output
20232026
most citedSecure Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless MEC Networks

27 citations

7 papers

cs.SE2026

A Mixed-Method Empirical Study of LLM Assistance in Software Engineering Workflows

Pamali D. Weerasinghe, Roshan N. Rajapakse, Isuru Dharmadasa +1

Large Language Models (LLMs) are increasingly integrated into software development workflows, yet their effects are often discussed without distinguishing between task types, devel…

stat.AP2026★ 1 cited

Coating Breakdown Prediction for Ships and Inspection Planning

Huy Truong-Ba, Michael E. Cholette, Geoffrey Will +1

Marine corrosion significantly reduces a ship's availability, increases costs of operation and could impact safety. Protective coatings mitigate these risks, but their effectivenes…

hep-ph2025★ 4 cited

F-mode Oscillations of Neutron Stars with Dark Matter from Neutron Decay: Implications for Gravitational-Wave Detectability

Wasif Husain

In this study, the impact of neutron decay into dark matter and various dark matter self-interaction strengths on neutron star properties have been explored. Using the quark-meson…

cs.SI2025★ 4 cited

Robust Deep Signed Graph Clustering via Weak Balance Theory

Peiyao Zhao, Xin Li, Zeyu Zhang +3

Signed graph clustering is a critical technique for discovering community structures in graphs that exhibit both positive and negative relationships. We have identified two signifi…

cs.LG2025★ 2 cited

Physics-Informed Machine Learning for Microscale Drying of Plant-Based Foods: A Systematic Review of Computational Models and Experimental Insights

C. P. Batuwatta-Gamage, H. Jeong, HCP Karunasena +3

This review examines the current state of research on microscale cellular changes during the drying of plant-based food materials (PBFM), with particular emphasis on computational…

cs.LG2023★ 27 cited

Secure Deep Reinforcement Learning for Dynamic Resource Allocation in Wireless MEC Networks

Xin Hao, Phee Lep Yeoh, Changyang She +2

This paper proposes a blockchain-secured deep reinforcement learning (BC-DRL) optimization framework for {data management and} resource allocation in decentralized {wireless mobile…