Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…The algorithm filters out strategies that violate constraints by introducing a logarithmic barrier function. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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libBICOS – An Open Source GPU-Accelerated Library implementing BInary COrrespondence Search for 3D Reconstruction by C. Liebender, M. Bleier, A. Nüchter

“…Our GPU-accelerated implementation reduces the latency of disparity computation using 7MP images on modern hardware down to 20 milliseconds. Based on the algorithm introduced by Dietrich et al. (2019), we extend their approach by increasing the descriptor size while augmenting postprocessing to increase its applicability on other types of pattern projections. …”
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Intuition-guided Reinforcement Learning for Soft Tissue Manipulation with Unknown Constraints by Xian He, Shuai Zhang, Jian Chu, Tongyu Jia, Lantao Yu, Bo Ouyang

“…Successful simulation results confirmed that the proposed framework can manipulate the soft tissue while avoiding obstacles and adding new positional constraints. …”
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Enhanced Rapid Autofocus Back-Projection for PBSAR Based on the GEO Satellite by Te Zhao, Jun Wang, Zuhan Cheng, Ziqian Huang, Jiaqi Song

“…Conventional autofocusing algorithms operate under the assumption that measurement errors primarily perturb phase components while exerting negligible influence on signal envelopes. …”
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Identifying Coronal Mass Ejection Active Region Sources: An Automated Approach by Julio Hernandez Camero, Lucie M. Green, Alex Piñel Neparidze

“…We find that CME–flare association rates increase with flare intensity, aligning with previous studies. While our approach has limitations, such as focusing exclusively on SHARP regions and relying on a limited set of posteruptive signatures, it significantly reduces the time required for CME source identification while providing transparent, reproducible results. …”
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Scenario-Based Association Rule Mining in Veterinary Services Using FP-Growth: Differentiating Clinical and Customer-Driven Patterns by Rafi Dio, Aulia Agung Dermawan, Dwila Sempi Yusiani, Rifaldi Herikson, Andikha Andikha, Dwi Ely Kurniawan, Adyk Marga Raharja

“…This study aims to differentiate between procedural and customer-driven service patterns by applying the FP-Growth association rule mining algorithm to 1,000 anonymized transactions comprising 94 unique items, collected from a veterinary clinic in West Java, Indonesia, during 2023. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…Additionally, we optimize this process using a Genetic Algorithm (GA), allowing for efficient search of the perturbation space while conserving query budget. …”
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Optimizing frequency stability with adaptive fast frequency reserves and Wide-Area Monitoring Systems by Bwandakassy Elenga Baningobera, Irina Oleinikova, Kjetil Uhlen

“…These additional stability considerations enhance the algorithm’s capacity to maintain frequency stability without excessive load shedding or oscillatory behavior. …”
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Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool by Jianying Liu, Wei Jiang, Yahong Yu, Jiali Gong, Guie Chen, Yuxing Yang, Chao Wang, Dalong Sun, Xuefeng Lu

“…The SHAP algorithm helped rank feature importance. A web-based application was developed using the Streamlit framework to enhance clinical usability.Results The Boruta algorithm identified 7 key features. …”
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Automatic Recognition of Motor Skills in Triathlon: A Novel Tool for Measuring Movement Cadence and Cycling Tasks by Stuart M. Chesher, Carlo Martinotti, Dale W. Chapman, Simon M. Rosalie, Paula C. Charlton, Kevin J. Netto

“…<b>Background/Objectives</b>: The purpose of this research was to create a peak detection algorithm and machine learning model for use in triathlon. …”
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Investigation of influential environmental and climatic determinants on COVID-19 spread in India to formulate a sustainable pandemic response by Jaraline Kirubavathy K., Thulasi Bai V.

“…This algorithm identifies the most influential ECDs in the spread of COVID-19 in India, categorizing them as Determinants of Concern (DOC) or Determinants of Interest (DOI). …”
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Multi-Vehicle Object Recognition Method Based on YOLOv7-W by Xin Liu, Jingbin Zhao, Zhi Zhang, Rongxing Wu, Xun Li

“…To meet the demands of intelligent traffic control systems for high-precision vehicle object recognition, an improved recognition algorithm, YOLOv7-W, is proposed based on the YOLOv7 algorithm. …”
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Optimizing winner determination for sustainability and timeliness in fresh agricultural product logistics service procurement auctions: insights from a fourth-party logistics persp... by Yi Zhou, Mingqiang Yin, Qiang Liu, Xiaohu Qian, Delong Jin, Xianming Lang

“…Based on Latin hypercube sampling approach, this paper reconstructs the traditional SAA algorithm framework, and combines the dual decomposition and Lagrangian relaxation algorithm to develop a sampling-based approximate algorithm to solve the proposed model. …”
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Non-Destructive Detection of External Defects in Potatoes Using Hyperspectral Imaging and Machine Learning by Ping Zhao, Xiaojian Wang, Qing Zhao, Qingbing Xu, Yiru Sun, Xiaofeng Ning

“…For potato external defect detection, ordinary spectral technology has limitations in detail detection and processing accuracy, while the machine vision method has the limitation of a long feedback time. …”
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Automation Applied to the Collection and Generation of Scientific Literature by Nadia Paola Valadez-de la Paz, Jose Antonio Vazquez-Lopez, Aidee Hernandez-Lopez, Jaime Francisco Aviles-Viñas, Jose Luis Navarro-Gonzalez, Alfredo Valentin Reyes-Acosta, Ismael Lopez-Juarez

“…Preliminary activities of searching and selecting relevant articles are crucial in scientific research to determine the state of the art (SOTA) and enhance overall outcomes. While there are automatic tools for keyword extraction, these algorithms are often computationally expensive, storage-intensive, and reliant on institutional subscriptions for metadata retrieval. …”
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Self-Organized Connectivity Control and Optimization Subjected to Dispersion of Mobile Ad Hoc Sensor Networks by Zhenqiang Mi, Yang Yang, Hao Ding

“…First, to reduce redundant communication links while preserving global connectivity, a distributed link removal algorithm is developed that only requires local information of no more than two-hop neighbors. …”
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A longan-picking sequence planning method for UAV system based on multi-target tracking by Kaixuan Wu, Meiqi Zhang, Linlin Shi, Hengxu Chen, Yuju Mai, Mingda Luo, Hengyi Lin, Jun Li

“…Manual harvesting of tall fruit trees is plagued by substantial labor intensity and significant operational risks, while ground-based manipulators encounter substantial challenges in achieving the picking of high-altitude fruits. …”
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A generic multi-lidar data batching strategy on the sensor driver level by T. Faitli, H. Hyyti, J. Hyyppä, A. Kukko, H. Kaartinen

“…In order to demonstrate our batching strategy, we provide a case study where we evaluated a SLAM algorithm with a single and a dual-lidar setup. Our batching algorithm enabled us to use the SLAM algorithm that was previously designed for a single spinning lidar without any additional change, while it showcased benefits, especially in stability due to the larger field of view and reduced occlusion.…”
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Rethinking Exploration and Experience Exploitation in Value-Based Multi-Agent Reinforcement Learning by Anatolii Borzilov, Alexey Skrynnik, Aleksandr Panov

“…Our approach outperforms existing algorithms in four of seven scenarios across three distinct environments while remaining competitive in the other three.…”
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