Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

“…Based on the 6 driving cycles, the key parameters of rule-based control strategy are optimized and established by a combinatorial optimization algorithm in Isight. …”
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Phase diagram from nonlinear interaction between superconducting order and density: toward data-based holographic superconductor by Sejin Kim, Kyung Kiu Kim, Yunseok Seo

“…We introduce positional embedding layers to improve the learning process in our algorithm, and the Adam optimization is used to predict the critical temperature data via holographic calculation with appropriate accuracy. …”
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Analysis and Implementation of the Crowbar Clamping Circuit for Surge Voltage Reduction in the DC Solid-State Circuit Breaker by Phanit Sok, Sung-Geun Song, Feel-Soon Kang

“…A significant challenge in DC SSCB is simulating the behavior with several types of MOV with the highly non-linear model of MOV. The equivalent non-linear model of the MOV used in this paper for simulation is determined through the curve fit function using the algorithm for optimization.…”
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Impacts of inter-train distances on aerodynamic drag reduction in heavy-haul train groups by LYU Jun, XIANG Tao, SONG Zongying, GAO Guangjun

“…This paper analyzes the impacts of inter-train distances in this operational mode on the aerodynamic characteristics of trailing trains, using computational fluid dynamics (CFD) methods, based on the SST <italic>k</italic>-<italic>ω</italic> turbulence model. Initial algorithm validation was performed, and the results were compared with data from wind tunnel experiments conducted in a large low-speed wind tunnel at the China aerodynamics research and development center. …”
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Maximum Power Extraction in Photovoltaic Systems Using High-Performance Adaptive Control Approach by Ahmed Ouaret, Hocine Lehouche, Adel Oubelaid, Arvind Yadav, Boubekeur Mendil, Ievgen Zaitsev

“…These outcomes underscore the notable performance enhancements facilitated by the proposed algorithm. In conclusion, the developed control algorithm offers superior performance in optimizing power extraction and maintaining precise set point tracking for PV systems, leading to improved system efficiency and increased profitability.…”
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Comparison of Spatial Predictability Differences in Truck Activity Patterns: An Empirical Study Based on Truck Tracking Dataset of China by Lianghua Li, Peng Du, Guohua Jiao, Xin Fu

“…Existing research on truck location prediction focuses on direct trajectory prediction and ignores the link between activity patterns and predictability, whereas the mode of operation is an important factor in the difference between activity trajectories, and analyzing the mode of operation can help to develop the next-location prediction algorithms to improve the efficiency of matching truckloads and to reduce costs. …”
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KDFE: Robust KNN-Driven Fusion Estimator for LEO-SoOP Under Multi-Beam Phased-Array Dynamics by Jiaqi Yin, Ruidan Luo, Xiao Chen, Linhui Zhao, Hong Yuan, Guang Yang

“…This decision model overcomes the accuracy-robustness trade-off by matching algorithmic strengths to beam-specific dynamics, ensuring optimal performance during abrupt SNR transitions and high Doppler rates. …”
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GAT-Enhanced YOLOv8_L with Dilated Encoder for Multi-Scale Space Object Detection by Haifeng Zhang, Han Ai, Donglin Xue, Zeyu He, Haoran Zhu, Delian Liu, Jianzhong Cao, Chao Mei

“…According to the characteristics of space missions, an annotated dataset containing 8000 satellite and space station images is constructed, covering a variety of lighting, attitude and scale scenes, and providing benchmark support for model training and verification. Experimental results on the space object dataset reveal that the enhanced algorithm achieves a mean average precision (mAP) of 97.2%, representing a 2.1% improvement over the original YOLOv8_L. …”
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Measurement Techniques for Highly Dynamic and Weak Space Targets Using Event Cameras by Haonan Liu, Ting Sun, Ye Tian, Siyao Wu, Fei Xing, Haijun Wang, Xi Wang, Zongyu Zhang, Kang Yang, Guoteng Ren

“…In the target denoising phase, we fully consider the characteristics of space targets’ motion trajectories and optimize a classical spatiotemporal correlation filter, thereby significantly improving the signal-to-noise ratio for weak targets. …”
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Abnormal Vibration Analysis of Low-floor Tram by Shuo LYU, Huanyun DAI, Qunsheng WANG

“…By establishing a vehicle dynamics model, the influence of the wheel on the different eccentricity is analyzed, and the vertical ride comfort is greatly improved by optimizing parameters of inter-vehicle longitudinal damper and secondary vertical damper. …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…To address the challenges posed by class imbalance and temporal dependency in drilling condition data and enhance the accuracy of condition identification, this study proposes an integrated method combining feature engineering, data resampling, and deep learning model optimization. Firstly, a feature selection strategy based on weighted symmetrical uncertainty is employed, assigning higher weights to critical features that distinguish minority classes, thereby enhancing class contrast and improving the classification capability of the model. …”
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Empowering drones in vehicular network through fog computing and blockchain technology. by Shivani Wadhwa, Divya Gupta, Shalli Rani, Maha Driss, Wadii Boulila

“…The proposed algorithm dynamically plans drone trajectories and optimizes computation offloading. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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A Study on Fitting Longitudinal Profiles of Railway Station Tracks by Junhao Zeng, Lianbo Deng, Wenqin Deng, Jinglan Jiang, Yuantian Huang

“…To satisfy the model constraints, an optimal vertical curve fitting algorithm, utilising a bisector vector approach to unambiguously resolve the conjugacy issue in analytical circular curve calculations, and a genetic algorithm based on neighbourhood search, specifically designed to fine-tune initial least squares gradient estimates and avoid systematic deviations, are proposed. …”
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Digital mapping of peat thickness and extent in Finland using remote sensing and machine learning by Jonne Pohjankukka, Timo A. Räsänen, Timo P. Pitkänen, Arttu Kivimäki, Ville Mäkinen, Tapio Väänänen, Jouni Lerssi, Aura Salmivaara, Maarit Middleton

“…We carefully split the reference data into training and test sets, allowing for independent and robust model validation. Feature selection included an initial screening for multicollinearity using correlation-based feature pruning, followed by final selection using a genetic algorithm. …”
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Broiler Behavior Detection and Tracking Method Based on Lightweight Transformer by Haixia Qi, Zihong Chen, Guangsheng Liang, Riyao Chen, Jinzhuo Jiang, Xiwen Luo

“…In addition, we propose a new cross-scale feature fusion network to optimize the neck network of the original model. These improvements led to a 78% decrease in the number of parameters and a 68% decrease in GFLOPs. …”
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Machine learning-based prediction of carotid intima–media thickness progression: a three-year prospective cohort study by An Zhou, Kui Chen, Kui Chen, Yonghui Wei, Qu Ye, Qu Ye, Yuanming Xiao, Rong Shi, Jiangang Wang, Wei-Dong Li

“…Baseline CIMT, absolute monocyte count, sex, age, and LDL-C were identified as the most influential predictors. After Platt scaling, the calibration improved significantly across all the models. …”
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Object Detection using YOLOv8 : A Systematic Review by Nugraha Asthra Megantara, Ema Utami

“…This study evaluates the performance of YOLOv8 based on precision, recall, F1-score, and mean average precision (mAP) metrics, and compares its advantages and limitations with previous YOLO versions and other object detection algorithms. Improvements in the YOLOv8 architecture, including attention mechanisms, improved feature extraction, and hyperparameter optimization, enable significant improvements in accuracy and computational efficiency, especially for small objects and low-light conditions. …”
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The use of artificial intelligence in stereotactic ablative body radiotherapy for hepatocellular carcinoma by Atsuto Katano

“…Clinical studies have demonstrated notable benefits, such as a reduction in contouring time and improved dosimetric quality using machine learning–based optimization algorithms. …”
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Research on green supply chain finance risk identification based on two-stage deep learning by Ying Liu, Sizhe Li, Chunmei Yu, Mingli Lv

“…Finally, to model low-order feature interactions, we integrate the Support Vector Machine (SVM) algorithm. …”
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