ADVCOMP 2024 - The Eighteenth International Conference on Advanced Engineering Computing and Applications in Sciences
September 29, 2024 - October 03, 2024
ADVCOMP 2024: Awards
Onsite and Online Options: In order to accommodate a large number of situations, we are offering the option for either physical presence or virtual participation (pdf slides or pre-recorded videos).
The papers listed below have been selected as "Best Papers" based on the reviews of the original submission, the camera-ready version, and the presentation during the conference. For the awarded papers, a digital award will be issued in the name of the authors. The authors of these papers are also receiving invitations to submit an extended article version to one of the IARIA Journals.
Awarded Papers (also Invited for IARIA Journals)
You’ve Got a Plan? A Domain Modelling Approach for Collaborative Product Disassembly Planning with PDDL
Dominique Briechle, Andreas Rausch
Integrative Development and Evaluation of V2X Communication Architectures to Support Autonomous Driving Systems in 5G Campus Networks
Florian Pramme, Bastian Teßin, Gert Bikker, Tamas Kurczveil
MORUS-PRNG: a Hardware Accelerator Based on the MORUS Cipher and the IXIAM Framework
Alessio Medaglini, Mirco Mannino, Biagio Peccerillo, Sandro Bartolini
Comparing Fault-tolerance in Kubernetes and Slurm in HPC Infrastructure
Mirac Aydin, Michael Bidollahkhani, Julian Kunkel
The following papers have been selected on the basis of their contents, specificaly for lending themselves to an interesting extended work. The authors of these papers are receiving invitations to submit an extended article version to one of the IARIA Journals.
Papers Invited for IARIA Journals
FEM Modeling for PCB Assembly Simulation
Ming-Hsiao Lee, Jiunn-Horng Lee, Chih-Min Yao, Jen-Gaw Lee
Mixing Flows in Dynamic Fluid Transport Simulations
Mehrnaz Anvari, Anton Baldin, Tanja Clees, Bernhard Klaassen, Igor Nikitin, Lialia Nikitina
Application of a Maneuver-Based Decision Making Approach for an Autonomous System Using a Learning Approach
Xin Xing, Sebastian Ohl
Automating Benchmarking Process for Multimodal Large Language Models (MLLMs) in the Context of Waste Disposal
Sundus Hammoud, Robert Werner