Redefining Trauma Triage for Elderly Adults: Development of Age-Specific Guidelines for Improved Patient Outcomes Based on a Machine-Learning Algorithm by Ji Yeon Lim, Yongho Jee, Seong Gyu Choi, Yoon Hee Choi, Sam S. Torbati, Carl T. Berdahl, Sun Hwa Lee

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Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks by Nishant Gupta, Satyam Agarwal, Aymen Fakhreddine

“…In the second stage, we utilize the solution obtained in the first part and develop an interference-aware iterative scheme to jointly optimize user scheduling, resource allocation, and ABS placement. Given the non-convex nature of this problem, we employ the successive convex approximation technique to approximate the non-convex objectives and constraints. …”
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Enhancing Infotainment Services in Integrated Aerial–Ground Mobility Networks by Chenn-Jung Huang, Liang-Chun Chen, Yu-Sen Cheng, Ken-Wen Hu, Mei-En Jian

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Secure data offloading strategy for multi-UAV wireless networks based on minimum energy consumption by Gaofeng CUI, Yuanyuan XU, Shanghong ZHANG, Weidong WANG

“…To solve the problems of ground passive eavesdropping when ground users offload data to the multi-UAV(unmanned aerial vehicle) edge computing network, a secure data offloading strategy that minimized system energy consumption by jointly optimizing user matching and resource allocation was proposed.Considering the constraints of system delay, communication resources and computing resources, the probability of security interruption was used to restrict the security performance of the data offload process.By using block coordinate descent and successive convex approximation algorithm, the user transmission power, offload factor, UAV computing resource allocation and jamming power were jointly optimized.A pair-wise stable user matching algorithm was proposed to minimize the total energy consumption of UAV system.Simulation results demonstrate that the algorithm can realize the safe offloading of data, and has good performance in energy consumption and delay by comparing with the conventional strategies.…”
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Secure data offloading strategy for multi-UAV wireless networks based on minimum energy consumption by Gaofeng CUI, Yuanyuan XU, Shanghong ZHANG, Weidong WANG

“…To solve the problems of ground passive eavesdropping when ground users offload data to the multi-UAV(unmanned aerial vehicle) edge computing network, a secure data offloading strategy that minimized system energy consumption by jointly optimizing user matching and resource allocation was proposed.Considering the constraints of system delay, communication resources and computing resources, the probability of security interruption was used to restrict the security performance of the data offload process.By using block coordinate descent and successive convex approximation algorithm, the user transmission power, offload factor, UAV computing resource allocation and jamming power were jointly optimized.A pair-wise stable user matching algorithm was proposed to minimize the total energy consumption of UAV system.Simulation results demonstrate that the algorithm can realize the safe offloading of data, and has good performance in energy consumption and delay by comparing with the conventional strategies.…”
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Optimizing Pharmaceutical Inventory and Investment Strategies During Pandemics: A Dynamic Approach Integrating Environmental Emission Rates and Advanced Optimization Algorithms by Vinita Dwivedi, Mamta Keswani, Uttam Kumar Khedlekar, Lalji Kumar

“…Optimal control theory is applied for dynamic investment adjustments, enhancing resource allocations and decision-making. The study addresses a complex replenishment problem involving joint pricing, environmental costs, order costs, preservation technology, and replenishment schedules for non-instantaneous deteriorating items, aiming to maximize retailer's profit. …”
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Methods for Cognitive Diagnosis of Students’ Abilities Based on Keystroke Features by Xu Chi, Xinyu Guo, Yu Sheng

“…This provides strong support for the formulation of teaching strategies and the allocation of resources, and the method possesses important application value and practical significance.…”
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Secondary Frequency Control of Islanded Microgrid Based on Deep Reinforcement Learning by Li WANG, Yuxiang JIANG, Xiangjun ZENG, Bin ZHAO, Junhao LI

“…The frequency deviation is used as the state input variable, and the design of the state space, action space, reward function, neural network, and hyperparameters in the deep Q-Networks algorithm is carried out. The reward function balances the goals of frequency recovery and power allocation among distributed energy resources , ensuring consistency in action selection among the intelligent agents. …”
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Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

“…First, the net-load profile is decomposed by successive variational mode decomposition (SVMD) optimized with the Red-billed Blue Magpie Optimization (RBMO) algorithm to construct a flexibility demand model. …”
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A TRIZ-based algorithm for business model innovation in manufacturing SMEs: a systematic framework for strategic innovation integrated with the business model canvas by Juan G. Mejia-Duque, Andres Guerrero-Alvarado

“…A single-case study in a Colombian manufacturing SME demonstrated measurable improvements in resource allocation, cost efficiency, quality, customer engagement, and market opportunity identification, strengthening competitiveness and value creation. …”
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Energy management in autonomous hybrid electric vehicles: A review by Abid H., Kissaoui M., Raihani A., Zaggaf M.H.

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Predicting hospital outpatient volume using XGBoost: a machine learning approach by Lingling Zhou, Qin Zhu, Qian Chen, Ping Wang, Hao Huang

“…Abstract Hospital outpatient volume is influenced by a variety of factors, including environmental conditions and healthcare resource availability. Accurate prediction of outpatient demand can significantly enhance operational efficiency and optimize the allocation of medical resources. …”
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Load balancing method of service cluster based on mean-variance by Xiaoan BAO, Xue WEI, Lei CHEN, Guoheng HU, Na ZHANG

“…When a large number of concurrent requests are allocated,the load scheduling mechanism is to achieve the load balancing of nodes in the network by minimizing the response time and maximizing the utilization ratio of nodes.In the load balancing algorithm based on genetic algorithm,the fitness function is designed to have an important influence on the load balancing efficiency.A service cluster load balancing method based on mean-variance was proposed to optimize the fitness function.The investment portfolio selection model mean-variance was used to minimize the response time,which was used to get the weight of each server's resource utilization,so as to obtain the optimal allocation combination.This method improves the accuracy and efficiency of the fitness function.Compared with other models in different service environment,the simulation results show that the load balancing algorithm makes the service cluster get a better balance performance in terms of node utilization and response time.…”
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Particle Swarm Optimization Algorithm for Determining Global Optima of Investment Portfolio Weight Using Mean-Value-at-Risk Model in Banking Sector Stocks by Moh. Alfi Amal, Herlina Napitupulu, Sukono

“…The results of this study indicate that the adapted PSO algorithm successfully determines the optimal portfolio weight composition, calculates the expected return and VaR in the optimal portfolio, creates an efficient frontier surface graph, and establishes portfolio performance measures. …”
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A Novel Self-Configurable Algorithm for Uncoordinated Deployment of Home gNodeBs in 5^th Generation Wireless Networks by Madhusmita Panda, Saraju Prasad Padhy, Meetarani Swain

“…This is primarily due to allocation of resources in a timely and reliable manner. …”
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Internet of Things Based Application Placement Technique in Fog Environment by N Malathy, M Ruba, S Vinothini

“…Leveraging an Improved Memetic Algorithm (IMA), this strategy enables effective scheduling of parallel IoT workflows across fog and cloud servers, ensuring balanced resource utilization and enhanced scalability. …”
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A computation offloading scheme for energy consumption optimization in Internet of vehicles by Wenxuan GAO, Xinjie YANG

“…In Internet of vehicles (IoV), vehicle-oriented applications are generally computation-intensive and latency-sensitive.Introducing idle computing resources from mobile vehicles as a supplement to network computing power can effectively alleviate the load pressure on edge servers.The problem of task allocation for edge computation offloading in the context of IoV environment were researched.By fully leveraging the combined computing resources of roadside units (RSU), user vehicles, and mobile vehicles within the RSU service range, a computation offloading strategy based on the sparrow search algorithm was proposed and referred to as sparrow search based computation offloading scheme (S²COS), aiming to optimize the overall system energy consumption.In addition, this strategy fully taked into account practical network issues such as service time constraints caused by vehicle mobility and the potential occurrence of computation node failures.The simulation results demonstrate that S²COS can meet the latency requirements for computation-intensive and latency-sensitive tasks, while significantly reducing system energy consumption.…”
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A two-stage robust optimization for EV user-friendly VPP participation in ancillary service markets by Yu Wang, Xiangrui Tong, Yiheng Xie, Bing Chen, Ning Tong, Xiaomei Wu

“…The VPP ensures reserves to swiftly respond to market uncertainties. A power allocation strategy was implemented based on a consensus algorithm that takes into account the satisfaction level of EV users participating in ancillary services and the battery degradation cost. …”
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Scientific planning of dynamic crops in complex agricultural landscapes based on adaptive optimization hybrid SA-GA method by Changlong Li, Zengye Su, Yudan Nie, Zhiyi Ye, Jinyi Li, Jing Wang, Zicong Yang, Xuxin Li, Weijian Zeng, Yanjian Chen

“…This research establishes an integrated “monitoring-modelling-decision” paradigm, driven by multi-source data and machine learning, offering a practical and robust tool that provides valuable guidance for enhancing resource allocation efficiency and promoting sustainable precision agriculture in complex topographical regions, thereby holding significant reference value for optimising agricultural production nationwide.…”
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Asymptotic quadratic price game mechanism for video stream extensible feedback unloading by Qianqian GE

“…A progressive quadratic price game mechanism with scalable feedback offloading of video streams was proposed.Firstly,the congestion of cellular network could be alleviated by effectively uninstalling some video traffic from all video streaming services to Wi-Fi network,thus providing seamless video streaming services.Several physi-cal paths were integrated in an economical and efficient way.The fountain coded symbols of compressed video data were transmitted simultaneously through LTE and Wi-Fi network to flexibly control the viewing through Wi-Fi net-work and reduce the video quality degradation caused by wireless channel errors.Secondly,a progressive secondary price auction mechanism was used to allocate limited LTE resources to multiple user devices to maximize social wel-fare and achieve Nash equilibrium.The scalability and convergence of the system were verified theoretically.Finally,the performance advantages of the proposed algorithm in video streaming transmission quality and energy consump-tion were verified by experimental simulation.…”
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