A Reputation Value-Based Task-Sharing Strategy in Opportunistic Complex Social Networks by Jia Wu, Fangfang Gou, Wangping Xiong, Xian Zhou

“…The model consists of a task-sharing decision model that integrates latency and energy consumption, and a reputation value-based model for the allocation of the computational resource game. The two submodels apply an improved particle swarm algorithm and a Lagrange multiplier, respectively. …”
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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Early and accurate prediction of acute kidney injury (AKI), disease severity, renal replacement therapy (RRT) requirements, and mortality risk is essential for timely identification of high-risk individuals, personalized treatment planning, and optimal allocation of healthcare resources. We aimed to develop and externally validate an interpretable multi-task machine learning (ML) model to predict four clinical outcomes in patients with rhabdomyolysis: AKI, disease severity, the need for RRT, and in-hospital mortality. …”
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Optimal QoM in Multichannel Wireless Networks Based on MQICA by Na Xia, Lina Xu, Chengchun Ni

“…In this paper, a Multiple-Quantum-Immune-Clone-Algorithm- (MQICA-) based solution was proposed to achieve the optimal channel allocation. …”
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Security-driven service caching and computation offloading strategy in air-ground collaborative edge computing networks by WU Mengru, KONG Yawei, HAN Huimei, LU Haiquan, SI Peiyuan, LU Weidang, GUO Lei

“…Considering dual secrecy rate constraints and resource limitations suffered by a UAV server, UAV service caching, computation offloading decisions of ground devices, resource allocation, and UAV deployment were jointly optimized to minimize the task completion delay of ground devices. …”
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Joint Caching and Computation in UAV-Assisted Vehicle Networks via Multi-Agent Deep Reinforcement Learning by Yuhua Wu, Yuchao Huang, Ziyou Wang, Changming Xu

“…This requires balancing system energy consumption and resource allocation fairness while maximizing cache hit rate and minimizing task latency. …”
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Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

“…When multi-scenario services coexist in the 5G networks, exploring optimized resource scheduling and allocation strategies become a critical issue. …”
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IntelliGrid AI: A Blockchain and Deep-Learning Framework for Optimized Home Energy Management with V2H and H2V Integration by Sami Binyamin, Sami Ben Slama

“…The core of IntelliGrid AI is an advanced Q-learning algorithm that intelligently allocates energy resources. …”
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Gemini: A Cascaded Dual-Agent DRL Framework for Task Chain Planning in UAV-UGV Collaborative Disaster Rescue by Mengxuan Wen, Yunxiao Guo, Changhao Qiu, Bangbang Ren, Mengmeng Zhang, Xueshan Luo

“…Specifically, this framework comprises a chain selection agent and a resource allocation agent: The chain selection agent plans paths for task chains, and the resource allocation agent distributes platform loads along generated paths. …”
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Security performance analysis for cell-free massive multiple-input multiple-output system with multi-antenna access points deployment in presence of active eavesdropping by Xiaoyu Wang, Yuanyuan Gao, Guangna Zhang, Mingxi Guo, Kui Xu

“…Compared to equal power allocation, the proposed power control algorithm can further boost the network security performance.…”
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Optimization, Design, and Implementation of Biodiversity-Focused Fisheries Survey Stations: A Case Study of the Coastal Waters of Maoming by Yuexiu DENG, Yongheng HUANG, Jianyu DONG, Ning CHEN, Jing ZHANG, Xuefeng WANG

“…This package, based on a genetic algorithm, can determine the optimal stratification, sample size, and sample allocation to meet precision constraints in the presence of multiple stratification variables and multiple target variables. …”
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The methodology for calculating the number of teaching staff using economically feasible norms by L. A. Krokhmal, Yu. A. Kovshun

“…It has been established that the planned number of teaching staff is lower than the planned staffing level, calculated based on the volume of contact work hours, which makes it possible to encourage universities to restructure their curricula without going beyond funding limits.Conclusons and Relevance:the proposed approach allowed to conduct the calculation of teaching staff in accordance with the curriculum with a standardized volume of financial resources allocated to finance the remuneration of teaching staff of a specific educational program. …”
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NOMA-based secure computation offloading in marine Internet of things by JIANG Wei, YUAN Xiao, WANG Qian, QIAN Liping

“…Considering the requirements such as energy constraints and security transmission, the offloading ratio, transmitting power, computation resource allocation and NOMA cluster selection were jointly optimized with the objective of minimizing the maximum task processing latency. …”
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Constrained Restless Bandits for Dynamic Scheduling in Cyber-Physical Systems by Kesav Ram Kaza, Rahul H. Meshram, Varunkumar Mehta, Shabbir N. Merchant

“…CRMABs can be applied to resource allocation problems in cyber-physical systems, including sensor/relay scheduling. …”
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Optimizing sum rates in IoT networks: A novel IRS-NOMA cooperative system by Mukkara Prasanna Kumar, Ammar Summaq, Sunil Chinnadurai, Poongundran Selvaprabhu, Vinoth Babu Kumaravelu, Md. Abdul Latif Sarker, Dong Seog Han

“…By leveraging our optimization algorithm, the proposed system ensures efficient resource allocation, achieving superior spectral efficiency and fairness among users compared to traditional models. …”
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Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

“…Simulation results demonstrate that the U-FRQL-EA algorithm effectively reduces the system’s bit error rate, enhances communication quality, and optimizes network resource utilization, offering a novel solution for improving the performance of uncrewed aerial vehicle communication systems.…”
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Deep Reinforcement Learning-Based Two-Phase Hybrid Optimization for Scheduling Agile Earth Observation Satellites by Guanghui Zhou, Zhicheng Jin, Dongning Liu

“…To mitigate problem complexity, the action space is decomposed into two interdependent decision layers: task sequencing and resource allocation. Given the resource occupation constraints during action execution, a novel reward function is designed by integrating resource occupation utility into the immediate reward mechanism. …”
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Incorporating Contextual Factors into a Comprehensive Analysis of Operational Efficiency and Service Quality in Healthcare Sector by Utsav Pandey, Sanjeet Singh

“…In the first stage, an output-oriented Data Envelopment Analysis is employed to model the interdependency between operational efficiency and service quality by assessing the allocation of the input resources for achieving these two objectives. …”
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Bit Rate Optimization with MMSE Detector for Multicast LP-OFDM Systems by Ali Maiga, Jean-Yves Baudais, Jean-François Hélard

“…We propose a new resource allocation algorithm with minimum mean square error (MMSE) detector for multicast linear precoded orthogonal frequency division multiplexing (LP-OFDM) systems. …”
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Study on multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning by Xiaojin DING, Yehui XU, Wen BAO, Gengxin ZHANG

“…To solve the problem of the weak spectrum-cognitive ability caused by monitoring angle, direction resolution, limited processing ability and peak power for a low-earth-orbit (LEO) satellite, a multi-satellite cooperative spectrum cognitive method integrating Stackelberg game and federated learning was proposed.Firstly, considering the available computing resource, cognitive performance, processing and transmission delay of each spectrum cognitive satellite, a cooperative-satellite selection and computing-resource allocation algorithm was built for multiple spectrum-cognitive tasks.Secondly, based on the selected satellites and the allocated computing resources, a low-complexity multi-satellite cooperative spectrum cognitive strategy was further designed, which could automatically sense the spectrum holes, and detect interference as well as identify the modulation mode.Simulation results demonstrate that compared to the single-node cognitive method, the designed multi-satellite cooperative spectrum cognitive strategy can obtain a better cognitive performance.Moreover, comparing with the existing model, the model utilized in the designed strategy can effectively achieve 96.69% and 93.32% lower number of parameters and required floating point operations per second, whilst maintaining the performance.…”
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Using random subcarrier weighting for multi-carrier systems physical layer security by Zhou ZHONG, Liang JIN, Kai-zhi HUANG

“…An OFDM security model and a physical layer security transmission scheme were proposed for multi-carrier systems to achieve low probability of interception.In contrast to the resource allocation algorithm which would be disabled at the low SNR,this method designed the subcarrier transmission weighting vectors to randomize the eavesdropper’s signals but not the authorized receiver’s signals.The channel state information was the only character to distinguish authorized receivers and eavesdroppers,which was conducted to guide the weighting vectors design.Simulation results show that the proposed method guarantees that authorized receiver performs transmitted reference demodulation successfully,while the eavesdroppers can not detect the transmitted symbols.…”
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