Underwater Acoustic MAC Protocol for Multi-Objective Optimization Based on Multi-Agent Reinforcement Learning by Jinfang Jiang, Yiling Dong, Guangjie Han, Gang Su

“…MOMA-MAC utilizes a delay reward mechanism combined with the Multi-agent Proximal Policy Optimization Algorithm (MAPPO) to design a dual reward mechanism, which enables agents to adaptively collaborate and compete to optimize the use of network resources. …”
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The role of artificial intelligence in enhancing disaster preparedness and trauma care by Mohamad Sorani

“…This review examines the various applications of AI in forecasting disaster events, optimizing resource allocation, facilitating real-time monitoring, and improving communication among all stakeholders involved.The influence of AI on trauma care is equally significant, with advanced technologies enhancing patient triage, diagnostics, and surgical assistance, particularly in high-pressure situations. …”
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Integrating Social Determinants of Health in Machine Learning–Driven Decision Support for Diabetes Case Management: Protocol for a Sequential Mixed Methods Study by Seung-Yup Lee, Leslie W Hayes, Bunyamin Ozaydin, Steven Howard, Alison M Garretson, Heather M Bradley, Andrew M Land, Erin W DeLaney, Amy O Pritchett, Amanda L Furr, Ashleigh Allgood, Matthew C Wyatt, Allyson G Hall, Jane C Banaszak-Holl

“…By taking a mixed methods approach, we aim to align the model with the hospital’s specific quality and patient safety considerations for the quality of patient care and the optimization of case management resource allocation. International Registered Report Identifier (IRRID)DERR1-10.2196/56049…”
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AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women by Li Ma, Li Ma, Ru Chen, Weigong Ge, Paul Rogers, Beverly Lyn-Cook, Huixiao Hong, Weida Tong, Ningning Wu, Wen Zou

“…Our findings indicated that AI algorithms could augment both traditional and contemporary topic modeling techniques. …”
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Runoff Prediction and Uncertainty Analysis for Xijiang River Basin Based on CMIP6 Climate Scenarios by WU Huiming, YAN Meng, ZHOU Shuai

“…Additionally, the successfully built XAJ model is then driven by the data, and indicators such as the coefficient of variation and relative runoff changes are adopted to reveal the characteristics of future water resource variability in the basin. …”
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Research on strategies for enhancing drug knowledge dissemination on Chinese social media WeChat public accounts based on text mining technology by Xihui Yu, Xiaotong Chen, Xia Yan, Xuejun Wu, Yizhi Zhang, Xiajiong Luo, Weihao Ma, Hongbo Fu, Yaofeng Zhang

“…It provides references for science popularization workers, so that science popularization can play a better role in improving the public’s knowledge of medication safety.MethodsTaking the well-known pharmaceutical science popularization WeChat account “PSM Medicine Shield Public Welfare” as an example, we combined the Term Frequency-Inverse Document Frequency (TF-IDF) algorithm and VOSviewer visualization analysis technology to construct a hot topic analysis model for pharmaceutical science popularization articles, and analyzed the common rules and characteristics of successful hot articles. …”
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Study on Optimal Decision of Unit Commitment with Flexible Reserve Participation in Power Grid by ZHOU Yi, LI Yichen, FU Youshu, QIN Kangping, ZHU Wen, FAN Dongqi

“…Secondly, a unit combination model considering the flexible reserve is established with the objective function of minimizing the total operating cost of the system, and the optimization algorithm program is written in the Lingo environment to optimize a variety of reserve resources. …”
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Integration of Accelerometers and Machine Learning with BIM for Railway Tight- and Wide-Gauge Detection by Jessada Sresakoolchai, Chayutpong Manakul, Ni-Asri Cheputeh

“…BIM’s capabilities allow for the precise mapping of tight- and wide-gauge locations, streamlining maintenance workflows and resource allocation. Results demonstrate high accuracy in detecting and predicting tight and wide gauges, emphasizing the reliability of machine-learning models when coupled with accelerometer data. …”
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Urban Air Mobility Vertiport’s Capacity Simulation and Analysis by Antoni Kopyt, Sebastian Dylicki

“…By examining the interplay between infrastructure design, operational workflows, and resource allocation, the research provides a versatile tool for urban planners and policymakers to optimize vertiport layouts and traffic management protocols. …”
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Intelligent monitoring and control of farmland based on edge-cloud collaboration and digital twin for digital energy management: investment benefit analysis by Zheng Liu

“…Edge-cloud collaborative architecture for real-time data collection/analysis, reducing network latency by 40% compared to traditional cloud-only models; deep reinforcement learning (DRL)-driven irrigation optimization, achieving 51% crop yield increase and 18% water efficiency improvement; digital twin modeling of photovoltaic-energy storage systems, enhancing energy flow prediction accuracy to 98.2% and reducing energy waste by 9.5%; game theory-based resource allocation to balance energy supply–demand, improving system economic benefits by 15%. …”
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Challenges and Applications of Artificial Intelligence in Education: A Systematic Review by Saeid Arifnejad, Asadolah khadivi, Farhad Alipour

“…Additionally, it facilitates efficient teaching methodologies, automates grading and assessment, and optimizes resource allocation. The integration of AI can significantly improve the quality of education.Value: This research contributes to bridging the knowledge gap regarding AI applications in education while identifying key challenges for educators and policymakers.…”
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An Efficient Evolutionary Task Scheduling/Binding Framework for Reconfigurable Systems by A. Al-Wattar, S. Areibi, G. Grewal

“…An efficient reconfigurable platform is implemented along with novel placement/scheduling algorithms. The proposed algorithms tend to reuse hardware tasks to reduce reconfiguration overhead, migrate tasks between software and hardware to efficiently utilize resources, and reduce computation time. …”
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The Novel Heuristic for Data Transmission Dynamic Scheduling Problems by Hao Xu, Yue Zhao, Li-Ning Xing, You Zhou

“…The data transmission dynamic scheduling is a process that allocates the ground stations and available time windows to the data transmission tasks dynamically for improving the resource utilization. …”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…These innovations promise self-learning agents capable of automated spatial pattern recognition, real-time alerts, and optimized resource allocation. Despite progress, challenges persist in model selection, interpretability, and robustness. …”
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Reliable transmission mechanism with differentiated protection in virtualized fiber-wireless access network by Ruyan WANG, Yishuang GAO, Xiao CHEN

“…In view of the different reliability requirements of network service,a reliable transmission mechanism with differentiated protection was proposed in virtualized fiber-wireless access network.The quality of protection required by users and the fees that can be paid were used as a prerequisite.The backup protection resources were flexibly allocated by quantifying the multi-level protection quality with the probability of recovery.Then,for reducing traffic congestion and the unprotected services,the level service differentiation algorithm was used to choose protection link which was satisfied with the level of protection quality.The results show the proposed mechanism has more advantages in terms of long-term benefit-to-cost ratio and underlying network resource overhead,and provides users with a more flexible virtual network transmission while satisfying users’ reliability requirements.…”
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Efficient identification of maximum independent sets in stochastic multilayer graphs with learning automata by Mohammad Mehdi Daliri Khomami, Mohammad Reza Meybodi, Alireza Rezvanian

“…The identification of a maximum independent set -comprising nodes without direct connections- offers a significant understanding of phenomena such as information diffusion, resource allocation, and epidemic spread within complex social networks. …”
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Advancements in artificial intelligence transforming medical education: a comprehensive overview by Aliasghar Khakpaki

“…Conclusion: AI is an important tool in medical education, offering significant opportunities to enhance learning outcomes and bridge educational gaps. However, its successful integration requires ethical frameworks, faculty training, and equitable resource allocation. …”
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Climate risk and low-carbon policies: implications for sports economics and global events by Siyu Fu, Chen Kong

“…ICSF, on the other hand, leverages game theory and optimization algorithms to enhance decision-making in areas such as resource allocation, salary cap management, and sustainability-oriented strategic planning.ResultsEmpirical results from multiple datasets and experiments confirm that the integration of climate risk and low-carbon policy variables significantly improves the predictive accuracy and resilience of economic planning in the sports sector.DiscussionThis research provides theoretical advancements and practical insights for policymakers, sports managers, and investors seeking to navigate the complex interplay between sustainability and profitability in a rapidly changing global environment.…”
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Influence of Clinician-Related Factors on Adherence to the American Heart Association Guidelines for Acute Coronary Syndrome among Clinicians at Kenya Ports Authority clinics in Mo... by Mary Kavinya Mailu, Nilufa Jivraj Shariff, Ruth Mbugua

“…The study recommends enhancing resource allocation for ACS management, ensuring availability of essential medications and equipment, and developing simplified clinical algorithms to support guideline adherence. …”
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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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