technology. I A. Cerone & M. Roveri (red.), Software Engineering and Formal Methods - SEFM 2017 Collocated Workshops: DataMod, FAACS, MSE, CoSim-CPS, and FOCLASA, Revised Selected Papers (s. 377-390). Springer. https://doi.org/10.1007/978-3-319-74781-1_26

Hardenberg, M., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2024). Feasibility study of steady-state surface NMR with adiabatic pulses. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420051

Jensen, A. L., Kristensen, E. F. & Grøn Sørensen, C. (2022). Feasibility study for organic farming. Poster-session præsenteret på The XX CIGR World Congress 2022, Kyoto, Japan.

Larsen, J. J., Kass, M. A., Grombacher, D. & Griffiths, M. P. (2024). Feasibility of Surface Nuclear Magnetic Resonance With Absurdly Long Excitation Pulses. Geophysical Research Letters, 51(20), Artikel e2024GL110826. https://doi.org/10.1029/2024GL110826

Mohammadnia, A., M. Ziapour, B., Ghaebi, H. & Khooban, M. H. (2021). Feasibility assessment of next-generation drones powering by laser-based wireless power transfer. Optics & Laser Technology, 143, Artikel 107283. https://doi.org/10.1016/j.optlastec.2021.107283

Larsen, P. G., Esterle, L., Fitzgerald, J. & Frasheri, M. (2023). Fault Injection in Co-simulation and Digital Twins for Cyber-Physical Robotic Systems. I Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (s. 222-236). Springer Science+Business Media. https://doi.org/10.1007/978-3-031-40132-9_14

Frasheri, M., Thule, C., Macedo, H. D., Lausdahl, K., Larsen, P. G. & Esterle, L. (2021). Fault Injecting Co-simulations for Safety. 6-13. Afhandling præsenteret på 5th International Conference on System Reliability and Safety, Palermo, Italien. https://doi.org/10.1109/ICSRS53853.2021.9660728

Kjaer-Rasmussen, A., Griffiths, M. P., Grombacher, D. & Larsen, J. J. (2022). Fast removal of powerline harmonic noise from surface NMR datasets using a projection-based approach on graphical processing units. IEEE Geoscience and Remote Sensing Letters, 19, Artikel 8024005. https://doi.org/10.1109/LGRS.2021.3118064

Ruf, F., Faurby, C. F. D., Paesani, S., Wang, Y., Nielsen, L., Midolo, L., Volet, N. & Heck, M. (2022). Fast All-Optical Switches in Si₃N₄ Photonic Integrated Circuits for Single-Photon Routing. Poster-session præsenteret på National Optics Congress, Aarhus, Danmark.

Kopler, I., Marchaim, U., Tikász, I. E., Opaliński, S., Kokin, E., Mallinger, K., Neubauer, T., Gunnarsson, S., Soerensen, C., Phillips, C. J. C. & Banhazi, T. (2023). Farmers’ Perspectives of the Benefits and Risks in Precision Livestock Farming in the EU Pig and Poultry Sectors. Animals, 13(18), Artikel 2868. https://doi.org/10.3390/ani13182868

Woodcock, J. (2025). Farewell Editorial. Formal Aspects of Computing, 37(4), Artikel 26. https://doi.org/10.1145/3773042

Honoré, J. T., Rask, R. D. & Wagner, S. R. (2023). Fall Detection Combining Android Accelerometer and Step Counting Virtual Sensors. I G. A. Papadopoulos, A. Achilleos, E. Pissaloux & R. Velázquez (red.), ICT for Health, Accessibility and Wellbeing - 2nd International Conference, IHAW 2022, Revised Selected Papers (s. 3-16). Springer. https://doi.org/10.1007/978-3-031-29548-5_1

Banhazi, T., Banhazi, A., Tikasz, I. E., Palotay, S., Mallimger, K., Neubauer, T., Corpaci, L., Marchaim, U., Kopler, I., Opalinski, S., Olejnik, K., Kokin, E., Gunnarsson, S., Bjerre, T. & Soerensen, C. (2024). Facilitating PLF Technology Adoption in the Pig and Poultry Industries. Studies in Agricultural Economics, 126(1), 43-49. https://doi.org/10.7896/j.2725

Macedo, H. D., Sassanelli, C., Larsen, P. G. & Terzi, S. (2021). Facilitating model-based design of cyber-manufacturing systems. Procedia CIRP, 104, 1936-1941. https://doi.org/10.1016/j.procir.2021.11.327

Liu, H., Yang, Y., Wu, Q., He, B., Liao, Y. & Zhou, P. (2024). FacGNN: Multi-faceted Fairness Enhancement for GNN through Adversarial and Contrastive Learning. I 2024 International Joint Conference on Neural Networks (IJCNN) IEEE. https://doi.org/10.1109/IJCNN60899.2024.10649939

Merhi, Y. & Agarwala, S. (2022). Fabrication of flexible, and bioresorbable poly-l-lactide acid piezoelectric material with tunable properties. Materials Today: Proceedings, 70, 531-534. https://doi.org/10.1016/j.matpr.2022.09.553

Mørup, C., Kloborg, A. & Lucani Rötter, D. E. (2022). Extreme Bitmapping: Efficiently Sorting Data for Cloud Compression. I 2022 IEEE 11th International Conference on Cloud Networking (CloudNet) (s. 247-251). IEEE. https://doi.org/10.1109/CloudNet55617.2022.9978780

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Extrapolating sparse SNMR data sets onto dense TEM coverage using spatially variable correlations. Abstract fra AGU Fall meeting 2024, Washington DC, USA.

Arent, N. H., Far Brusatori, M. & Volet, N. (2020). Extraction of frequency noise spectral components from delayed self-heterodyne measurements of a laser. Abstract fra European Semiconductor Laser Workshop 2020.

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

Noor, M. A., Benhassen, L. L., Johansen, P. & Hasenkam, J. M. (2022). External aortic annuloplasty ring. Manuskript afsendt til publicering. (Patentnummer PCT/EP2022/071334).

Kulik, T., Talasila, P., Greco, P., Veneziano, G., Marguglio, A., Sutton, L. F., Larsen, P. G. & Macedo, H. D. (2021). Extending the Formal Security Analysis of the HUBCAP sandbox. I H. D. Macedo, C. Thule & K. Pierce (red.), Proceedings of the 19th International Overture Workshop (s. 36-50) https://arxiv.org/abs/2110.09371

Schultz, C. P. L. & Kamari, A. (2025). Exploring the renovation design space: A new iterative approach based on scenario distance metrics and resampling strategies. Building Simulation, 18(6), 1515-1542. https://doi.org/10.1007/s12273-025-1267-1

Bandaru, N., Reddy, C. V., Vallabhudasu, K., Vijayalakshmi, M., Raghava Reddy, K., Cheolho, B., Shim, J. & Aminabhavi, T. M. (2024). Exploring the potential of MXene nanohybrids as high-performance anode materials for lithium-ion batteries. Chemical Engineering Journal, 500, Artikel 157317. https://doi.org/10.1016/j.cej.2024.157317

Morante, M., Frølich, K. & Rehman, N. U. (2025). Exploring functional connectivity at different timescales with multivariate mode decomposition. Frontiers in Neuroscience, 19, Artikel 1653007. https://doi.org/10.3389/fnins.2025.1653007

Akbar, H., Abro, G. E. M., Baloch, S. K., Khan, T. A., Memon, I., Nasir, H. & Memon, S. A. (2026). Exploring carbon nanotube-copper composites for enhanced induction motor design in electrical vehicles. Scientific Reports, 16(1), Artikel 3505. https://doi.org/10.1038/s41598-025-32761-w

Arabsalmani, N., Ghouchani, A., Jafarabadi Ashtiani, S. & Zamani, M. (2025). Exploring Bio-Impedance Sensing for Intelligent Wearable Devices. Bioengineering, 12(5), Artikel 521. https://doi.org/10.3390/bioengineering12050521

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

Kakavandi, F. & Larsen, P. G. (2023). Explainable Product Quality Assessment in a Medical Device Assembly Pilot Line. I 2022 10th International Conference on Control, Mechatronics and Automation (ICCMA) (s. 271-275). IEEE. https://doi.org/10.1109/ICCMA56665.2022.10011621

Chen, G., Kobek-Kjeldager, C., Jensen, L. D., Kristensen, J. K., Kaiser, M., Thodberg, K., Zhang, G., Rong, L., Herskin, M. S. & Foldager, L. (2024). Experimental study on temperature difference between the interior and exterior of the vehicle transporting weaner pigs. Biosystems Engineering, 247, 119-131. https://doi.org/10.1016/j.biosystemseng.2024.09.001

Sepehrzad, R., Ghafourian, J., Hedayatnia, A., Al-Durrad, A. & Khooban, M. H. (2023). Experimental and developed DC microgrid energy management integrated with battery energy storage based on multiple dynamic matrix model predictive control. Journal of Energy Storage, 74(Part A), Artikel 109282. https://doi.org/10.1016/j.est.2023.109282

Oakes, B. J., Gomes, C., Larsen, P. G., Denil, J., Deantoni, J., Cambeiro, J. & Fitzgerald, J. (2023). Examining Model Qualities and Their Impact on Digital Twins. I M. J. Blas & G. Alvarez (red.), 2023 Annual Modeling and Simulation Conference (ANNSIM) (s. 220-232). IEEE. https://ieeexplore.ieee.org/document/10155350

Gheisarnejad, M., Oshnoei, S., Sharifzadeh, M., Laurendeau, E. & Al-Haddad, K. (2025). Event-Triggered Entropy Learning for Encountering of FDI Attack in Grid-Connected Packed E-Cell Inverter. IEEE Transactions on Industrial Electronics, 72(12), 12797-12808. https://doi.org/10.1109/TIE.2025.3581190

Andersen, K. F., Pham, H. X., Ugurlu, H. I. & Kayacan, E. (2022). Event-based Navigation for Autonomous Drone Racing with Sparse Gated Recurrent Network. I 2022 European Control Conference (ECC) (s. 1342-1348). IEEE. https://doi.org/10.23919/ECC55457.2022.9838538

Villa-Henriksen, A., Edwards, G. T. C., Green, O. & Sørensen, C. A. G. (2021). Evaluation of grain quality-based simulated selective harvest performed by an autonomous agricultural robot. Agronomy, 11(9), Artikel 1728. https://doi.org/10.3390/agronomy11091728

Lebiecka-Johansen, P., Cabrera, A. F., Strøm, J., Mikkelsen, K., Elsborg Madsen, R., Dyhr Thomsen, M., Hansen, M., Engelhard Christensen, J., Hemmsen, M. & Kidmose, P. (2024). Evaluation of Ear-EEG based Automatic Sleep Staging Performance. Journal of Sleep Research, 33(S1), Artikel e14291. https://doi.org/10.1111/jsr.14291

Noor, M. A., Skov, S. N. & Johansen, P. (2020). Evaluating Strain Measurements on the Mitral Valve Leaflets using an Optical Image System. Structural heart : the journal of the Heart Team, 4, 72. https://doi.org/10.1080/24748706.2020.1715165

Merhi, Y., Lozano Montero, K., Johansen, P., Mantysalo, M. & Agarwala, S. (2025). Evaluating Piezoelectric Performance of Biodegradable PLLA Film and Its Application for Aortic Annuloplasty. https://chemrxiv.org/engage/chemrxiv/article-details/677788f9fa469535b99d3829

Frasheri, M., Struhar, V., Papadopoulos, A. V. & Causevic, A. (2022). Ethics of Autonomous Collective Decision-Making: The Caesar Framework. Science and Engineering Ethics, 28(6), Artikel 61. https://doi.org/10.1007/s11948-022-00414-0

Strandberg, P. E., Frasheri, M. & Enoiu, E. P. (2021). Ethical AI-Powered Regression Test Selection. I 2021 IEEE International Conference on Artificial Intelligence Testing (AITest) (s. 83-84). IEEE. https://doi.org/10.1109/AITEST52744.2021.00025

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

Amariei, G., Schaarup-Kjær, A. S., Klarskov, P., Henriksen, M. L. & Hinge, M. (2023). Estimation of pigment concentration in LDPE via in-line hyperspectral imaging and machine learning. Journal of Spectral Imaging, 12(a2). https://doi.org/10.1255/jsi.2023.a2

Lakshminarayanan, S., Duecker, D., Sarabakha, A., Ganguly, A., Takayama, L. & Haddadin, S. (2024). Estimation of External Force acting on Underwater Robots. I 2024 IEEE 20th International Conference on Automation Science and Engineering, CASE 2024 (s. 3125-3131). IEEE. https://doi.org/10.1109/CASE59546.2024.10711608

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2024). Estimating Fuel Consumption of an Agricultural Robot by Applying Machine Learning Techniques during Seeding Operation. AgriEngineering, 6(1), 754-772. https://doi.org/10.3390/agriengineering6010043

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