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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Vathoopan Kannan, M., Talasila, P., Boudjadar, J., Larsen, C., Bicocchi, N., Picone, M. & Melloni, M. (2026). Orchestrating Distributed Simulations for Circular Manufacturing-as-a-Service Ecosystems. I IEEE International Conference on Industrial Technology (ICIT) IEEE. https://doi.org/10.1109/ICIT64854.2026.11491518

Vathoopan Kannan, M., Boudjadar, J. & Ramanujan, D. (Accepteret/In press). Ontologies for architecting circular and sustainable manufacturing-as-a-service systems. Afhandling præsenteret på 12th International Conference on Industrial Engineering and Applications.

Vathoopan, M., Boudjadar, J., Hertwig, M. M. & Lentes, J. (2025). Ontology-Driven Simulations for Quantified Service Discovery in Manufacturing Ecosystems. I D. Maga (red.), 2025 29th International Symposium on Distributed Simulation and Real Time Applications (DS-RT) IEEE. https://doi.org/10.1109/DS-RT68115.2025.11186005

Vassis, S., Todnem, L., Straadt, D., Pedersen, C. F., Noeldeke, B., Resnick, C. M., Glerup, M., Pedersen, T. K., Pauwels, R. & Stoustrup, P. (2025). Improving early detection of temporomandibular joint involvement in juvenile idiopathic arthritis with a clinically interpretable machine learning model. Scientific Reports, 15(1), Artikel 39120. https://doi.org/10.1038/s41598-025-25988-0

Vanommeslaeghe, Y., Gomes, C., Van Acker, B., Denil, J. & De Meulenaere, P. (2025). Adapting parallel DEVS semantics to FMI 3.0 co-simulation using synchronous clocks. Simulation. Advance online publication. https://doi.org/10.1177/00375497251393255

Vang, M., Grombacher, D., Griffiths, M. P., Liu, L. & Larsen, J. J. (2023). Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance - three Danish case studies. Hydrology and Earth System Sciences, 27(16), 3115-3124. https://doi.org/10.5194/hess-27-3115-2023

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). Small coil surface nuclear magnetic resonance in dynamic river systems in New Zealand. I 2nd Conference on Hydrogeophysics 2023, Held at Near Surface Geoscience Conference and Exhibition 2023, NSG 2023 European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202320070

Vang, M., Grombacher, D., Larsen, J. J. & Wilson, S. (2023). SMALL COIL SURFACE NUCLEAR MAGNETIC RESONANCE FOR SHALLOW RESOLUTION OF RIVERS IN NEW ZEALAND. Proceedings of the Symposium on the Application of Geophyics to Engineering and Environmental Problems, SAGEEP, 2023-April.

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.

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Christiansen, A. V. (2024). Clustering on SNMR and TEM parameters over a saline-freshwater interface to resolve hydrogeological layers. I NSG2024, 30th European Meeting of Environmental and Engineering Geophysics (s. 1-5). European Association of Geoscientists and Engineers. https://doi.org/10.3997/2214-4609.202420102

Vang, M. Ø., Grombacher, D., Larsen, J. J. & Wilson, S. (2025). Efficient mapping of complex groundwater systems associated with braided rivers using small coil surface nuclear magnetic resonance. Geophysics, 90(3), 1-12. https://doi.org/10.1190/geo2023-0765.1

Vang, M., Larsen, J. J., Christiansen, A. V. & Grombacher, D. (2025). Alleviating interpretational ambiguity in hydrogeology through clustering-based analysis of transient electromagnetic and surface nuclear magnetic resonance data. Hydrology and Earth System Sciences, 29(20), 5315-5329. https://doi.org/10.5194/hess-29-5315-2025

van der Meer, L., Esterle, L., Cools, M. & Loidl, M. (2026). Cities aren't rocket engines: the maturity of digital twins in human-centred urban planning. International Journal of Digital Earth, 19(1), Artikel 2630452. https://doi.org/10.1080/17538947.2026.2630452

Vahedifar, M. A., Akhtarshenas, A., Rafatpanah, M. M. & Sabbaghian, M. (2025). Shapley-Based Data Valuation with Mutual Information: A Key to Modified K-Nearest Neighbors. I 2025 IEEE 35th International Workshop on Machine Learning for Signal Processing (MLSP) https://doi.org/10.1109/MLSP62443.2025.11204262

Vahedifar, M. A. & Zhang, Q. (2025). Signal Prediction for Loss Mitigation in Tactile Internet: A Leader-Follower Game-Theoretic Approach. I 35th IEEE International Workshop on Machine Learning for Signal Processing: Signal Processing in the Age of Lorge Language Models, MLSP 2025 IEEE Computer Society Press. https://doi.org/10.1109/MLSP62443.2025.11204284

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

Vahdanjoo, M., Nørremark, M. & Grøn Sørensen, C. (2021). A System for Optimizing the Process of Straw Bale Retrieval. Sustainability, 13(14), Artikel 7722. https://doi.org/10.3390/su13147722

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2023). Operational, Economic, and Environmental Assessment of an Agricultural Robot in Seeding and Weeding Operations. AgriEngineering, 5(1), 299–324. Artikel 5. https://doi.org/10.3390/agriengineering5010020

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

Vahdanjoo, M., Gislum, R. & Grøn Sørensen, C. (2024). Three-dimensional area coverage planning model for robotic application. Computers and Electronics in Agriculture, 219, 1-15. Artikel 108789. https://doi.org/10.1016/j.compag.2024.108789

Vahdanjoo, M., Grøn Sørensen, C. & Nørremark, M. (2025). Digital transformation of the agri-food system. Current Opinion in Food Science, 63, Artikel 101287. https://doi.org/10.1016/j.cofs.2025.101287

Ulsig, E. Z. & Volet, N. (2021). Second-order nonlinear effects in InGaAsP waveguides for efficient wavelength conversion to the mid-infrared. I P. G. Schunemann & K. L. Schepler (red.), Nonlinear Frequency Generation and Conversion: Materials and Devices XX Artikel 116700U SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2581819

Ulsig, E. Z. & Volet, N. (2021). Design study of efficient far-UVC second-harmonic generation using an integrated approach. I M. Bertolotti, A. V. Zayats & A. M. Zheltikov (red.), Nonlinear Optics and Applications XII (Bind 11770). Artikel 117700P SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2592408

Ulsig, E. Z., Degli Eredi, I. & Volet, N. (2022). Efficient frequency conversion of low-intensity light in AlGaAs-on-insulator waveguides. I P. G. Schunemann & V. Petrov (red.), Nonlinear Frequency Generation and Conversion: Materials and Devices XXI Artikel 119850D SPIE - International Society for Optical Engineering. https://doi.org/10.1117/12.2607179

Ulsig, E. Z. & Tønning, P. (2022, mar. 16). Forskere: En sikker type UV-lys er et nyt våben mod corona og fremtidige epidemier. https://videnskab.dk/forskerzonen/teknologi-innovation/en-sikker-type-uv-lys-er-det-nye-vaaben-mod-corona-og-fremtidige-epidemier

Ulsig, E. Z., Stanton, E. J., Reddy, D. V., Shalm, K., Volet, N. & Mirin, R. (2023). Correlated Photon Pairs Obtained by SPDC in AlGaAs-OI Waveguides. I Quantum 2.0: Proceedings Optica Quantum 2.0 Conference and Exhibition (s. QTh4C-2) https://doi.org/10.1364/QUANTUM.2023.QTh4C.2

Ulsig, E. Z., Degli-Eredi, I., Stanton, E. J. & Volet, N. (2022). Efficient Low Threshold Frequency Conversion in AlGaAs-On-Insulator Waveguides. Frontiers in Photonics, 3, Artikel 904651. https://doi.org/10.3389/fphot.2022.904651

Ulsig, E. Z. & Tønning, P. (2022). Forskere: En sikker type uv-lys er det nye våben mod corona og fremtidige epidemier. Videnskab.dk [online]. https://videnskab.dk/forskerzonen/teknologi-innovation/en-sikker-type-uv-lys-er-det-nye-vaaben-mod-corona-og-fremtidige-epidemier

Ulsig, E., Madsen, M., J. Stanton, E., Reddy, D., Leger, A., Sørensen, S., Degli-Eredi, I., Stevens, M., Hamel, D., Shalm, L., Mirin, R. & Volet, N. (2024). Widely tunable integrated GaAs and AlGaAs platforms for efficient second-order frequency conversion. https://doi.org/10.1364/opticaopen.25540030.v1

Ulsig, E. Z., Madsen, M. L., Stanton, E. J., Reddy, D. V., Leger, A. Z., Sørensen, S. R., Godoy, P. H., Degli-Eredi, I., Stevens, M. J., Hamel, D. R., Shalm, L. K., Mirin, R. P. & Volet, N. (2024). Efficient and widely tunable mid-infrared sources using GaAs and AlGaAs integrated platforms for second-order frequency conversion. Optics Express, 32(21), 36986-37000. https://doi.org/10.1364/OE.523615

Ulsig, E. Z., Linnet Madsen, M., Stanton, E. J., Venkatarama Reddy, D., Degli-Eredi, I., Mirin, R. & Volet, N. (2023). Single-photon downconversion in GaAs, AlGaAs and InGaP-on-insulator. I 2023 IEEE Photonics Conference (IPC) https://doi.org/10.1109/IPC57732.2023.10360732

Ulsig, E. Z. (2024). Second-order frequency conversion in III-V waveguides integrated on silicon. [Ph.d.-afhandling, Aarhus Universitet].

Ugurlu, H. I., Pham, X. H. & Kayacan, E. (2022). Sim-to-Real Deep Reinforcement Learning for Safe End-to-End Planning of Aerial Robots. Robotics, 11(5), Artikel 109. https://doi.org/10.3390/robotics11050109

Ugurlu, H. I., Redder, A. & Kayacan, E. (2025). Lyapunov-Inspired Deep Reinforcement Learning for Robot Navigation in Obstacle Environments. I 2025 IEEE Symposium on Computational Intelligence on Engineering/Cyber Physical Systems, CIES 2025 IEEE. https://doi.org/10.1109/CIES64955.2025.11007627

Tunon, O. A. (2024). Vision-based navigation for underwater safety-critical applications. [Ph.d.-afhandling, Aarhus Universitet].

Troldborg, K. B., Skov, S. I., Fathollahi, A. & Pedersen, J. H. (2026). Advanced Machine Learning Approach for Fast Temperature Estimation in SiC-Based Power Electronics Converters †. Electronics, 15(6), Artikel 1325. https://doi.org/10.3390/electronics15061325

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2020). Performance Indicator in Multilinear Compressive Learning. I 2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 (s. 1822-1828). Artikel 9308418 IEEE. https://doi.org/10.1109/SSCI47803.2020.9308418

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

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Remote Multilinear Compressive Learning with Adaptive Compression. IEEE Internet of Things Journal, 9(9), 6905-6913. https://doi.org/10.1109/jiot.2021.3114743

Tran, D. T., Kanniainen, J. & Iosifidis, A. (2021). How informative is the Order Book Beyond the Best Levels? Machine Learning Perspective. Afhandling præsenteret på NeurIPS 2021 Workshop on Machine Learning meets Econometrics. https://doi.org/10.2139/ssrn.3920827

Tran, D. T., Passalis, N., Tefas, A., Gabbouj, M. & Iosifidis, A. (2022). Attention-Based Neural Bag-of-Features Learning for Sequence Data. IEEE Access, 10, 45542-45552. https://doi.org/10.1109/ACCESS.2022.3169776

Tran, D. T., Gabbouj, M. & Iosifidis, A. (2022). Progressive and compressive learning. I A. Iosifidis & A. Tefas (red.), Deep Learning for Robot Perception and Cognition (s. 187-220). Elsevier. https://doi.org/10.1016/B978-0-32-385787-1.00014-2

Tøttrup, D., Skovgaard, S. L., Sejersen, J. L. F. & de Figueiredo, R. P. (2022). A Real-Time Method for Time-to-Collision Estimation from Aerial Images. Journal of Imaging, 8(3), Artikel 62. https://doi.org/10.3390/jimaging8030062

Tøttrup, M. F., Hu, E. C., Kramer, B. A., Macedo, H. D. & Esterle, L. (2023). Using INTO-CPS Tools in the Development of a Digital Twin for the F1TENTH Race Car. I P. Masci, C. Bernardeschi, P. Graziani, M. Koddenbrock & M. Palmieri (red.), Software Engineering and Formal Methods. SEFM 2022 Collocated Workshops: International Conference on Software Engineering and Formal Methods (s. 200-209). Springer. https://doi.org/10.1007/978-3-031-26236-4_18

Tola, D., Gonçalves Gomes, C. Â., Schultz, C. P. L., Schlette, C., Hansen, C. & Esterle, L. (2021). RoboCIM: Towards a Domain Model for Industrial Robot System Configurators. I A. Soylu, A. T. Nezhad, N. Nikolov, I. Toma, A. Fensel & J. Vennekens (red.), Proceedings of the 15th International Rule Challenge, 7th Industry Track, and 5th Doctoral Consortium @ RuleML+RR 2021 co-located with 17th Reasoning Web Summer School (RW 2021) and 13th DecisionCAMP 2021 as part of Declarative AI 2021 CEUR-WS.org. http://ceur-ws.org/Vol-2956/paper12.pdf

Tola, D. & Larsen, P. G. (2021). A Co-Simulation Based Approach for Developing Safety-Critical Systems. I Proceedings of the 18th International Overture Workshop https://arxiv.org/pdf/2101.07261.pdf#page=65

Tola, D., Madsen, E., Gomes, C., Esterle, L., Schlette, C., Hansen, C. & Larsen, P. G. (2022). Towards Easy Robot System Integration: Challenges and Future Directions. I 2022 IEEE/SICE International Symposium on System Integration (SII) (s. 77-82). IEEE. https://doi.org/10.1109/SII52469.2022.9708846

Tola, D., Böttjer, T., Larsen, P. G. & Esterle, L. (2022). Towards Modular Digital Twins of Robot Systems. I Proceedings - 2022 IEEE International Conference on Autonomic Computing and Self-Organizing Systems Companion, ACSOS-C 2022 (s. 95-100). IEEE. https://doi.org/10.1109/ACSOSC56246.2022.00040

Tola, D. & Corke, P. (2023). Understanding URDF: A Dataset and Analysis.

Tola, D. & Corke, P. (2023). Understanding URDF: A Survey Based on User Experience.

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