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Wongwan Jung and Daejun Chang
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Jiacun Wang, Guipeng Xi, Xiwang Guo, Shujin Qin and Henry Han
The scheduling of disassembly lines is of great importance to achieve optimized productivity. In this paper, we address the Hybrid Disassembly Line Balancing Problem that combines linear disassembly lines and U-shaped disassembly lines, considering multi...
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Aristeidis Karras, Anastasios Giannaros, Christos Karras, Leonidas Theodorakopoulos, Constantinos S. Mammassis, George A. Krimpas and Spyros Sioutas
In the context of the Internet of Things (IoT), Tiny Machine Learning (TinyML) and Big Data, enhanced by Edge Artificial Intelligence, are essential for effectively managing the extensive data produced by numerous connected devices. Our study introduces ...
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Muhammad Sheraz, Teong Chee Chuah, Mardeni Bin Roslee, Manzoor Ahmed, Amjad Iqbal and Ala?a Al-Habashna
Data caching is a promising technique to alleviate the data traffic burden from the backhaul and minimize data access delay. However, the cache capacity constraint poses a significant challenge to obtaining content through the cache resource that degrade...
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Herbert Palm and Lorin Arndt
The multi-objective optimization (MOO) of complex systems remains a challenging task in engineering domains. The methodological approach of applying MOO algorithms to simulation-enabled models has established itself as a standard. Despite increasing in c...
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Wongwan Jung and Daejun Chang
This study proposed a deep reinforcement learning-based energy management strategy (DRL-EMS) that can be applied to a hybrid electric ship propulsion system (HSPS) integrating liquid hydrogen (LH2) fuel gas supply system (FGSS), proton-exchange membrane ...
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Jonas F. Leon, Yuda Li, Xabier A. Martin, Laura Calvet, Javier Panadero and Angel A. Juan
The use of simulation and reinforcement learning can be viewed as a flexible approach to aid managerial decision-making, particularly in the face of growing complexity in manufacturing and logistic systems. Efficient supply chains heavily rely on steamli...
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Kamyar B. Shahrbijari, Joaquim A. O. Barros and Isabel B. Valente
This article explores the application of the global resistance methods (GRMs) on the design of hybrid glass fiber-reinforced polymer (GFRP) and steel fiber-reinforced concrete (SFRC) beams. Addressing challenges posed by GFRP-reinforced beams, this study...
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Sitong Zhang, Yibing Li, Fang Ye, Xiaoyu Geng, Zitao Zhou and Tuo Shi
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Ali Mirzazade, Cosmin Popescu and Björn Täljsten
The aim of this study was to find strains in embedded reinforcement by monitoring surface deformations. Compared with analytical methods, application of the machine learning regression technique imparts a noteworthy reduction in modeling complexity cause...
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