Advancing named entity recognition in interprofessional collaboration and education by Rui Zhang, Yifeng Shan, MengZhe Zhen

“…Each agent contributes dynamically to the collaborative process, adapting its knowledge, skills, and resources to optimize global utility while minimizing conflicts and enhancing synergy. …”
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Probing the Pitfalls: Understanding SVD’s Shortcomings in Language Model Compression by Сергей Александрович Плетенев

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Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir, Aiman Erbad, Bechir Hamdaoui, Samir Brahim Belhaouari, Mohsen Guizani, Thang X. Vu

“…Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. Extensive simulations show that our model outperforms competitive methods by around 29% in terms of latency and around 23% in terms of transmission power improvements while delivering results comparable to the traditional LDTP optimization solution by around 9% in terms of latency.…”
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New Design of Smooth PSO-IPF Navigator With Kinematic Constraints by Mahsa Mohaghegh, Hedieh Jafarpourdavatgar, Samaneh-Alsadat Saeedinia

“…Smooth path planning is crucial for mobile robots to ensure stable and efficient navigation, as it minimizes jerky movements and enhances overall performance Achieving this requires smooth collision-free paths. Partial Swarm Optimization (PSO) and Potential Field (PF) are notable path-planning techniques, however, they may struggle to produce smooth paths due to their inherent algorithms, potentially leading to suboptimal robot motion and increased energy consumption. …”
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Fast Task Scheduling With Model Predictive Control Integrating a Priority-Based Heuristic by Francesco Liberati, Manuel Donsante, Chiara Maria Francesca Cirino, Andrea Tortorelli

“…There are two main objectives. The algorithm shall suggest to the planning operators an optimized scheduling of the activities, i.e., one which minimizes the total completion time (the makespan), while satisfying all the applicable constraints. …”
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Enhancing Kidney Disease Diagnosis Using ACO-Based Feature Selection and Explainable AI Techniques by Abbas Jafar, Myungho Lee

“…The ant colony optimization method identified the most relevant feature subsets using a clinical dataset, reducing model complexity while preserving predictive accuracy. …”
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Smart Agile Prioritization and Clustering: An AI-Driven Approach for Requirements Prioritization by Aya M. Radwan, Manal A. Abdel-Fattah, Wael Mohamed

“…Feature fusion and dimensionality reduction using Uniform Manifold Approximation and Projection (UMAP) facilitate clustering, while Particle Swarm Optimization (PSO) determines the optimal number of clusters for efficient backlog prioritization. …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…The VRP with prioritized customers introduces additional complexity by requiring efficient routing while ensuring high-priority customers receive service within strict constraints. …”
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A machine learning approach to assess the climate change impacts on single and dual-axis tracking photovoltaic systems by Udit Mamodiya, Indra Kishor, Priyam Ganguly, Isha Mukherjee, Nithesh Naik

“…COMLAT’s reinforcement learning controller optimized tracking angles with sub-second latency while minimizing mechanical movement. …”
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Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications by Peiqingfeng Wang, Shusheng Xu, Xuerong Shi, Jiaqing Zhu, Haichao Xiong, Huimin Wen

“…Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. …”
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Learning Rate Tuner with Relative Adaptation (LRT-RA): Road to Sustainable Computing by Saptarshi Biswas, Sumagna Dey, Subhrapratim Nath

“…Optimizing learning rates (LRs) in deep learning (DL) has long been challenging. …”
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Estimation and Reduction of CO₂ Emissions From Fossil Fuel Power Plants in Bangladesh by Deepak Kumar Chowdhury, Nur Mohammad, Tanjim Mahmud, Md. Khaliluzzaman, Karl Andersson, Mohammad Shahadat Hossain

“…The paper presents Matpower Interior Point Solver (MIPS), and Dynamic Non-Linear Particle Swarm Optimization (DNPSO) algorithms to solve combined economic emission dispatch (CEED) to optimize generation dispatch and minimize emissions. …”
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Advancement in public health through machine learning: a narrative review of opportunities and ethical considerations by Sumit Singh Dhanda, Deepak Panwar, Chia-Chen Lin, Tarun Kumar Sharma, Deependra Rastogi, Shantanu Bindewari, Anand Singh, Yung-Hui Li, Neha Agarwal, Saurabh Agarwal

“…Ethically, this review surfaces critical issues, including algorithmic bias, data privacy concerns in mental health analytics, and the interpretability of black-box models used in outbreak surveillance. …”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…<i>langbianensis</i> forests, while GA-optimized machine learning models demonstrate excellent performance, providing strong support for regional-scale forest resource monitoring and carbon stock assessment.…”
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Evolutionary Game-Based Battery Scheduling: A Comparative Study for Prosumers in Smart Grids by Anas Karaki, Khaled Abedrabboh, Luluwah Al-Fagih

“…A novel decentralized evolutionary game theory (EGT) algorithm is introduced to enhance energy management while preserving privacy and scalability. …”
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Bridging the Gap Between Computational Efficiency and Segmentation Fidelity in Object-Based Image Analysis by Fernanda Pereira Leite Aguiar, Irenilza de Alencar Nääs, Marcelo Tsuguio Okano

“…Future work will explore dynamic parameter optimization and algorithm adaptability across diverse datasets to further refine its capabilities. …”
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Multi video stream collaborative adaptive offloading scheme based on equilibrium game theory by Shijun Yuan

“…Secondly, an adaptive task offloading algorithm based on game theory and Nash equilibrium is designed to achieve optimal node selection through offloading algorithm and weight allocation, minimizing the processing cost of the entire multi video stream system and balancing video stream computation latency and energy consumption; Finally, the simulation results show that the proposed scheme satisfies long-term MEC energy constraints while significantly outperforming existing benchmark research schemes in terms of cost performance.…”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. …”
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