A YOLOv8n-T and ByteTrack-Based Dual-Area Tracking and Counting Method for Cucumber Flowers by Liyang Su, Shujuan Zhang, Hongtu Zhang, Xiangsen Meng, Xiongkui He

“…The YOLOv8n-T incorporates a Coordinate Attention (CA) mechanism and lightweight modules while optimizing the loss function, thereby improving floral feature extraction capabilities and reducing computational complexity. …”
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Energy-Efficient Route and Velocity Planning for Electric Vehicles: A Hierarchical Eco-Driving Framework Integrating Traffic and Road Information by Dong Xie, Jianhua Guo, Yu Jiang, Zhuoran Hou, Jintao Deng

“…Then, an energy-efficient route is efficiently planned using the proposed multi-heuristic A* algorithm. Finally, based on the route information from the upper level, along with traffic, kinematic, and road information, a convex optimization algorithm is employed to achieve accurate and efficient velocity planning. …”
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A Maximal Concurrency and Low Latency Distributed Scheduling Protocol for Wireless Sensor Networks by Xiaohui Liu, Yu Chen, Hongwei Zhang

“…Existing work that schedules concurrent transmissions without collisions suffers from low channel utilization. We propose the Optimal Node Activation Multiple Access (ONAMA) protocol to achieve maximal channel spatial reuse through a distributed maximal independent set (DMIS) algorithm. …”
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Voronoi-GRU-Based Multi-Robot Collaborative Exploration in Unknown Environments by Yang Lei, Jian Hou, Peixin Ma, Mingze Ma

“…In the lower layer, navigation planning is achieved using A* and Timed Elastic Band (TEB) algorithms, while an improved Cartographer algorithm is used to construct a joint map for the multi-robot system. …”
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Deep Reinforcement Learning-Based Impact Angle-Constrained Adaptive Guidance Law by Zhe Hu, Wenjun Yi, Liang Xiao

“…This study presents an advanced second-order sliding-mode guidance law with a terminal impact angle constraint, which ingeniously combines reinforcement learning algorithms with the nonsingular terminal sliding-mode control (NTSM) theory. …”
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Enhancing high pressure pulsation test bench performance: a machine learning approach to failure condition tracking by Aslı Aksoy, Ömer Haki

“…The objective of this study is to enhance the efficiency of HPPT benches by addressing specimen, bench, and test environment- based problems and to develop a failure condition tracking tool (FCTT) by using machine learning (ML) algorithms. The findings of this study provide a basis for the development of the company’s data-driven smart predictive maintenance applications while providing an increase in the operational efficiency of HPPT benches. …”
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Expansion Planning of Electrical Distribution Systems Considering Voltage Quality and Reliability Criteria by Marco Israel Zuñiga Villarreal, Alexander Aguila Téllez, Narayanan Krishnan, Marcelo García

“…A 5% annual load growth was simulated for each system, which involved analyzing key parameters, such as the power loss, voltage deviation, and average failure rate. An algorithm was developed to perform a multi-criteria analysis, which provided optimal solutions for the system behavior in response to increasing demand. …”
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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

“…A relevancy factor analysis quantified the influence of each input parameter on model outputs, whereas the Leverage technique identified outliers and defined the parameter ranges for optimal algorithm performance. While the ML models achieved high predictive reliability, their computational demands and complexity may limit deployment in resource-constrained environments and decision-critical applications. …”
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An online multi-camera multi-vehicle tracking using lightweight YOLO11 and improved association strategies by Feijiang Huang, Jialong Yao, Chengyue Su, Sheng Xu

“…Abstract Multi-camera multi-vehicle tracking (MCMVT) is essential for intelligent transportation and urban security but is hindered by similar vehicle appearances, varying viewpoints, and occlusions. While existing offline algorithms offer high accuracy, their heavy computational load and lack of real-time performance limit practical use. …”
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Combination of Feature Selection and Learning Methods for IoT Data Fusion by V. Sattari-Naeini, Zahra Parizi-Nejad

“…In this paper, we propose five data fusion schemes for the Internet of Things (IoT) scenario,which are Relief and Perceptron (Re-P), Relief and Genetic Algorithm Particle Swarm Optimization (Re-GAPSO), Genetic Algorithm and Artificial Neural Network (GA-ANN), Rough and Perceptron (Ro-P)and Rough and GAPSO (Ro-GAPSO). …”
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Linear Continuous-Time Regression and Dequantizer for Lithium-Ion Battery Cells with Compromised Measurement Quality by Zoltan Mark Pinter, Mattia Marinelli, M. Scott Trimboli, Gregory L. Plett

“…Then, the Linear Continuous-Time Regression (LCTR) algorithm extracts exponential parameters from first-order or overdamped second-order systems, deducing ECM parameters and guaranteeing optimality with respect to RMSE. …”
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Blasting Vibration Control Using an Improved Artificial Neural Network in the Ashele Copper Mine by Shida Xu, Tianxiao Chen, Jiaqi Liu, Chenrui Zhang, Zhiyang Chen

“…In this paper, a genetic algorithm (GA) and an artificial neural network (ANN) algorithm were jointly used to construct a neural network model with a 4-5-1 topology to predict the PPV. …”
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Trade-off between gradient measurement efficiency and expressivity in deep quantum neural networks by Koki Chinzei, Shinichiro Yamano, Quoc Hoan Tran, Yasuhiro Endo, Hirotaka Oshima

“…Abstract Quantum neural networks (QNNs) require an efficient training algorithm to achieve practical quantum advantages. …”
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A Simulation Based Metaheuristics for Capacitated Vehicle Routing Problem by Tamara Latifah Jasmine, Heru Purboyo Hidayat Putro, Niken Prilandita, Gatot Yudoko

“…The methodology utilizes a simheuristics approach, integrating a Genetic Algorithm (GA) to determine optimal routing solutions, while employing Discrete Event Simulation (DES) to incorporate key economic, environmental, and social variables. …”
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Lightweight YOLOv8s-Based Strawberry Plug Seedling Grading Detection and Localization via Channel Pruning by CHEN Junlin, ZHAO Peng, CAO Xianlin, NING Jifeng, YANG Shuqin

“…Furthermore, a two-stage seedling-hole matching algorithm was introduced based on the pruned YOLOv8s model. …”
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Influence of information technologies on technical fitness of students in sport-oriented physical education by Zh.L. Kozina, O.M. Ol'khovyj, V.A. Temchenko

“…Such approach envisages holistic form of program material construction and unified algorithm of students’ progress assessment. Conclusions: the wholeness of sport-oriented physical education’s functioning is ensured at the account of application of information technologies. …”
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Mortality prediction of heart transplantation using machine learning models: a systematic review and meta-analysis by Ida Mohammadi, Setayesh Farahani, Asal Karimi, Saina Jahanian, Shahryar Rajai Firouzabadi, Mohammadreza Alinejadfard, Alireza Fatemi, Bardia Hajikarimloo, Mohammadhosein Akhlaghpasand

“…Among the algorithms, CatBoost demonstrated the highest accuracy (AUC 0.80, 95% CI: 0.74, 0.86), while K-nearest neighbor had the lowest accuracy (AUC 0.53, 95% CI: 0.50, 0.55). …”
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Genotyping Identification of Maize Based on Three-Dimensional Structural Phenotyping and Gaussian Fuzzy Clustering by Bo Xu, Chunjiang Zhao, Guijun Yang, Yuan Zhang, Changbin Liu, Haikuan Feng, Xiaodong Yang, Hao Yang

“…The research results showed that the Gaussian Fuzzy Clustering algorithm was the optimal choice for clustering maize genotypes. …”
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Multi-Feature Long Short-Term Memory Facial Recognition for Real-Time Automated Drowsiness Observation of Automobile Drivers with Raspberry Pi 4 by Michael Julius R. Moredo, James Dion S. Celino, Joseph Bryan G. Ibarra

“…The model was trained on the NTHU-DDD dataset and optimized using long short-term memory (LSTM) deep learning algorithms implemented using TensorFlow version 2.14.0. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…Abdominal fat (AF) in hens impacts egg production and may reflect poor feed efficiency, meaning that dynamic monitor of AF changes facilitate to optimize feeding management and production efficiency. …”
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