Non-destructive detection of early wheat germination via deep learning-optimized terahertz imaging by Guangming Li, Hongyi Ge, Yuying Jiang, Yuan Zhang, Xi Jin

“…However, current THz imaging techniques are limited by low image resolution, which restricts their practical application. …”
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Facilitating automated fact-checking: a machine learning based weighted ensemble technique for claim detection by Md. Rashadur Rahman, Rezaul Karim, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Gahangir Hossain, Tetsuya Shimamura

“…To determine the optimal model and feature representation for claim detection, various machine learning algorithms were evaluated using BoW, TF-IDF, Word2Vec, and FastText features. …”
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A Segmented Low-Order Bistable Stochastic Resonance Method for Fixed-Distance Target Detection in Millimeter-Wave Fuze Under Rainy Conditions by Bing Yang, Kaiwei Wu, Zhe Guo, Yanbin Liang, Shijun Hao, Zhonghua Huang

“…To address these limitations while satisfying real-time processing requirements, this study proposes (1) a novel segmented low-order bistable stochastic resonance (SLOBSR) system based on piecewise polynomial potential functions and (2) a corresponding fixed-distance target detection algorithm incorporating signal pre-processing, particle swarm optimization (PSO)-based parameter optimization, and kurtosis threshold detection. …”
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A Modularized Super Capactior Energy Storage System forMetro Train and Its Control Algorithm by CHEN Guangzan, LIU Lan, HUANG Deliang, YI Yunlan

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Machine learning models and dimensionality reduction for improving the Android malware detection by Pablo Morán, Antonio Robles-Gómez, Andres Duque, Llanos Tobarra, Rafael Pastor-Vargas

“…They can detect an average of 91.72% malware samples, with a very low false positive rate of 0.13%, and using only 5,000 features. …”
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A method for detecting abnormal electricity prices at charging stations based on two rounds of clustering by XUE Xiaohui, ZHANG Wen, ZHANG Jing, CHEN Yan, ZHOU Chun, CHEN Liang, CAO Zengwei

“…Then, in the second clustering, the density-based spatial clustering of applications with noise (DBSCAN) algorithm was used to accurately identify more complex default situations,such as high price and low connection. …”
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Infrared Small Target Detection Based on Compound Eye Structural Feature Weighting and Regularized Tensor by Linhan Li, Xiaoyu Wang, Shijing Hao, Yang Yu, Sili Gao, Juan Yue

“…Our model is efficiently solved using the Alternating Direction Method of Multipliers (ADMM). Experimental results demonstrate that the proposed model can rapidly and accurately detect small infrared targets in bio-inspired compound eye image sequences, outperforming other comparative algorithms.…”
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A computational framework for IoT security integrating deep learning-based semantic algorithms for real-time threat response by Ripal Ranpara, Shobhit K. Patel, Om Prakash Kumar, Fahad Ahmed Al-Zahrani

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Sensor-free, Camera-only: Low-cost multi-angle CPR skill assessments method based on computer vision by Longxin Liu, Cen Wu, Jiafeng Liu, Jiayi Yu, Meng Bi, Hong Yu

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LEAF-YOLO: Lightweight Edge-Real-Time Small Object Detection on Aerial Imagery by Van Quang Nghiem, Huy Hoang Nguyen, Minh Son Hoang

“…To address this, we propose LEAF-YOLO, a lightweight and efficient object detection algorithm with two versions: LEAF-YOLO (standard) and LEAF-YOLO-N (nano). …”
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An Efficient Approach Based on RAE-GAMI-NET for Long Range Attack Detection on Blockchain by Vasavi Chithanuru, Mangayarkarasi Ramaiah

“…The proposed explainable neural network model includes Residual Auto Encoder (RAE) guided generalized additive models with incorporating structured interactions (RAE-GAMI-Net) for LRA detection in PoS Blockchain In this work, a wrapper-based Binary Orchard Algorithm (W-BOA) is used to find the best features to lessen the dimensionality of extracted Characteristics, and a global feature extraction has been implemented based on multi-scale Densenet (MDensenet) that assures early convergence and optimal performance by providing global optimal solution. …”
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A Safe and Efficient Global Path-Planning Method Considering Multiple Environmental Factors of the Moon Using a Distributed Computation Strategy by Ruyan Zhou, Yuchuan Liu, Zhonghua Hong, Haiyan Pan, Yun Zhang, Yanling Han, Jiang Tao

“…This paper proposes a distributed path-planning method that considers multiple lunar environmental factors, addressing the issues of inadequate safety considerations and low computational efficiency in current research. …”
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A Low Inrush Current Pre-Charging Strategy of M3C with Improved Nearest Level Modulation by Rufei He, Yikai Li, Yumin Peng, Yiming Ma, Fanqi Huang, Hailong Li, Wei Luo

“…The modular multilevel matrix converter (M3C) can perform AC/AC conversion directly. However, M3C operation often requires a pre-charging process, which can be challenging due to the need for fast pre-charging with low inrush current. …”
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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…Passion fruit pests are characterized by their high species diversity, small physical size, and dense populations. Traditional algorithms often face challenges in achieving high detection accuracy and efficiency when addressing the complex task of detecting densely distributed small objects. …”
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Single-Lane 112-Gbit/s SSB-PAM4 Transmission With Dual-Drive MZM and Kramers–Kronig Detection Over 80-km SSMF by Liang Shu, Jianqiang Li, Zhiquan Wan, Fan Gao, Songnian Fu, Xiang Li, Qi Yang, Kun Xu

“…We have experimentally demonstrated the signal-to-signal beating interference (SSBI) mitigation capability of Kramers–Kronig (KK) detection in a single sideband (SSB) four-ary pulse-amplitude-modulation (PAM4) direct detection (DD) system. …”
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Sustainable Self-Training Pig Detection System with Augmented Single Labeled Target Data for Solving Domain Shift Problem by Junhee Lee, Heechan Chae, Seungwook Son, Jongwoong Seo, Yooil Suh, Jonguk Lee, Yongwha Chung, Daihee Park

“…To address the degradation issue, this study proposes a self-training-based domain adaptation method that utilizes a single label on target (SLOT) sample from the target domain, a genetic algorithm (GA)-based data augmentation search (DAS) designed explicitly for SLOT data to optimize the augmentation parameters, and a super-low-threshold strategy to include low-confidence-scored pseudo-labels during self-training. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…Experimental results indicate that the MTGNN outperforms comparative algorithms, such as CrossGNN and FourierGNN, in prediction accuracy, with the mean absolute error (MAE) being as low as 0.00237 and the root mean square error (RMSE) maintained below 0.0203 across different sensor locations (T0, T1, T2). …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…Abstract Accurate estimation of permeability reduction in clay-rich sandstones during low-salinity water flooding is critical for optimizing enhanced oil recovery (EOR) strategies and ensuring efficient reservoir management. …”
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Intelligent recognition algorithm and application of coal mine overhead passenger device based on multiscale feature fusion by Beijing XIE, Heng LI, Hang DONG, Zheng LUAN, Ben ZHANG, Xiaoxu LI

“…The YOLOv8n single-stage object detection algorithm was used as the baseline model, and a coal mine cmopd intelligent recognition algorithm based on multi-scale feature fusion was proposed.In the image preprocessing stage, adaptive histogram equalization was employed to enhance image quality, and random rectangle masking was applied to simulate real scenarios where cmopd is occluded by underground objects during operation. …”
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Perception-Based H.264/AVC Video Coding for Resource-Constrained and Low-Bit-Rate Applications by Lih-Jen Kau, Chin-Kun Tseng, Ming-Xian Lee

“…Motivated by these practical demands, this paper proposes a perception-based video coding algorithm specifically tailored for low-bit-rate H.264/AVC applications. …”
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