Optimizing integration techniques for UAS and satellite image data in precision agriculture — a review by Aliasghar Bazrafkan, C. Igathinathane, Nonoy Bandillo, Paulo Flores

“…Integrated UAS and satellite data impact precision agriculture, contributing to improved resolution, monitoring capabilities, resource allocation, and crop performance evaluation. …”
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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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Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

“…To address the issues of ineffective task offloading decisions caused by multitasking and resource constraints in vehicular networks, the Quasi-Newton method deep reinforcement learning dual-phase online offloading (QNRLO) algorithm was proposed. …”
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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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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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Interference Mitigation in mmWave Heterogeneous Cloud-Radio Access Network: For Better Performance and User Connectivity by Najwan M. Swadi, Firas A. Sabir, Hamed S. Al-Raweshidy

“…It integrates User-RRH associations to mitigate interference, enhance network throughput (via Heuristic Algorithm) and RRH-BBU clustering (via k-means) to manage resources in the network. …”
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Task Scheduling in Cloud Environment–Techniques, Applications, and Tools: A Systematic Literature Review by Olanrewaju L. Abraham, Md Asri Bin Ngadi, Johan Bin Mohamad Sharif, Mohd Kufaisal Mohd Sidik

“…Cloud computing has become a revolutionary model for providing computational resources and services via the internet. As the volume of tasks and the dynamic nature of cloud resources increase, several critical challenges emerge, including load balancing, resource utilization, task allocation, and system performance. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…By integrating AI into Nigeria’s public health infrastructure, early detection and response can be improved, resource allocation optimized, and disease transmission minimized. …”
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User Handover Aware Hierarchical Federated Learning for Open RAN-Based Next-Generation Mobile Networks by Amardip Kumar Singh, Kim Khoa Nguyen

“…To address these challenges, we propose MHORANFed, a novel optimization algorithm tailored to minimize learning time and resource usage costs while preserving model performance within a mobility-aware hierarchical FL framework for O-RAN. …”
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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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Context-Aware Beam Selection for IRS-Assisted mmWave V2I Communications by Ricardo Suarez del Valle, Abdulkadir Kose, Haeyoung Lee

“…This approach enables optimized resource allocation and significantly improves coverage, data rate, and resource utilization compared to conventional methods.…”
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Distributed Optimization for Mobile Robots under Mobile Edge Computing Environment by Hui Luo, Quan Yin

“…The mmW base station provides reliable communication services for MRs under the coverage of information cloud (IC). We design a joint resource and power allocation strategy aimed at minimizing network energy consumption. …”
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A Machine Learning Approach for Quantifying Academic Misconduct by Almasi S. Maguya

“…To deal with this problem effec tively, a clear understanding of its magnitude is necessary for planning and resource allocation. This paper proposes a machine learning algorithm to quantify the mag nitude of academic misconduct among undergraduate students. …”
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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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Genomic selection optimization in blueberry: Data‐driven methods for marker and training population design by Paul Adunola, Luis Felipe V. Ferrão, Juliana Benevenuto, Camila F. Azevedo, Patricio R. Munoz

“…Our contribution in this study is threefold: (i) for the genotyping resource allocation, the use of genetic data‐driven methods to select an optimal set of markers slightly improved prediction results for all the traits; (ii) for the long‐term implication, we carried out a simulation study and emphasized that data‐driven method results in a slight improvement in genetic gain over 30 cycles than random marker sampling; and (iii) for the phenotyping resource allocation, we compared different optimization algorithms to select training population, showing that it can be leveraged to increase predictive performances. …”
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Pulse Sequence Division in Mixed Signal Flow by V. F. Korotkov, R. S. Zyryanov

“…Based on the classification improved algorithm for the allocation sequence is developed. …”
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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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A multi objective optimization framework for smart parking using digital twin pareto front MDP and PSO for smart cities by Dinesh Sahu, Priyanshu Sinha, Shiv Prakash, Tiansheng Yang, Rajkumar Singh Rathore, Lu Wang

“…Evaluation outcomes also show that the proposed algorithm is better than Round Robin, Random Allocation, and Threshold Based algorithms in terms of 25% improvement in the search time, 18% better energy usage, and 30% less traffic congestion. …”
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Chemical Properties of Heterogenous Catalysts in Improving Yield of Biofuel Production by Qian Yanfei

“…It systematically optimizes hub layouts, flexible resource allocation, and dynamic control by employing spatial topology algorithms, multi-agent game models, and digital twin technology.A three-tier toolkit comprising “model classification,” “algorithm adaptation,” and “scenario application” has been developed to address issues such as facility layout mismatches, inefficient resource scheduling, and limited resilience to sudden surges in passenger flow.Empirical evidence indicates that, following optimization, the distance between subway and bus connections is reduced to 150 meters, decreasing transfer time by 40%. …”
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