Publikationer fra instituttet

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

Instituttet udgiver også tekniske rapporter, som du kan læse mere om under Tekniske rapporter.

Under ph.d.-afhandlinger finder du instituttets publicerede ph.d.-afhandlinger.

Publikationsliste

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Magris, M. & Iosifidis, A. (2021). Approximate Bayes factors for unit root testing. Afhandling præsenteret på International Association for Applied Econometrics Annual Conference 2021, Rotterdam, Holland. https://www.researchgate.net/publication/349492007_Approximate_Bayes_factors_for_unit_root_testing

Magris, M. & Iosifidis, A. (2023). Bayesian learning for neural networks: an algorithmic survey. Artificial Intelligence Review, 56(10), 11773-11823. https://doi.org/10.1007/s10462-023-10443-1

Magris, M. & Iosifidis, A. (2023). Variational Inference for GARCH-family Models. I ICAIF 2023 - 4th ACM International Conference on AI in Finance (s. 541-548). Association for Computing Machinery, Inc.. https://doi.org/10.1145/3604237.3626863

Magris, M., Shabani, M. & Iosifidis, A. (2024). Manifold Gaussian Variational Bayes on the Precision Matrix. Neural Computation, 36(9), 1744-1798. https://doi.org/10.1162/neco_a_01686

Madsen, E., Tola, D., Hansen, C., Gomes, C. & Larsen, P. G. (2022). AURT: A Tool for Dynamics Calibration of Robot Manipulators. I 2022 IEEE/SICE International Symposium on System Integration, SII 2022 (s. 190-195). IEEE. https://doi.org/10.1109/SII52469.2022.9708769

Madsen, M. L., Ulsig, E. Z., Folsach, S., Godoy, P. H., Stanton, E. J. & Volet, N. (2023). Mid-infrared difference-frequency generation in AlGaAs-on-insulator waveguides. Journal of the Optical Society of America B: Optical Physics, 40(7), 1742-1748. https://doi.org/10.1364/JOSAB.488065

Macedo, H. D. (2021). Digital Twins. 12-15. Afhandling præsenteret på Digitale tvillinger i afløbs- og spildevandsbranchen . http://www.evanet.dk/wp-content/uploads/2021/09/2021_03_EVA_blad.pdf

Macedo, H. D., Thule, C. & Pierce, K. (2021). Proceedings of the 19th International Overture Workshop. https://arxiv.org/abs/2110.09371

Macedo, H. D., Højberg, J., Jensen, J. & Thomsen, U. (2022). Data-Driven Extraneous Water Quantification. Abstract fra 12th Urban Drainage Modeling Conference. https://udm2022.org/2021/11/09/data-driven-extraneous-water-quantification/

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

Macedo, H. D. & Pierce, K. (red.) (2022). Proceedings of the 20th International Overture Workshop. https://doi.org/10.48550/arXiv.2208.10233

Macedo, H. D. & Touili, T. (2013). Mining Malware Specifications through Static Reachability Analysis.

Macedo, H. D. & Oliveira, J. N. (2013). Typing linear algebra: A biproduct-oriented approach.

Macedo, H. D. & Pierce, K. (2023). Proceedings of the 21st International Overture Workshop. http://arxiv.org/pdf/2311.07120v2

Maalandish, M., Babaeian, E., Abolhasani, P., Gheisarnejad Chirani, M. & Khooban, M. H. (2023). Ultra high step-up soft-switching DC/DC converter using coupled inductor and interleaved technique. IET Power Electronics, 16(8), 1320-1338. https://doi.org/10.1049/pel2.12472

Maalandish, M., Hosseini, S. H., Sabahi, M., Rostami, N. & Khooban, M. H. (2023). B-MIMO high step-up DC/DC converter with high capability to control inputs. IET Power Electronics, 16(9), 1499-1513. https://doi.org/10.1049/pel2.12486

Maalandish, M., Hosseini, S. H., Sabahi, M., Rostami, N. & Khooban, M. H. (2023). High step-up multi input–multi output DC–DC converter with high controllability for battery charger/EV applications. IET Power Electronics, 16(15), 2606-2623. https://doi.org/10.1049/pel2.12587

Maalandish, M., Hosseini, S. H., Sabahi, M., Rostami, N. & Khooban, M. H. (2024). Soft-switching multiport DC-DC converter for PV/EV applications with a bidirectional port. IET Renewable Power Generation, 18(12), 1862-1879. https://doi.org/10.1049/rpg2.13055

Ma, C., Rutz, D., Hofmeier, V., Janssen, R., Balafoutis, A., Vaiopoulos, K., Vandorou, F., Sørensen, C. A. G., Manolakos, D., Koutsouris, A., Paris, B., Papadakis, G., Borzecka, M., Wydra, M., Biševac, V., Creupelandt, D., Román, J., Rossi, D., Próchniak, M. ... Asín, M. (2022). Support for Decarbonizing the European Agriculture - The Agrofossilfree Project. I European Biomass Conference and Exhibition Proceedings (EUBCE 2022) (s. 402-405). ETA-Florence Renewable Energies. http://www.etaflorence.it/proceedings/

Ma, C., Rutz, D., Balafoutis, A., Vaiopoulos, K., Vandorou, F., Kyriakarakos, G., Grøn Sørensen, C., Nørremark, M., Kristensen, E. F., Manolakos, D., Koutsouris, A., Kanaki, V., Paris, B., Papadakis, G., Borzecka, M., Wydra, M., Biševac, V., Vansintjan, D., Román, J. ... Hansen, A. G. (2023). SUPPORTING BIOMASS USAGE AND PRODUCTION TO DECARBONIZE AGRICULTURE INDUSTRY: THE AGROFOSSILFREE PROJECT. I 31st European Biomass Conference and Exhibition: Proceedings (s. 373 - 378)

Lyng, R., Bennedsen, J., Bettaieb, L., Bodsberg, N. R., Edström, K., Guðjónsdóttir, M. S., Roslöf, J., Solbjørg, O. K. & Øien, G. (2023). Editorial. I Proceedings of the 19th International CDIO Conference (s. iv-v). NTNU Norwegian University of Science and Technology.

Lund, J., Jensen, L. B., Macedo, H. D. & Larsen, P. G. (2022). Towards UML and VDM Support in the VS Code Environment. I H. D. Macedo & K. Pierce (red.), Proceedings of the 20th International Overture Workshop (s. 50-65) https://doi.org/10.48550/arXiv.2208.10233

Lund, J., Jensen, L. B., Battle, N., Larsen, P. G. & Macedo, H. D. (2023). Bidirectional UML Visualisation of VDM Models.

Lumer-Klabbers, G., Hausted, J. O., Kvistgaard, J. L., Macedo, H. D., Frasheri, M. & Larsen, P. G. (2021). Towards a digital twin framework for autonomous robots. I W. K. Chan, B. Claycomb, H. Takakura, J.-J. Yang, Y. Teranishi, D. Towey, S. Segura, H. Shahriar, S. Reisman & S. I. Ahamed (red.), 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC) (s. 1254-1259). IEEE. https://doi.org/10.1109/COMPSAC51774.2021.00174

Lotlikar, V. S., Satpute, N. & Gupta, A. (2022). Brain Tumor Detection Using Machine Learning and Deep Learning: A Review. Current Medical Imaging, 18(6), 604-622. https://doi.org/10.2174/1573405617666210923144739

Lotfi, A., Maalandish, M., Aghaei, A., Samadian, A., Fathollahi, A., Hosseini, S. H. & Khooban, M. H. (2024). Novel multilevel inverter topology with low switch count. International Journal of Emerging Electric Power Systems, 25(3), 305-319. https://doi.org/10.1515/ijeeps-2022-0309

Lorenzen, K. P., Heremans, E. R. M., Vos, M. D. & Mikkelsen, K. B. (2024). Personalization of Automatic Sleep Scoring: How Best to Adapt Models to Personal Domains in Wearable EEG. IEEE Journal of Biomedical and Health Informatics, 28(10), 5804-5815. https://doi.org/10.1109/JBHI.2024.3409165

Liu, Z., Liang, J., Zhang, S. & Kayacan, E. (2022). ANN-Based vibration control of an aerial refueling hose system with input nonlinearity and prescribed output constraint. Journal of the Franklin Institute, 359(6), 2627-2645. https://doi.org/10.1016/j.jfranklin.2022.01.006

Liu, L., Grombacher, D., Griffiths, M., Vang, M. & Larsen, J. J. (2023). Signal Processing Steady-State Surface NMR Data. IEEE Transactions on Instrumentation and Measurement, 72, Artikel 6502313. https://doi.org/10.1109/TIM.2023.3264033

Liu, B., Wang, Y., Mofid, O., Mobayen, S. & Khooban, M. H. (2024). Barrier Function-Based Backstepping Fractional-Order Sliding Mode Control for Quad-Rotor Unmanned Aerial Vehicle under External Disturbances. IEEE Transactions on Aerospace and Electronic Systems, 60(1), 716-728. https://doi.org/10.1109/TAES.2023.3328801

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

Lindahl Petersen , K., Ladegaard Jensen, K., Back Nielsen, M., Pas, L.-C., Jensen, N.-P., Nielsen, P. R., Bøjer, O. M., Nyholm Jørgensen, R., Laursen, M. S., Teimouri, N. & Hartmann, B. (2021). Analyse af mulige herbicidbesparelser ved brug af erfaringer og data fra RoboWeedMaPS. Datalogisk Institut. https://datalogisk.dk/wp-content/uploads/2021/03/MST_20rapport_version_2_2002092021.pdf

Lin, P.-C., Abbaszadeh, E., Mobayen, S., Rouhani, S. H., Su, C.-L., Haddad-Zarif, M. & Khooban, M. H. (2024). Soft variable structure fractional sliding-mode control for frequency regulation in renewable shipboard microgrids. Ocean Engineering, 296, Artikel 117065. https://doi.org/10.1016/j.oceaneng.2024.117065

Lillelund, C. M., Pedersen, C. F., Harbo, M. & Fibiger Smed, C. (2021). Vejen til genoptræning går gennem data. Medicoteknik, 8(3), 18-19. https://ipaper.ipapercms.dk/TechMedia/Medicoteknik/2021/3/?page=18

Lillelund, C. M., Jensen, H. B. & Pedersen, C. F. (2022). Cloud K-SVD for Image Denoising. SN Computer Science, 3, Artikel 151. https://doi.org/10.1007/s42979-022-01042-y

Lillelund, C. M., Pannullo, F., Jakobsen, M. O. & Pedersen, C. F. (2023). Predicting Survival Time of Ball Bearings in the Presence of Censoring. I AAAI Symposium on Survival Prediction: Algorithms, Challenges, and Applications (SPACA) AAAI Press.

Lillelund, C. M., Magris, M. & Pedersen, C. F. (2023). Uncertainty Estimation in Deep Bayesian Survival Models. I IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI’23) IEEE. https://doi.org/10.1109/BHI58575.2023.10313466

Li, B., Schultz, C. P. L., Melzner, J., Golovina, O. & Teizer, J. (2020). Safe and Lean Location-based Construction Scheduling. I H. Osumi, H. Furuya & K. Tateyama (red.), Proceedings of the 37th International Symposium on Automation and Robotics in Construction (ISARC 2020): From Demonstration to Practical Use - To New Stage of Construction Robot - (s. 1409-1416). International Association for Automation and Robotics in Construction (IAARC). https://doi.org/10.22260/ISARC2020/0195

Li, B., Schultz, C. P. L., Dimyadi, J. & Amor, R. (2021). Defeasible reasoning for automated building code compliance checking. I V. Semenov & R. J. Scherer (red.), ECPPM 2021 – eWork and eBusiness in Architecture, Engineering and Construction: Proceedings of the 13th European Conference on Product & Process Modelling (ECPPM 2021), 15-17 September 2021, Moscow, Russia (s. 229-236). CRC Press. https://doi.org/10.1201/9781003191476

Li, B., Schultz, C., Teizer, J., Golovina, O. & Melzner, J. (2022). Towards a unifying domain model of construction safety, health and well-being: SafeConDM. Advanced Engineering Informatics, 51, Artikel 101487. https://doi.org/10.1016/j.aei.2021.101487

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

Li, N., Iosifidis, A. & Zhang, Q. (2022). Collaborative edge computing for distributed CNN inference acceleration using receptive field-based segmentation. Computer Networks, 214, Artikel 109150. https://doi.org/10.1016/j.comnet.2022.109150

Li, N., Iosifidis, A. & Zhang, Q. (2022). Receptive Field-based Segmentation for Distributed CNN Inference Acceleration in Collaborative Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 4281-4286). IEEE. https://doi.org/10.1109/ICC45855.2022.9838547

Li, N., Iosifidis, A. & Zhang, Q. (2022). Distributed Deep Learning Inference Acceleration using Seamless Collaboration in Edge Computing. I ICC 2022 - IEEE International Conference on Communications (s. 3667-3672). IEEE. https://doi.org/10.1109/ICC45855.2022.9839083

Li, N., Iosifidis, A. & Zhang, Q. (2022). Graph Reinforcement Learning-based CNN Inference Offloading in Dynamic Edge Computing. I 2022 IEEE Global Communications Conference, GLOBECOM 2022 - Proceedings (s. 982-987). IEEE. https://doi.org/10.1109/GLOBECOM48099.2022.10001067

Li, R., Shreya, S., Ricci, S., Bridarolli, D., Ielmini, D., Farkhani, H. & Moradi, F. (2023). Thermal-Induced Multi-State Memristors for Neuromorphic Engineering. I IEEE International Symposium on Circuits and Systems (ISCAS): Proceedings IEEE. https://doi.org/10.1109/ISCAS46773.2023.10182122

Li, N. (2023). Edge AI for Time-critical Internet-of-things. Aarhus University.

Li, H., Zhang, Q. & Kuldeep, G. (2023). Demo: 3TierView: A Three-tier Privacy-preserving Live Video Surveillance IoT System. I MobiSys '23: Proceedings of the 21st Annual International Conference on Mobile Systems, Applications and Services (s. 594–595). Association for Computing Machinery. https://doi.org/10.1145/3581791.3597289

Li, N., Iosifidis, A. & Zhang, Q. (2023). Attention-Based Feature Compression for CNN Inference Offloading in Edge Computing. I M. Zorzi, M. Tao & W. Saad (red.), ICC 2023 - IEEE International Conference on Communications (s. 967-972). IEEE. https://doi.org/10.1109/ICC45041.2023.10279110

Li, C., Kies, A., Zhou, K., Schlott, M., Sayed, O. E., Bilousova, M. & Stöcker, H. (2024). Optimal Power Flow in a highly renewable power system based on attention neural networks. Applied Energy, 359, Artikel 122779. https://doi.org/10.1016/j.apenergy.2024.122779

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