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Institut for Elektro- og Computerteknologi

Publications by Communication, Control & Automation

Are you looking for publications by Section of Communication, Control & Automation? On this page you can find all the publications made by the Section of Communication, Control & Automation - Department of Electrical and Computer Engineering, Aarhus University.

Below you can find a list of all the publications, their publishing date, their author(s), and titles. The list can be sorted by date, author, and title:

List of Publications

Sortér efter: Dato | Forfatter | Titel

Lucani Rötter, D. E., Vieira, F. & Montpetit, M.-J. (2011). Opportunities for Network Coding in Satellite Networks. SATELLITE AND SPACE COMMUNICATIONS, 21(2), 7-11. http://ssc.committees.comsoc.org/files/2015/11/sscnlv21n2.pdf

Lucani Rötter, D. E., Pedersen, M. V., Ruano, D., W. Sørensen, C., Fitzek, F. H. P., Heide, J., Geil, O., Nguyen, VU. & Reisslein, M. (2018). Fulcrum: Flexible Network Coding for Heterogeneous Devices. IEEE Access, 6, 77890-77910. Artikel 8554264. https://doi.org/10.1109/ACCESS.2018.2884408

Lucani Rötter, D. E., Nielsen, L., Orlandi, C., Pagnin, E. & Vestergaard, R. (2020). Secure generalized deduplication via multi-key revealing encryption. I C. Galdi & V. Kolesnikov (red.), Security and Cryptography for Networks (s. 298-318). Springer. https://doi.org/10.1007/978-3-030-57990-6_15

Loufopoulou, M., Rodias, E., Bochtis, D. & Moshou, D. (2013). Estimation and analysis of CO2¬ emissions from agricultural vehicles. I Proceedings of 8th National Conference of Hellenic Society of Agricultural Engineers (HelAgEng 2011) (s. 326-330)

Liu, D., Zhang, G., Zhao, X. & Sørensen, C. (2011). A Simulation and Experiments of Rapeseed Logistics Supply System Based on Flexsim Software. Afhandling præsenteret på Advanced Research on Computer Education, Simulation and Modeling , Wuhan, Kina. https://doi.org/10.1007/978-3-642-21783-8

Liu, J. & Zhang, Q. (2018). Offloading Schemes in Mobile Edge Computing for Ultra-Reliable Low Latency Communications. IEEE Access, 6, 12825-12837. https://doi.org/10.1109/ACCESS.2018.2800032

Liu, J. & Zhang, Q. (2019). Code-Partitioning Offloading Schemes in Mobile Edge Computing for Augmented Reality. I IEEE Access (Bind 7, s. 11222-11236). IEEE. https://doi.org/10.1109/ACCESS.2019.2891113

Liu, J. & Zhang, Q. (2019). Reliability and Latency Aware Code-Partitioning Offloading in Mobile Edge Computing. I 2019 IEEE Wireless Communications and Networking Conference, WCNC 2019 Artikel 8885778 IEEE. https://ieeexplore.ieee.org/abstract/document/8885778

Liu, J. & Zhang, Q. (2019). Edge Computing Enabled Mobile Augmented Reality with Imperfect Channel Knowledge. I European Wireless 2019 Conference, EW 2019 (s. 90-95). VDE Verlag GmbH. https://www.vde-verlag.de/proceedings-en/564948016.html

Liu, J. & Zhang, Q. (2020). To Improve Service Reliability for AI-Powered Time-Critical Services Using Imperfect Transmission in MEC: An Experimental Study. IEEE Internet of Things Journal, 7(10), 9357-9371. Artikel 9051992. https://doi.org/10.1109/JIOT.2020.2984333

Liu, J. & Zhang, Q. (2020). Using Imperfect Transmission in MEC Offloading to Improve Service Reliability of Time-Critical Computer Vision Applications. IEEE Access, 8, 107364 - 107372. Artikel 9114971. https://doi.org/10.1109/ACCESS.2020.3001620

Liu, J. & Zhang, Q. (2020). Computation Resource Allocation for Heterogeneous Time-Critical IoT Services in MEC. I 2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings Artikel 9120832 IEEE. https://doi.org/10.1109/WCNC45663.2020.9120832

Liu, J. & Zhang, Q. (2020). Adaptive Task Partitioning at Local Device or Remote Edge Server for Offloading in MEC. I 2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings Artikel 9120484 IEEE. https://doi.org/10.1109/WCNC45663.2020.9120484

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

Lindstrøm, J. & Sørensen, C. A. G. (2008). ICT in Dairy production - a complete management tool. I L. Pesonen, C. G. Sørensen, R. Nikkilä, A. Rydberg & O. Green (red.), Information and Communication Technology in Agriculture: NJF seminar no 411 (Bind 4, No 1, s. 24-26). NJF.

Lindstrøm, J. & Sørensen, C. A. G. (2009). Information modelling in dairy production. I C. Lokhorst, J. F. M. Huijsmans & R. P. M. de Louw (red.), JIAC2009: Book of abstracts (s. 123). Wageningen Academic Publishers.

Lindstrøm, J. & Sørensen, C. A. G. (2009). Information modelling in dairy production. I A. Bregt, S. Wolfert, J. E. Wien & C. Lokhorst (red.), EFITA conference '09 - Papers presented at the 7th EFITA conference (s. 161-164). Wageningen Academic Publishers.

Lin, Y., Liao, Y., Wu, Z. & Zhou, P. (2024). Mitigating Backdoors in Federated Learning with FLD. I 2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology, AINIT 2024 (s. 530-535). IEEE. https://doi.org/10.1109/AINIT61980.2024.10581839

Liang, Y., Kortoçi, P., Zhou, P., Lee, L. H., Mehrabi, A., Hui, P., Tarkoma, S. & Crowcroft, J. (2022). Federated split GANs for collaborative training with heterogeneous devices[Formula presented]. Software Impacts, 14, Artikel 100436. https://doi.org/10.1016/j.simpa.2022.100436

Li, L., Zhao, G., Shi, W., Chen, Z. & Zhang, Q. (2016). Autonomous relaying scheme for energy-efficient cooperative multicast communications. I 2016 IEEE Wireless Communications and Networking Conference, WCNC 2016: WCNC 2016 Artikel 7565083 IEEE. https://doi.org/10.1109/WCNC.2016.7565083

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, 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, J., Wang, H., Liu, Z., Zhou, P., Chen, X., Li, Q. & Hong, R. (2023). Toward Optimal Real-Time Volumetric Video Streaming: A Rolling Optimization and Deep Reinforcement Learning Based Approach. IEEE Transactions on Circuits and Systems for Video Technology, 33(12), 7870-7883. https://doi.org/10.1109/TCSVT.2023.3277893

Li, H., Ma, L., Shi, H., Hao, Y., Liao, Y., Cheng, L. & Zhou, P. Y. (2025). 3D-GOI: 3D GAN Omni-Inversion for Multifaceted and Multi-object Editing. I A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler & G. Varol (red.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (s. 390-406). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-73033-7_22

Li, H., Shi, H., Zhang, W., Wu, W., Liao, Y., Wang, L., Lee, L. H. & Zhou, P. Y. (2025). DreamScene: 3D Gaussian-Based Text-to-3D Scene Generation via Formation Pattern Sampling. I A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler & G. Varol (red.), Computer Vision – ECCV 2024 - 18th European Conference, Proceedings (s. 214-230). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-72904-1_13

Letafat, A., Rafiei Foroushani, M., Sheikh, M., Afshari-Igder, M., Banaei, M., Boudjadar, J. & Khooban, M. H. (2020). Simultaneous energy management and optimal components sizing of a zero-emission ferry boat. Journal of Energy Storage, 28, Artikel 101215. https://doi.org/10.1016/j.est.2020.101215

Letafat, A., Rafiei, M., Ardeshiri, M., Sheikh, M., Banaei, M., Boudjadar, J. & Khooban, M. H. (2020). An Efficient and Cost-Effective Power Scheduling in Zero-Emission Ferry Ships. Complexity, 2020, Artikel 6487873. https://doi.org/10.1155/2020/6487873

Lee, L. H., Chatzopoulos, D., Zhou, P. & Braud, T. (2023). Metaverse: An introduction. I Metaverse Communication and Computing Networks: Applications, Technologies, and Approaches Wiley-Interscience. https://doi.org/10.1002/9781394160013.ch1

Lee, L.-H., Hosio, S., Braud, T. & Zhou, P. (2024). A Roadmap Toward Metaversity: Recent Developments and Perspectives in Education. I D. Liu, R. Huang, A. H. S. Metwally, A. Tlili & E. Fan Lin (red.), Application of the Metaverse in Education (s. 73-95). Springer Nature. https://doi.org/10.1007/978-981-97-1298-4_5

Lee, L. H., Braud, T., Zhou, P. Y., Wang, L., Xu, D., Lin, Z., Kumar, A., Bermejo, C. & Hui, P. (2024). All One Needs to Know about Metaverse: A Complete Survey on Technological Singularity, Virtual Ecosystem, and Research Agenda. Foundations and Trends in Human-Computer Interaction, 18(2-3), 100-337. https://doi.org/10.1561/1100000095

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.

Lawson, L. G., Pedersen, S. M., Sørensen, C. A. G., Pesonen, L., Fountas, S., Werner, A., Oudshoorn, F. W., Herold, L., Chatzinikos, T., Kirketerp, I. M. & Blackmore, S. (2011). A four nation survey of farm information management and advanced farming systems: A descriptive analysis of survey responses. Computers and Electronics in Agriculture, 77(1), 7-20. https://doi.org/10.1016/j.compag.2011.03.002

Lassen, P., Bøjer, O. Q., Hansen, J. G., Jensen, A. L. & Thysen, I. (2003). Implementation of Internet based decision support systems in Estonia, Latvia, Lithuania and Poland. I EFITA 2003 Conference (s. 59-66). <Forlag uden navn>.

Larsen, B. H., Holst, T., Shen, Y., Freltoft, T., Osbahr, C. J., Jacobsen, R. H. & Keiding, S. R. (1997). Generation and propagation of subpicosecond pulses in a photoconductive GaAs switch integrated onto a gold/YBa/sub 2/Cu/sub 3/O/sub x/ coplanar transmission line structure. I E E E Transactions on Applied Superconductivity, 7(2), 3726-3729. https://doi.org/10.1109/77.622228

Larsen, P. G., Fitzgerald, J., Gomes, C., Woodcock, J., Basagiannis, S., Ulisse, A., Esterle, L., Lucani Rötter, D. E., Hansen, S. T. & Oakes, B. J. (2024). Future Directions and Challenges. I J. Fitzgerald, C. Gomes & P. G. Larsen (red.), The Engineering of Digital Twins (s. 363-386). Springer. https://doi.org/10.1007/978-3-031-66719-0_15

Lampridi, M. G., Kateris, D., Vasileiadis, G., Marinoudi, V., Pearson, S., Sørensen, C. G., Balafoutis, A. & Bochtis, D. (2019). A case-based economic assessment of robotics employment in precision arable farming. Agronomy, 9(4), Artikel 175. https://doi.org/10.3390/agronomy9040175

Lampridi, M. G., Sørensen, C. G. & Bochtis, D. (2019). Agricultural sustainability: A review of concepts and methods. Sustainability, 11(18), Artikel 5120. https://doi.org/10.3390/su11185120

Lampridi, M., Kateris, D., Sørensen, C. G. & Bochtis, D. (2020). Energy footprint of mechanized agricultural operations. Energies, 13(3), Artikel 769. https://doi.org/10.3390/en13030769

Kumar, V., Mukherjee, M., Lloret, J., Zhang, Q. & Kumari, M. (2022). Delay-optimal and Incentive-aware Computation Offloading for Reconfigurable Intelligent Surface-assisted Mobile Edge Computing. IEEE Networking Letters, 4(3), 127-131. https://doi.org/10.1109/LNET.2022.3187720

Kuldeep, G. & Zhang, Q. (2020). Revisiting Compressive Sensing based Encryption Schemes for IoT. I 2020 IEEE Wireless Communications and Networking Conference, WCNC 2020 - Proceedings Artikel 9120785 IEEE. https://doi.org/10.1109/WCNC45663.2020.9120785

Kuldeep, G. & Zhang, Q. (2020). Energy Concealment based Compressive Sensing Encryption for Perfect Secrecy for IoT. I 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings Artikel 9322181 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9322181

Kuldeep, G. & Zhang, Q. (2020). Compressive Sensing based Multi-class Privacy-preserving Cloud Computing. I 2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings Artikel 9348093 IEEE. https://doi.org/10.1109/GLOBECOM42002.2020.9348093

Kuldeep, G. & Zhang, Q. (2021). A Novel Efficient Secure and Error-Robust Scheme for Internet of Things Using Compressive Sensing. IEEE Access, 9, 40903-40914. Artikel 9373354. https://doi.org/10.1109/ACCESS.2021.3064700

Kuldeep, G. & Zhang, Q. (2022). Design Prototype and Security Analysis of a Lightweight Joint Compression and Encryption Scheme for Resource-constrained IoT Devices. IEEE Internet of Things Journal, 9(1), 165-181. https://doi.org/10.1109/JIOT.2021.3098859

Kuldeep, G. (2022). Lightweight Time-Series Signal Compression Period Extraction and Multiresolution using Difference Sequences. IEEE Internet of Things Journal, 9(9), 7043-7050. https://doi.org/10.1109/JIOT.2021.3113951

Kuldeep, G. (2022). Secure Data Compression for Internet of Things. Århus Universitet.

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AU Engineering