A Diagnostic and Performance System for Soccer: Technical Design and Development by Alberto Gascón, Álvaro Marco, David Buldain, Javier Alfaro-Santafé, Jose Victor Alfaro-Santafé, Antonio Gómez-Bernal, Roberto Casas

“…Results indicate high accuracy rates for detecting ball-striking events and CoDs, with improvements in algorithm performance achieved through adaptive thresholds and ensemble neural network models. …”
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A study on life assessment of metro cowcatcher based on multi-axis vibration environment reconstruction by ZHENG Yuhao, WU Xingwen, LIU Yang, CHI Maoru, LIANG Shulin

“…Then, the modal damping ratio was optimized by the genetic algorithm, improving the consistency between the simulation and measured response results, and proving the correctness of the modeling method. …”
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The integration of artificial intelligence in assisted reproduction: a comprehensive review by Pragati Kakkar, Shruti Gupta, Kasmiria Ioanna Paschopoulou, Ilias Paschopoulos, Ioannis Paschopoulos, Vassiliki Siafaka, Orestis Tsonis

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Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

“…Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods.…”
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Seasonally Adaptive VMD-SSA-LSTM: A Hybrid Deep Learning Framework for High-Accuracy District Heating Load Forecasting by Yu Zhang, Keyong Hu, Lei Lu, Qingqing Yang, Min Fang

“…Subsequently, the SSA is utilized to optimize the hyperparameters of the LSTM network, with targeted adjustments made according to the seasonal characteristics of the heating load, enabling the identification of optimal configurations for each season. …”
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State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani Mustaffa, Mohd Herwan Sulaiman, Jeremiah Isuwa

“…This study proposes a novel approach for SoC estimation in BMW EVs by integrating a metaheuristic algorithm with deep neural networks. Specifically, teaching-learning based optimization (TLBO) is employed to optimize the weights and biases of the deep neural networks model, enhancing estimation accuracy. …”
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No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
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UAM Vertiport Network Design Considering Connectivity by Wentao Zhang, Taesung Hwang

“…To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. …”
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Modeling of Cloud-Edge Collaborated Electricity Market Considering Flexible Ramping Products Provided by VPPs by PENG Chaoyi, CHEN Wenzhe, XU Suyue, LI Jianshe, ZHOU Huafeng, GU Huijie, NIE Yongquan, SUN Haishun

“…The distributed optimization model is iteratively solved using the analytical target cascading (ATC) method, and heuristic constraints are introduced to improve the convergence of the algorithm. …”
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Application of supervised machine learning and unsupervised data compression models for pore pressure prediction employing drilling, petrophysical, and well log data by Abu Bakker Siddique, Tanveer Alam Munshi, Nazmul Islam Rakin, Mahamudul Hashan, Sushmita Sarker Chnapa, Labiba Nusrat Jahan

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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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LEO satellite constellation design with multi-QoS guarantee for non-terrestrial network by Ruyan WANG, Xianyi YE, Peng HE, Yaping CUI, Dapeng WU, Fedotov Alexander

“…LEO satellite constellation (LSC) offers seamless and fast connectivity for non-terrestrial network (NTN).However, the lack of QoS guarantees for users significantly impacts the performance of the NTN system.Considering multi-QoS metrics, a capacity and downlink budget model for LSC was established, and subsequently, the establishment of inter-satellite links was framed as a link budget issue for the QoS guarantee.The non-dominated sorting genetic algorithm (INSGA-II) with improved crossover and mutation operators was proposed to optimize LSC, aiming to maximize coverage and system capacity while minimizing constellation costs.The numerical results demonstrate that the designed LSC exhibits comparable or superior performance to Telesat and Kepler, and its scale is only 64% of the Kepler system.…”
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Microcontroller-Driven Battery Management in Hybrid Energy Systems: A Systematic Review of Applications, Control Strategies, and Emerging Trends by Ripfumelo Humphrey Malele, Bongumsa Mendu, Bessie Baakanyang Monchusi

“…Tools like Maximum Power Point Tracking (MPPT) and Pulse Width Modulation (PWM) help improve efficiency, while microcontrollers like Arduino and TMS320F28379D balance cost and performance depending on the project. …”
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Balancing line hardening, distributed generation and de-energization for wildfire risk mitigation with microgrid formation by Mengqi Yao, Shunbo Lei, Weimin Wu, Duncan S. Callaway

“…The objective is to balance the desire to enhance system resilience while minimizing the system upgrade cost against wildfires. An adopted column-and-constraint generation algorithm is developed to solve the model and obtain the optimal decisions. …”
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A State-of-the-Art Survey on Advanced Electromagnetic Design: A Machine-Learning Perspective by Masoud Salmani Arani, Reza Shahidi, Lihong Zhang

“…Research on electromagnetic (EM) components is essential to enabling the design and optimization of such devices as antennas and filters, leading to improved functionality, reduced costs, and enhanced overall performance. …”
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Recent Advances in Resistive Gas Sensors: Fundamentals, Material and Device Design, and Intelligent Applications by Peiqingfeng Wang, Shusheng Xu, Xuerong Shi, Jiaqing Zhu, Haichao Xiong, Huimin Wen

“…Machine learning (ML) algorithms have enabled intelligent design of novel sensing materials, optimized multi-gas identification, and enhanced data reliability in complex environments. …”
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Design of Dual-Channel Supply Chain Network Based on the Internet of Things Under Uncertainty by Hamed Nozari, Hossein Abdi, Agnieszka Szmelter-Jarosz, Seyyed Hesamoddin Motevalli

“…In this paper, a mathematical model of a dual-channel supply chain network (DCSCN) based on the Internet of Things (IoT) under uncertainty is presented, and its solution using algorithms based on artificial intelligence such as genetic algorithm (GA), particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and gray wolf optimizer (GWO). …”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. …”
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Random PWM Technique Based Two-State Markov Chain for Permanent Magnet Synchronous Motor Control by Zhiqiang Wang, Xinyuan Liu, Xuefeng Jin, Guozheng Zhang, Zhichen Lin

“…Secondly, to address the problem of insufficient random performance in the traditional RPWM technique, an innovative optimization scheme is proposed, i.e., the introduction of a two-state Markov chain and, based on the immune algorithm for transition probability and random gain, the optimization of two key parameters. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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