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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Hydropneumatic storage methodology towards a new era of hybrid energy system's efficiency and flexibility by JoaoS.T. Coelho, Modesto Pérez-Sánchez, Oscar E. Coronado-Hernández, Mohsen Besharat, Rui-Lin Feng, Elias Tasca, Ling Zhou, Helena M. Ramos

“…The optimization of hybrid systems through Solver and Python algorithms with various objective functions enables optimal design choices tailored to specific needs such as drinking water supply, irrigation, or industrial processes. …”
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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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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…These findings have meaningful clinical implications, offering a framework for more timely interventions, optimized resource allocation, and improved patient care in critical settings.…”
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THE USE OF QALY AS AN INTEGRAL MEASURE OF EFFECTIVENESS IN THE EVALUATION OF MEDICAL TECHNOLOGIES by N. Z. Musina, V. K. Fedyaeva

“…Its versatility enables better decision-making on financing the medical treatment within a limited budget. With this algorithm, the financial resources are allocated in such a way as to maximize the levels of QALY. …”
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Enhancing Triage Systems in Emergency Units: An Extensive Review by Dipankar Maiti, Tincy Mariam Easow, Jyothi R

“… Triage systems in emergency units play a crucial role in prioritizing patient care and optimizing resource allocation during mass casualty incidents or high-demand situations. …”
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A Dynamic Just-in-Time Component Delivery Framework for Off-Site Construction by Tongguang Si, Hong Xian Li, Zhen Lei, Hexu Liu, SangHyeok Han

“…Traditionally, both parties tend to rely on internal resources or third-party resources to manage schedule changes, paying little attention to the optimisation of the component delivery process. …”
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Excavation Safety Modeling Approach Using BIM and VPL by Numan Khan, Ahmad K. Ali, Miroslaw J. Skibniewski, Do Yeop Lee, Chansik Park

“…They have developed various algorithms to enhance safety in preconstruction phase such as automated generation of scaffolding and its potential risk analysis, checking BIM model for fall risks, and limited access zone allocation in wall masonry. …”
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Adaptive Real-Time Transmission in Large-Scale Satellite Networks Through Software-Defined-Networking-Based Domain Clustering and Random Linear Network Coding by Shangpeng Wang, Chenyuan Zhang, Yuchen Wu, Limin Liu, Jun Long

“…Experimental results indicate that the proposed method reduced resource allocation task execution time by at least 18.03% compared to traditional methods and enhanced task scheduling efficiency by at least 14.01%. …”
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Predicting Emergency Severity Index (ESI) level, hospital admission, and admitting ward in an emergency department using data-driven machine learning by Steve Agius, Vincent Cassar, Caroline Magri, Wasiq Khan, Dhiya Al-Jumeily Obe, Godwin Caruana, Luke Topham

“…Discussion The integration of early predictions into ED workflows has the potential to improve patient flow, reduce wait times, and enhance resource allocation. By leveraging XGBoost’s capabilities and integrating both demographic and clinical data, this study provides a robust framework for advancing decision-making processes in triage environments. …”
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Analyzing cropland fragmentation evolution and driving mechanisms in Shandong through MSPA and landscape metrics integration by Tianwei Zhang, Wei Li, Zengfeng Zhao, Meizhen Bi, Yi Zheng

“…Abstract As the foundational and core resource for agricultural development, arable land plays a critical role in optimizing regional agricultural resource allocation and ensuring food security. …”
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