Adverse events in the neonatal intensive care unit identified by triggers by Fabiana Bragança Albanese, Deise de Souza Ventura, Deise de Souza Ventura, Maurício Wesley Perroud, Maurício Wesley Perroud, Rafael Nogueira de Souza, Mariana Vieira Morau, Marília Berlofa Visacri, Marília Berlofa Visacri, Patricia Moriel, Patricia Moriel

“…AE severity was assessed using the Neonatal Adverse Event Severity Scale (NAESS) and the World Health Organization (WHO) classification, while ADR causality was evaluated using the WHO criteria and the algorithm proposed by Du et at. …”
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Battery Energy Storage System Contribution to Primary Frequency Control in Isolated Power Systems by Muhammad Asad, Giulia Tresca, Pericle Zanchetta, Jose Angel Sanchez-Fernandez

“…Results show the significant reduction in frequency deviation, optimal sizing of BESS and optimal tuning of the whole WDPS.…”
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In situ fully vectorial tomography and pupil function retrieval of tightly focused fields by Xin Liu, Shijie Tu, Yiwen Hu, Yifan Peng, Yubing Han, Cuifang Kuang, Xu Liu, Xiang Hao

“…When combined with our decoding algorithm, this strategy mitigates the imperfections in the detection path. …”
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Balancing resource utilization and slice dissatisfaction through dynamic soft slicing for 6G wireless networks by Zeinab Sasan, Siavash Khorsandi

“…The problem is formulated as a Mixed Integer Linear Programming (MILP) model, aiming to maximize network utilization while minimizing slice dissatisfaction. Given the NP-hard nature of the problem, we propose the Heuristic Resource Allocation for Soft Slicing (HRASS) algorithm, which achieves near-optimal performance with significantly reduced computational complexity. …”
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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…The proposed method was tested on a small dataset within transplantology, focusing on binary classification. Optimal parameters for the method were identified using the Dual Annealing algorithm. …”
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Impedance-Driven Decoupling Water–Nitrogen Stress in Wheat: A Parallel Machine Learning Framework Leveraging Leaf Electrophysiology by Shuang Zhang, Xintong Du, Bo Zhang, Yanyou Wu, Xinyi Yang, Xinkang Hu, Chundu Wu

“…A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. …”
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Remote Target High-Precision Global Geolocalization of UAV Based on Multimodal Visual Servo by Xuyang Zhou, Ruofei He, Wei Jia, Hongjuan Liu, Yuanchao Ma, Wei Sun

“…We design a step-convergent target geolocation optimization algorithm. By adjusting the step size and the scale factor of the cost function, we achieve fast accuracy convergence for different UAV reconnaissance modes, while maintaining the geolocation accuracy without divergence even when the laser ranging sensor is turned off for a short period. …”
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XSQ-Learning: Adaptive Similarity Thresholds for Accelerated and Stable Q-Learning by Ansel Y. Rodríguez González, Roberto E. López Díaz, Shender M. Ávila Sansores, María G. Sánchez Cervantes

“…Reinforcement Learning (RL) enables agents to learn optimal policies through environment interaction, with Q-learning being a fundamental algorithm for Markov Decision Processes (MDPs). …”
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Lightweight UAV Detection Method Based on IASL-YOLO by Huaiyu Yang, Bo Liang, Song Feng, Ji Jiang, Ao Fang, Chunyun Li

“…To address this, we propose the IASL-YOLO algorithm, which optimizes the YOLOv8s model to enhance detection accuracy and lightweight efficiency. …”
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A review on machine learning applications in hydrogen energy systems by Zaid Allal, Hassan N. Noura, Ola Salman, Flavien Vernier, Khaled Chahine

“…The paper provides an in-depth review of the literature, examining not only ML techniques but also optimization algorithms, evaluation methods, explainability techniques, and emerging technologies. …”
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Heterogeneity-aware device selection for efficient federated edge learning by Yiran Shi, Jieyan Nie, Xingwei Li, Hui Li

“…To address these issues, this paper proposes a novel Quality-aware online Device Selection (QDS) algorithm. The QDS algorithm leverages a greedy selection method that guarantees the deadline restrictions and reflects upon their historical performance metrics, as indicated by their loss function values from preceding training rounds. …”
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Pseudolite Self-Interference Cancellation Without Additional GNSS Signal Distortion by Lichao Gao, Jin He, Yuanxin Wu, Wenxian Yu

“…The simulation test results show that the algorithm can filter self-interference without additional distortion of the satellite navigation signals. …”
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Mapping the landscape of machine learning in chronic disease management: A comprehensive bibliometric study by Shiying Shen, Wenhao Qi, Sixie Li, Jianwen Zeng, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Qian Xu, Shihua Cao

“…Logistic regression (n = 459) remains the most widely used algorithm, while neural networks (n = 183) show promising potential. …”
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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

“…We introduce a parameter to the super-twisting algorithm and subsequently improve an intelligent parameter-adaptive algorithm grounded in the Twin-Delayed Deep Deterministic Policy Gradient (TD3) framework. …”
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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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