Temporal Convolutional Network Approach to Secure Open Charge Point Protocol (OCPP) in Electric Vehicle Charging by Ikram Benfarhat, Vik Tor Goh, Chun Lim Siow, Muhammad Sheraz, Teong Chee Chuah

“…Additionally, we conducted a comparative analysis with a hybrid model, demonstrating that the proposed TCN delivers superior performance with lower computational complexity, fewer parameters, a smaller model size, and shorter computation times. …”
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Design workflow of a symmetric traveling wave antenna for fast ion production on DD tokamaks by J.G. van de Lindt, S.J. Wukitch, N. Bertelli, S. Shiraiwa

“…The TWA produced by this workflow has several novel features when compared to previous TWA studies, including symmetric center feeding, and passive end straps for image current cancellation for reduced impurity production. …”
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Fault Diagnosis of Electric Impact Drills Based on Time-Varying Loudness and Logistic Regression by Yapeng Jing, Haitao Su, Shao Wang, Wenhua Gui, Qing Guo

“…A feature extraction peak-to-average ratio (PAR) method based on the time-varying loudness spectrum was described and implemented to compute the feature vectors. …”
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Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model by Xiaoai Dai, Junying Cheng, Shouheng Guo, Chengchen Wang, Ge Qu, Wenxin Liu, Weile Li, Heng Lu, Youlin Wang, Binyang Zeng, Yunjie Peng, Shuneng Liang

“…However, because of their multiband and multiredundant characteristics, hyperspectral data processing is still complex. Two feature extraction algorithms, the autoencoder (AE) and restricted Boltzmann machine (RBM), were used to optimize the classification model parameters. …”
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Tomato Ripening Detection in Complex Environments Based on Improved BiAttFPN Fusion and YOLOv11-SLBA Modeling by Yan Hao, Lei Rao, Xueliang Fu, Hao Zhou, Honghui Li

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Sea Surface Temperature Prediction Based on Spatio-Temporal Graph Contrastive Learning Network by Weihan Dai, Xiaoyu He, Xiulin Geng, Shuai Zhang, Ziheng Gao

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A Detection Method of Lentinus Edodes Based on Improved YOLOv4 Algorithm by HUANG Ying-lai, LI Da-ming, LU Xin, YANG Liu-song

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An improved DeepLabv3 + railway track extraction algorithm based on densely connected and attention mechanisms by Yanbin Weng, Jie Yang, Changfan Zhang, Jing He, Cheng Peng, Lin Jia, Hui Xiang

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SHIFA: SBERT-Based Healthcare Information Focused Arabic Question Answering by Rahaf Alruwaithi, Sarah AlHumoud

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Demystifying DFT-Based Harmonic Phase Estimation, Transformation, and Synthesis by Marco Oliveira, Vasco Santos, André Saraiva, Aníbal Ferreira

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Empowering sentiment analysis in social media: a comprehensive approach to enhance the classification of abusive Tamil comments using transformer models by Malliga Subramanian, Sathishkumar Veerappampalayam Easwaramoorthy, Nandhini Subbarayan, Usha Moorthy

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RRFNet: A free-anchor brain tumor detection and classification network based on reparameterization technology. by Wei Liu, Xingxin Guo

“…This study, introduces a backbone network built using RepConv and RepC3, along with FGConcat feature map splicing module to optimize the brain tumor detection model. …”
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Open-source Flux Transport (OFT). I. HipFT–High-performance Flux Transport by Ronald M. Caplan, Miko M. Stulajter, Jon A. Linker, Cooper Downs, Lisa A. Upton, Bibhuti Kumar Jha, Raphael Attie, Charles N. Arge, Carl J. Henney

“…The Open-source Flux Transport (OFT) model seeks to fill this gap by providing an open and user-extensible SFT model that also builds on the knowledge of previous models with updated numerical and data acquisition/assimilation methods along with additional user-defined features. In this first of a series of papers on OFT, we introduce its computational core: the High-performance Flux Transport (HipFT) code ( https://github.com/predsci/hipft ). …”
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Morphometry of upper Gilgel Abay watershed in southern Tana Basin, Ethiopia, 2023: analysis and implication for land and water resource management by Simachew Bantigegn Wassie, Melkamu Alebachew Anleye

“…This study tried to delineate the UGAW and its sub-watersheds, compute basic morphometric parameters, and link each value with its drainage characteristics. …”
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Foot Pressure-Based Abnormal Gait Recognition With Multi-Scale Cross-Attention Fusion by Menghao Yuan, Yan Wang, Xiaohu Zhou, Meijiang Gui, Aihui Wang, Chen Wang, Guotao Li, Hongnian Yu, Lin Meng, Zengguang Hou

“…Notably, these results are obtained with a lightweight architecture characterized by reduced FLOPs and parameter count, demonstrating that MSCAF-Gait offers both high accuracy and computational efficiency, making it well-suited for real-time deployment on wearable platforms.…”
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Investigating the hyperparameter space of deep neural network models for reaction coordinates by Kyohei Kawashima, Takumi Sato, Kei-ichi Okazaki, Kang Kim, Nobuyuki Matubayasi, Toshifumi Mori

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Physical Information Neural Network-Based Seepage Behavior Analysis of Earth and Rock Dams by XUE binghan, HUANG zhenhua, LEI Jianwei, FANG Hongyuan

“…This substantially enhances computational efficiency.…”
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Bone scintigraphy based on deep learning model and modified growth optimizer by Omnia Magdy, Mohamed Abd Elaziz, Abdelghani Dahou, Ahmed A. Ewees, Ahmed Elgarayhi, Mohammed Sallah

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A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification by Manishi Shakya, Ravindra Patel, Sunil Joshi

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MECHANICAL STATE ANALYSIS USING QUANTUM THEORY AND MATHEMATICAL MORPHOLOGICAL FILTER by SHI Ying

“…Aiming at the erosion operator for the mathematical morphological filter（ MMF）,the quantum-inspired weighting structuring element（ QWSE） is proposed based on the quantum theory to extract fault information of mechanical vibration signal.Firstly,after analyzing the system with multiple quantum bits,a method which is employed to map the quantum space to the real number space is presented and the calculation formula of the QWSE is obtained. Then in order to compute all the parameters of the QWSE,the stochastic characteristics of mechanical vibration signal is utilized to acquire the quantum-inspired weighting while the local feature of signal is utilized to generate the dynamic height of the QWSE. …”
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