Degeler, V. O., Hadadian, M., Karabulut, E., Lazovik, A., van het Loo, H., Tello, A., & Truong, H. (2025). DiTEC: Digital Twin for Evolutionary Changes in Water Distribution Networks. In T. Margaria, & B. Steffen (Eds.), Leveraging Applications of Formal Methods, Verification and Validation. Application Areas: 12th International Symposium, ISoLA 2024, Crete, Greece, October 27–31, 2024 : proceedings (Vol. V, pp. 62-82). (Lecture Notes in Computer Science; Vol. 15223). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-75390-9_5
Hadadian Nejad Yousefi, M., Degeler, V. O., & Lazovik, A. (2024). Self-Adaptive Service Selection for Machine Learning Continuous Delivery. In 2024 IEEE International Conference on Web Services (ICWS) IEEE. https://doi.org/10.1109/ICWS62655.2024.00123
Karabulut, E., Groth, P. T., & Degeler, V. O. (in press). 3K: Knowledge-Enriched Digital Twin Framework. In 14th International Conference on the Internet of Things (IoT 2024) workshops: International Workshop on Longevity in IoT Systems (LongevIoT)
Karabulut, E., Pileggi, S. F., Groth, P., & Degeler, V. (2024). Ontologies in Digital Twins: A Systematic Literature Review. Future Generation Computer Systems, 153, 442-456. https://doi.org/10.1016/j.future.2023.12.013[details]
Karabulut, E., Pileggi, S., Groth, P. & Degeler, V. (21-7-2023). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review". Zenodo. https://doi.org/10.5281/zenodo.8172341
Khalil, A., Lotfian Delouee, M., Degeler, V., Meuser, T., Fernandez Anta, A., & Koldehofe, B. (2024). Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks. In 2024 22nd Mediterranean Communication and Computer Networking Conference: MedComNet 2024 : Nice, France, 11-13 June 2024 (pp. 55-64). IEEE. https://doi.org/10.1109/MedComNet62012.2024.10578208[details]
Lotfian Delouee, M., Degeler, V., Amthor, P., & Koldehofe, B. (2024). APP-CEP: Adaptive Pattern-level Privacy Protection in Complex Event Processing Systems. In G. Lenzini, P. Mori, & S. Furnell (Eds.), ICISSP 2024: Proceedings of the 10th International Conference on Information Systems Security and Privacy : 26-28 February, 2024, Rome, Italy (pp. 486-497). SciTePress. https://doi.org/10.5220/0012358700003648[details]
Lotfian Delouee, M., Pernes, D., Degeler, V. O., & Koldehofe, B. (2024). Towards Federated LLM-Powered CEP Rule Generation and Refinement. In DEBS '24: Proceedings of the 18th ACM International Conference on Distributed and Event-based Systems (pp. 185-186). ACM. https://doi.org/10.1145/3629104.3672429
Tello, A., Degeler, V., & Lazovik, A. (2024). Too Good To Be True: accuracy overestimation in (re)current practices for Human Activity Recognition. In 2024 IEEE International Conference on Pervasive Computing and Communications workshops and other affiliated events (PerCom workshops 2024) : Biarritz, France, 11-15 March 2024 (pp. 511-517). IEEE. https://doi.org/10.1109/PerComWorkshops59983.2024.10503465[details]
Tello, A., Truong, H., Lazovik, A., & Degeler, V. O. (2024). Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Engineering Proceedings, 69, Article 50. https://doi.org/10.3390/engproc2024069050
Truong, H., Tello, A., Lazovik, A., & Degeler, V. (2024). Graph Neural Networks for Pressure Estimation in Water Distribution Systems. Water Resources Research, 60(7), Article e2023WR036741. https://doi.org/10.1029/2023WR036741[details]
Yiwen, H., Karabulut, E., & Degeler, V. O. (in press). Large Language Model for Ontology Learning In Drinking Water Distribution Network Domain. In EKAW 2024 Workshops, Tutorials, Posters and Demos, 24th International Conference on Knowledge Engineering and Knowledge Management
van Etten, T., Degeler, V., & Luo, D. (2024). Large-Scale Forecasting of Electric Vehicle Charging Demand Using Global Time Series Modeling. In A. Vinel, K. Berns, J. Ploeg, & O. Gusikhin (Eds.), VEHITS 2024: proceedings of the 10th International Conference on Vehicle Technology and Intelligent Transport Systems : 2-4 May, 2024, Angers, France (pp. 40-51). SciTePress. https://doi.org/10.5220/0012555400003702[details]
Demchenko, Y., Degeler, V., Opresu, A., & Brewer, S. (2023). Professional and 21st Century Skills for Data Driven Digital Economy. In 2023 IEEE Global Engineering Education Conference (EDUCON): Salmiya, Kuwait, 1-4 May 2023, American University of Kuwait (pp. 847-854). IEEE. https://doi.org/10.1109/EDUCON54358.2023.10125263[details]
Karabulut, E., Degeler, V., & Groth, P. (2023). Semantic Association Rule Learning from Time Series Data and Knowledge Graphs. In A. Waaler, E. Kharlamov, B. Zhou, A. Soylu, D. Kyritsis, D. Roman, O. Savkovic, & S. Staab (Eds.), Proceedings of the Second International Workshop on Semantic Industrial Information Modelling (SemIIM 2023) : co-located with the 22nd International Semantic Web Conference (ISWC 2023) : Greece, Athens, 7 November 2023 Article 3 (CEUR workshop proceedings; Vol. 3647). CEUR-WS. https://doi.org/10.48550/arXiv.2310.07348[details]
Lotfian Delouee, M., Koldehofe, B., & Degeler, V. (2023). AQuA-CEP: Adaptive Quality-Aware Complex Event Processing in the Internet of Things. In DEBS 2023: proceedings of the 17th ACM International Conference on Distributed and Event-based Systems : June 27-30, 2023, Neuchâtel, Switzerland (pp. 13-24). Association for Computing Machinery. https://doi.org/10.1145/3583678.3596884[details]
Lotfian Delouee, M., Koldehofe, B., & Degeler, V. (2023). Poster: Towards Pattern-Level Privacy Protection in Distributed Complex Event Processing. In DEBS 2023: proceedings of the 17th ACM International Conference on Distributed and Event-based Systems : June 27-30, 2023, Neuchâtel, Switzerland (pp. 185-186). Association for Computing Machinery. https://doi.org/10.1145/3583678.3603278[details]
Yousefi, M. H. N., Degeler, V., & Lazovik, A. (2023). Empowering Machine Learning Development with Service-Oriented Computing Principles. In M. Aiello, J. Barzen, S. Dustdar, & F. Leymann (Eds.), Service-Oriented Computing - 17th Symposium and Summer School, SummerSOC 2023, Revised Selected Papers: 17th Symposium and Summer School, SummerSOC 2023, Heraklion, Crete, Greece, June 25–July 1, 2023 : revised selected papers (pp. 24-44). (Communications in Computer and Information Science; Vol. 1847). Springer. https://doi.org/10.1007/978-3-031-45728-9_2[details]
Lotfian Delouee, M., Koldehofe, B., & Degeler, V. (2022). Towards adaptive quality-aware Complex Event Processing in the Internet of Things. In 2022 18th International Conference on Mobility, Sensing and Networking : MSN 2022: proceedings : 14-16 December 2022, Guangzhou, China (pp. 571-575). IEEE Computer Society. https://doi.org/10.1109/MSN57253.2022.00095[details]
Riesebos, R., Degeler, V., & Tello, A. (2022). Smartphone-Based Real-Time Indoor Positioning Using BLE Beacons. In 2022 IEEE 18th International Conference on Automation Science and Engineering (CASE 2022): Mexico City, Mexico, 20-24 August 2022 (pp. 1281-1288). IEEE. https://doi.org/10.1109/CASE49997.2022.9926639[details]
Al-Saudi, K., Degeler, V., & Medema, M. (2021). Energy consumption patterns and load forecasting with profiled CNN-LSTM networks. Processes, 9(11), Article 1870. https://doi.org/10.3390/pr9111870
Degeler, V., Heydenrijk-Ottens, L., Luo, D., van Oort, N., & van Lint, H. (2021). Unsupervised approach towards analysing the public transport bunching swings formation phenomenon. Public Transport, 13(3), 533-555. https://doi.org/10.1007/s12469-020-00251-z
2019
Mantouka, E. G., Vlahogianni, E. I., Papacharalampous, A. E., Heydenrijk-Ottens, L., Shelat, S., Degeler, V., & van Lint, H. (2019). Understanding Travel Behavior through Travel Happiness. Transportation research record, 2673(4), 889-897. https://doi.org/10.1177/0361198119836761
2018
French, R., Degeler, V., & Jones, K. (2018). A Model of a Malware Infected Automated Guided Vehicle for Experimental Cyber-Physical Security. In Lecture Notes in Networks and Systems (pp. 672-688). (Lecture Notes in Networks and Systems; Vol. 16). Springer. https://doi.org/10.1007/978-3-319-56991-8_49
2016
Degeler, V., French, R., & Jones, K. (2016). Combined danger signal and anomaly-based threat detection in cyber-physical systems. In M. E. M. Campista, A. Somov, B. Mandler, H. Chaouchi, M. Fazio, D. Caganova, S. Giordano, J. Marquez-Barja, S. Zeadally, M. Badra, & R-L. Vieriu (Eds.), Internet of Things: IoT Infrastructures - 2nd International Summit, IoT 360° 2015, Revised Selected Papers (pp. 27-39). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST; Vol. 169). Springer Verlag. https://doi.org/10.1007/978-3-319-47063-4_3
Degeler, V., French, R., & Jones, K. (2016). Self-Healing Intrusion Detection System Concept. In M. Qiu (Ed.), Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016 (pp. 351-356). Article 7502315 (Proceedings - 2nd IEEE International Conference on Big Data Security on Cloud, IEEE BigDataSecurity 2016, 2nd IEEE International Conference on High Performance and Smart Computing, IEEE HPSC 2016 and IEEE International Conference on Intelligent Data and Security, IEEE IDS 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigDataSecurity-HPSC-IDS.2016.27
2015
Degeler, V., French, R., & Jones, K. (2015). Demonstrating Danger Theory based threat detection for robotic manufacture protection. In IntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference (pp. 283-284). Article 7361156 (IntelliSys 2015 - Proceedings of 2015 SAI Intelligent Systems Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IntelliSys.2015.7361156
2014
Clifford, E., Coakley, D., Curry, E., Degeler, V., Costa, A., Messervey, T., Van Andel, S. J., Van De Giesen, N., Kouronpetroglou, C., Mink, J., & Smit, S. (2014). Interactive water services: The WATERNOMICS approach. Procedia Engineering, 89, 1058-1065. https://doi.org/10.1016/j.proeng.2014.11.225
Degeler, V., & Curry, E. (2014). Human-Assisted Rule Satisfaction in Partially Observable Environments. In Y. Zheng, P. Thulasiraman, B. O. Apduhan, Y. Nakamoto, H. Ning, & Y. Sun (Eds.), Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014 (pp. 171-178). Article 7306949 (Proceedings - 2014 IEEE International Conference on Ubiquitous Intelligence and Computing, 2014 IEEE International Conference on Autonomic and Trusted Computing, 2014 IEEE International Conference on Scalable Computing and Communications and Associated Symposia/Workshops, UIC-ATC-ScalCom 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/UIC-ATC-ScalCom.2014.134
Degeler, V., & Lazovik, A. (2014). Dynamic constraint satisfaction with space reduction in smart environments. International Journal on Artificial Intelligence Tools, 23(6), Article 14600276. https://doi.org/10.1142/S0218213014600276
Degeler, V., Lazovik, A., Leotta, F., & Mecella, M. (2014). Itemset-based mining of constraints for enacting smart environments. In 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS) (pp. 41-46). IEEE. https://doi.org/10.1109/PerComW.2014.6815162
2013
Degeler, V., & Lazovik, A. (2013). Architecture pattern for context-aware smart environments. In Creating Personal, Social, and Urban Awareness through Pervasive Computing (pp. 108-130). IGI Global. https://doi.org/10.4018/978-1-4666-4695-7.ch005
Degeler, V., & Lazovik, A. (2013). Dynamic constraint reasoning in smart environments. In Proceedings - 25th International Conference on Tools with Artificial Intelligence, ICTAI 2013 (pp. 167-174). IEEE Computer Society. https://doi.org/10.1109/ICTAI.2013.34
Degeler, V., Gonzalez, L. I. L., Leva, M., Shrubsole, P., Bonomi, S., Amft, O., & Lazovik, A. (2013). Service-oriented architecture for smart environments. In Proceedings - IEEE 6th International Conference on Service-Oriented Computing and Applications, SOCA 2013 (pp. 99-104). Article 6717291 (Proceedings - IEEE 6th International Conference on Service-Oriented Computing and Applications, SOCA 2013). IEEE Computer Society. https://doi.org/10.1109/SOCA.2013.26
Nguyen, T. A., Degeler, V., Contarino, R., Lazovik, A., Bucur, D., & Aiello, M. (2013). Towards context consistency in a rule-based activity recognition architecture. In Proceedings - IEEE 10th International Conference on Ubiquitous Intelligence and Computing, UIC 2013 and IEEE 10th International Conference on Autonomic and Trusted Computing, ATC 2013 (pp. 625-630). IEEE Computer Society. https://doi.org/10.1109/UIC-ATC.2013.97
2012
Degeler, V., & Lazovik, A. (2012). Cost-efficient context-aware rule maintenance. In 2012 IEEE International Conference on Pervasive Computing and Communications Workshops, PERCOM Workshops 2012 (pp. 608-612). IEEE Computer Society. https://doi.org/10.1109/PerComW.2012.6197587
Georgievski, I., Degeler, V., Pagani, G. A., Nguyen, T. A., Lazovik, A., & Aiello, M. (2012). Optimizing energy costs for offices connected to the smart grid. IEEE Transactions on Smart Grid, 3(4), 2273-2285. Article 6377248. https://doi.org/10.1109/TSG.2012.2218666
Nizamic, F., Degeler, V., Groenboom, R., & Lazovik, A. (2012). Policy-based scheduling of cloud services. Scalable Computing, 13(3), 187-199.
2011
Degeler, V., & Lazovik, A. (2011). Interpretation of inconsistencies via context consistency diagrams. In 2011 IEEE International Conference on Pervasive Computing and Communications, PerCom 2011 (pp. 20-27). IEEE Computer Society. https://doi.org/10.1109/PERCOM.2011.5767588
2010
Degeler, V., Georgievski, I., Lazovik, A., & Aiello, M. (2010). Concept mapping for faster QoS-aware web service composition. In Proceedings - 2010 IEEE International Conference on Service-Oriented Computing and Applications, SOCA 2010 Article 5707193 IEEE Computer Society. https://doi.org/10.1109/SOCA.2010.5707193
Tello, A., & Degeler, V. (2021). Digital Twins: An enabler for digital transformation. In B. S. Baalmans, T. L. J. Broekhuizen, & N. E. Fabian (Eds.), Digital Transformation: A Guide for Managers (pp. 176-203). Groningen Digital Business Centre. https://doi.org/10.5281/zenodo.7647493
Tello, A., Truong, H., Lazovik, A. & Degeler, V. (27-5-2024). Large-Scale Multipurpose Benchmark Datasets For Assessing Data-Driven Deep Learning Approaches For Water Distribution Networks. Zenodo. https://doi.org/10.5281/zenodo.11353195
Karabulut, E., Pileggi, S., Groth, P. & Degeler, V. (21-7-2023). Data and Statistics for the SLR entitled "Ontologies in Digital Twins: A Systematic Literature Review". Zenodo. https://doi.org/10.5281/zenodo.8172341
De UvA gebruikt cookies voor het meten, optimaliseren en goed laten functioneren van de website. Ook worden er cookies geplaatst om inhoud van derden te kunnen tonen en voor marketingdoeleinden. Klik op ‘Accepteren’ om akkoord te gaan met het plaatsen van alle cookies. Of kies voor ‘Weigeren’ om alleen functionele en analytische cookies te accepteren. Je kunt je voorkeur op ieder moment wijzigen door op de link ‘Cookie instellingen’ te klikken die je onderaan iedere pagina vindt. Lees ook het UvA Privacy statement.