Estimation of sugarcane biomass from Sentinel-2 leaf area index using an improved SAFY model (SAFY-Sugar) by Jingyuan Xu, Xin Du, Taifeng Dong, Qiangzi Li, Yuan Zhang, Hongyan Wang, Miao Liu, Jiong Zhu, Jian Yang

“…SAFY employed a fixed biomass allocation coefficient for stalk biomass estimation. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What’s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…As a result, the efficient allocation of public security resources based on spatio-temporal crime prediction models has become a critical concern for urban management. …”
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METHODOLOGICAL APPROACHES TO THE DEVELOPMENT OF MECHANISMS FOR THE SYSTEM INTEGRATION OF AGRICULTURAL, PROCESSING AND MARKETING ENTERPRISES by Anna Aleksandrovna LEKSINA

“…This is a three-stage structured algorithm for constructing elements of functional, informational, organizational and resource subsystems and the relationships between them. …”
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Mobile operation and maintenance system of electric power communication access network based on IoT technology by Haiming JIANG, Danni XIA, Yuan LIU, Shiwen ZHAO, Lin FEI, Jingyu REN

“…The mobile operation and maintenance system of electric power communication access network was designed.In this developed system,the technology with intelligent identification of internet of things and data real-time transmission was introduced to the on-site operation and maintenance standardization management of the power communication network.First of all,the mobile operation and maintenance system architecture was built to realize the informatization of on-site operation and maintenance.And then,the TOPSIS algorithm was utilized to allocate the worksheet automatically,which improved the efficiency of fault processing.Besides,by real-time monitoring the site through the system,the intelligent management of the power communication access network was realized.The test results show that the operational management system is able to realize resources unified management,fault intelligent analysis,informatization support of on-site operations management,and also greatly enhance the intelligent operation and management level of power communication access network.…”
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GSF-YOLOv8: A Novel Approach for Fire Detection Using Gather-Distribute Mechanism and SimAM Attention by Caixiong Li, Dali Wu, Xing Zhang, Peng Wu

“…To address the current challenges in fire detection algorithms, including insufficient feature extraction, high computational complexity, limited deployment on resource-constrained devices, missed detections, false detections, and low accuracy, we developed a high-precision algorithm named GSF-YOLOv8. …”
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Augmented robustness in home demand prediction: Integrating statistical loss function with enhanced cross-validation in machine learning hyperparameter optimisation by Banafshe Parizad, Ali Jamali, Hamid Khayyam

“…Sustainable forecasting of home energy demand (SFHED) is crucial for promoting energy efficiency, minimizing environmental impact, and optimizing resource allocation. Machine learning (ML) supports SFHED by identifying patterns and forecasting demand. …”
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The impacts of specific place visitations on theft patterns: a case study in Greater London, UK by Tongxin Chen, Kate Bowers, Tao Cheng

“…Abstract Exploring the impacts of population place visitation on crime patterns is crucial for understanding crime mechanisms and optimising resource allocation in crime prevention. While recent studies have broadly examined dynamic population activities at specific places from geo big data, limited crime-related studies have utilised this measurement to disentangle the impact of specific place visitation on urban crime patterns. …”
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Bilevel Programming Model of Urban Public Transport Network under Fairness Constraints by Jingjing Hao, Xinquan Liu, Xiaojing Shen, Nana Feng

“…The results showed that (1) the travel cost deprivation coefficient of the three groups declined from 33.42 to 26.51, with a decrease of 20.68%; the Gini coefficient of the road area declined from 0.248 to 0.030, with a decrease of 87.76%; it could be seen that the transportation equity feeling of low-income groups and objective resource allocation improved significantly; (2) before the optimization of public transport network, the sharing rate of cars, buses, and bicycles was 42%, 47%, and 11%, respectively; after the optimization, the sharing rate of each mode was 7%, 82%, and 11%, respectively. …”
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Performance Assessment of a Rehabilitation Transportation Reservation Matching Service with Market Design Mechanisms by Chen Yu Lan, Chih Peng Chu, Cheng Chieh (Frank) Chen

“…This study applies the market design theory to match the rehabilitation buses with the requests of patients, so as to improve resource utilization efficiency in rural areas. The developed market design mechanisms aim to allocate resources to those who need them most in a matching manner, by using the deferred acceptance algorithm and the top trading cycle approach. …”
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A Game Theoretical Priority-Aware R2V Task Offloading Framework for Vehicular Fog Networks by Kinda Khawam, Maurice Khabbaz, Joe Saad

“…The first level utilizes a two-stage Stackelberg game to incentivize vehicles within RSU coverage to allocate a portion of their computing resources. The second level focuses on task assignment to participating vehicles. …”
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Optimizing Energy Efficiency in Cloud Data Centers: A Reinforcement Learning-Based Virtual Machine Placement Strategy by Abdelhadi Amahrouch, Youssef Saadi, Said El Kafhali

“…The proposed method, RLVMP, classifies VMs as sensitive or insensitive and dynamically allocates resources to minimize energy consumption while ensuring compliance with service level agreements (SLAs). …”
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Coalition Game-Based Reinforcement Learning in Underwater Acoustic Networks by Khouloud Gharsalli, Sameh Najeh, Thierry Le Pors, Leila Najjar, Pierre-Jean Bouvet, Hichem Besbes

“…The purpose of this work is to address the limitations of existing resource allocation strategies that rely on static optimization or centralized control, which lack scalability and adaptability in large, dynamic UWA networks. …”
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Optimization and benefit evaluation model of a cloud computing-based platform for power enterprises by Xueli Yin, Xuguang Zhang, Luyao Pei, Rong Hu, Kaihui Ye, Kangkang Cai

“…The model employs an improved lightweight genetic algorithm combined with an elastic resource allocation strategy to dynamically adapt to task changes across various operational scenarios. …”
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Research on multidimensional dynamic defense strategy for microservice based on deep reinforcement learning by Dacheng ZHOU, Hongchang CHEN, Weizhen HE, Guozhen CHENG, Hongchao HU

“…Aiming at the problem that it is hard for security defense strategies in cloud native to guarantee the quality of service under dynamic requests, a multidimensional dynamic defense strategy for microservice based on deep reinforcement learning, named D2RA strategy, was proposed to provide dynamic configuration schemes that ensure security defense performance and quality of service for microservices under dynamical requests.Firstly, based on the characteristics of multiple replicas and invocation chains of microservices, a microservices state graph was established to depict the maps between requests, system configuration and security performance, quality of service, and resource overhead of microservices.Secondly, the D2RA framework was designed and a dynamic strategy optimization algorithm based on deep Q-network was proposed for microservices to provide fast and optimal system configurations update scheme under dynamic requests.The simulation results show that D2RA effectively allocate resources under dynamic requests, and achieve 19.07% more defense effectiveness and 42.31% higher quality of service as compared to the existing methods.…”
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A Transmit Beamforming and Nulling Approach with Distributed Scheduling to Improve Cell Edge Throughput by Wendy C. Wong, Qinghua Li, Shilpa Talwar

“…First, cell edge users suffering from severe interferences are identified. Next, the RRM unit allocates resource to serving cell edge users only. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…To achieve maximum energy efficiency, we jointly optimized the UAV’s trajectory, velocity, communication beamforming, sensing beamforming, and power allocation. Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
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Predicting Neoplastic Polyp in Patients With Gallbladder Polyps Using Interpretable Machine Learning Models: Retrospective Cohort Study by Zhaobin He, Shengbiao Yang, Jianqiang Cao, Huijie Gao, Cheng Peng

“…Conclusions Our interpretable ML models accurately predict neoplastic polyps in GBP patients, providing guidance for treatment planning and resource allocation. The model's transparency fosters trust and understanding, empowering physicians to confidently use its predictions for improved patient care.…”
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Radiology AI and sustainability paradox: environmental, economic, and social dimensions by Burak Kocak, Andrea Ponsiglione, Valeria Romeo, Lorenzo Ugga, Merel Huisman, Renato Cuocolo

“…Socially, AI risks perpetuating healthcare disparities through biases in algorithms and unequal access to technology. On the other hand, AI has the potential to improve sustainability in healthcare by reducing low-value imaging, optimizing resource allocation, and improving energy efficiency in radiology departments. …”
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Enhancing Yield Estimation and Field Zoning Accuracy in Precision Agriculture Using Solar-Powered Drone-Based Remote Sensing by Abbas Haider Mohammed, Obaid Mohammed Kadhim, Vittalaiah A.

“…The system processes this data using advanced machine learning algorithms to forecast crop yields and generate detailed field zoning maps, enabling optimized resource allocation and improved farm management. …”
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A Multi-Objective Hybrid Game Pricing Strategy for Integrated Energy Operator-Load Aggregator Alliances Considering Integrated Demand Response by Yunlong Wang, Shan He

“…Secondly, to achieve cooperation between load aggregators, we use Nash bargaining theory to decompose the cooperative game model into two subproblems: maximizing alliance benefits and allocating cooperation benefits. Finally, we use the Alternative Direction Method of Multipliers (ADMM) algorithm combined with dichotomy and compromise programming theory to solve the model, to maximize the interests of all parties in the continuous interaction process. …”
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