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

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Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

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Program Scheduling With Multi-Skill and External Resource Coordination Consideration Using Improved NSGA-II: Case Study by Heng Zhang, Jingbo Zhou, Huaying Ruan, Yixuan Qin

“…Technology-driven startups often experience fluctuations in business volume and their delivery peak exceeds the conventional functional department’s human resource staffing. Resource allocation is crucial for ensuring timely completion of project deliverables within resource constraints. …”
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New design paradigm for federated edge learning towards 6G:task-oriented resource management strategies by Zhiqin WANG, Jiamo JIANG, Peixi LIU, Xiaowen CAO, Yang LI, Kaifeng HAN, Ying DU, Guangxu ZHU

“…Methods: Using the federated learning network architecture, this paper analyzes the resource allocation and user scheduling schemes: 1. …”
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Adaptive MCS selection and resource planning for energy-efficient communication in LTE-M based IoT sensing platform. by Nhu-Ngoc Dao, Minho Park, Joongheon Kim, Sungrae Cho

“…The proposed algorithm determines the optimal pair of MCS and the number of primary resource blocks (#PRBs), at which the transport block size is sufficient to packetize the sensing data within the minimum transmit power. …”
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Adaptive Resource Optimization for IoT-Enabled Disaster-Resilient Non-Terrestrial Networks using Deep Reinforcement Learning by Fathe Jeribi, R. John Martin

“…The dynamic nature of NTNs makes static resource allocation insufficient, necessitating adaptive strategies to address varying demands and environmental conditions during disaster management. …”
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Shared carrier vertical network transformation algorithm in heterogeneous wireless networks by Liang ZHAO, Liang JIN, Kai-zhi HUANG, Mei-yue YANG

“…In order to enhance the spectrum efficiency in heterogeneous wireless networks,the idea of dynamic spectrum allocation (DSA) used in cognitive radio was introduced into the heterogeneous wireless networks,the idea of vertical handoff for multi-mode mobile users was introduced into the base station side,thereafter,the shared carrier vertical network transformation (SCVNT) algorithm in heterogeneous wireless networks was proposed.The theoretical analysis and simulation results show that SCVNT algorithm can effectively enhance the total channel efficiency in heterogeneous wireless networks,improve fairness in resource allocation,and will be able to achieve smooth upgrade,which is of a relatively high application value.…”
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Large Language Model-Guided SARSA Algorithm for Dynamic Task Scheduling in Cloud Computing by Bhargavi Krishnamurthy, Sajjan G. Shiva

“…Potential challenges arise with respect to task scheduling, load balancing, resource allocation, governance, compliance, migration, data loss, and lack of resources. …”
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Multi-dimensional flux balance analysis to optimized resources and energy efficiency in MEC aided 5G networks by Rachit Patel, Rajeev Arya

“…In comparison to (1) Resource allocations using Q learning with considering parameter throughput-RA(QL-Munkres-TH), (2) Resource allocations using Q learning with considering parameter distance-RA(QL-Munkres-Dist), and (3) Resource allocation with considering maximum power-RA(Max-Power), the suggested method reduces energy consumption by 83.26%, 86.01%, and 88.34%, respectively. …”
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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…EdgeGuard uses edge computing to improve system scalability and efficiency by offloading computational tasks from IoMT devices with limited resources. We have made several technological advances, including a lightweight blockchain consensus mechanism designed for IoMT networks, an adaptive edge resource allocation method based on reinforcement learning, and a federated learning algorithm optimized for medical data with differential privacy. …”
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Optimizing energy and latency in edge computing through a Boltzmann driven Bayesian framework for adaptive resource scheduling by Dinesh Sahu, Nidhi, Rajnish Chaturvedi, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Idrees Alsolbi

“…Abstract This paper presents a new approach based on Boltzmann Distribution and Bayesian Optimization to solve the energy-efficient resource allocation in edge computing. It employs Bayesian Optimization to optimize the parameters iteratively for the minimum energy consumption and latency. …”
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Optimal energy management for multi-energy microgrids using hybrid solutions to address renewable energy source uncertainty by M. Siva Ramkumar, Jaganathan Subramani, M. Sivaramkrishnan, Arunkumar Munimathan, Goh Kah Ong Michael, Mohammad Mukhtar Alam

“…Abstract Research in industrial grid energy management is essential due to increasing energy demands, rising costs, and the integration of renewable sources. Efficient energy management can reduce operational costs, enhance grid stability, and optimize resource allocation. …”
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Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area by Jinxi Zhang, Saidiwaerdi Maimaiti, Weidong Gao, Kaisa Zhang

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Synchronous Remote Calibration for Electricity Meters: Application and Optimization by Zhiyong Zha, Hanfang Ge, Chengcheng Zou, Fei Long, Xingfeng He, Geng Wu, Chenxi Dong, Tianping Deng, Jiaxiang Xu

“…It addresses the challenge of resource allocation for synchronous calibration across distributed nodes by introducing a hybrid genetic algorithm that optimises scheduling and resource management. …”
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A new method of task aggregation and optimization allocation for multiple groups collaborative task networks by WeiWei Du, XiaoWei Chen

“…Finally, an adaptive mechanism is introduced to optimize the genetic algorithm’s crossover and mutation strategies, proposing a new adaptive optimal allocation algorithm for multiple groups tasks. …”
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Review of Research on Artificial Intelligence-driven Joint Radar Communication by Xianmei WANG, Xiangbo LIU, Yuzheng REN, Yang LU, Haijun ZHANG

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Intelligent Priority-Aware Spectrum Access in 5G Vehicular IoT: A Reinforcement Learning Approach by Adeel Iqbal, Tahir Khurshaid, Yazdan Ahmad Qadri

“…RL-PASM dynamically allocates spectrum resources across three traffic classes: high-priority (HP), low-priority (LP), and best-effort (BE), utilizing reinforcement learning (RL). …”
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Research on intelligent energy management strategies for connected range-extended electric vehicles based on multi-source information by Xuewen Zhai, Hanwu Liu, Wencai Sun, Zihang Su

“…Abstract Reliance solely on vehicle-specific information, while neglecting multi-source information such as traffic flow and traffic light status, results in difficulties in optimizing energy allocation based on complex road conditions. …”
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Enhancing Uplink Communication in Wireless Powered Communication Networks Through Rate-Splitting Multiple Access and Joint Resource Optimization by Iqra Hameed, Mario R. Camana, Mohammad Abrar Shakil Sejan, Hyoung Kyu Song

“…However, their performance is often limited by interference in uplink communication and inefficient resource allocation. To address these challenges, we propose an RSMA-aided WPCN framework, which optimizes rate-splitting factors, power allocation, and time division to enhance spectral efficiency and user fairness. …”
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Distributed dynamic event-triggered time-varying resource management for microgrids via practical predefined-time multiagent methods by Tingting Zhou, Salah Laghrouche, Youcef Ait-Amirat

“…A novel TV resource management model is introduced, explicitly accounting for dynamic constraints and demand variations to ensure real-time resource allocation while effectively handling load fluctuations and renewable energy variability. …”
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