A feature selection method utilizing path accumulation cost, redundancy minimization, and interaction maximization for the diagnosis of coronary heart disease by Jiayao Jiang, Zheng Yue, Hongling Zhu, Yan Wang, Hongsen Cai, Wenguang Hou

“…Conclusion The proposed approach offers an efficient solution for early detection of CHD by identifying critical indicators, reducing diagnostic complexity, and improving predictive accuracy, thus potentially leading to more effective CHD management.…”
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Multi-Scale Residual Convolutional Neural Network with Hybrid Attention for Bearing Fault Detection by Yanping Zhu, Wenlong Chen, Sen Yan, Jianqiang Zhang, Chenyang Zhu, Fang Wang, Qi Chen

“…This paper proposes an advanced deep convolutional neural network model for motor bearing fault detection that was designed to overcome the limitations of traditional models in feature extraction, accuracy, and generalization under complex operating conditions. …”
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A Noninvasive System for the Automatic Detection of Gliomas Based on Hybrid Features and PSO-KSVM by Guoli Song, Zheng Huang, Yiwen Zhao, Xingang Zhao, Yunhui Liu, Min Bao, Jianda Han, Peng Li

“…However, it is a challenging task to detect the gliomas within the complex structure of the brain. …”
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Resolving Non-Proportional Frequency Components in Rotating Machinery Signals Using Local Entropy Selection Scaling–Reassigning Chirplet Transform by Dapeng Quan, Yuli Niu, Zeming Zhao, Caiting He, Xiaoze Yang, Mingyang Li, Tianyang Wang, Lili Zhang, Limei Ma, Yong Zhao, Hongtao Wu

“…In response to these issues, an enhanced time–frequency analysis approach, termed Local Entropy Selection Scaling–Reassigning Chirplet Transform (LESSRCT), has been developed to improve the representation accuracy for complex non-stationary signals. …”
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Enhanced neurological anomaly detection in MRI images using deep convolutional neural networks by Ahmed Mateen Buttar, Zubair Shaheen, Abdu H. Gumaei, Mogeeb A. A. Mosleh, Mogeeb A. A. Mosleh, Indrajeet Gupta, Samah M. Alzanin, Muhammad Azeem Akbar

“…IntroductionNeurodegenerative diseases, including Parkinson’s, Alzheimer’s, and epilepsy, pose significant diagnostic and treatment challenges due to their complexity and the gradual degeneration of central nervous system structures. …”
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YOLOLS: A Lightweight and High-Precision Power Insulator Defect Detection Network for Real-Time Edge Deployment by Qinglong Wang, Zhengyu Hu, Entuo Li, Guyu Wu, Wengang Yang, Yunjian Hu, Wen Peng, Jie Sun

“…To address these issues, we propose YOLOLS, a lightweight and efficient detection model derived from YOLOv8n and optimized for real-time edge deployment. …”
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Classification of Paddy Rice Planting Area Through Feature Selection Method Using Sentinel-1/2 Time Series Images by Shiyu Zhang, Pengao Li, Yong Xie, Wen Shao, Xueru Tian

“…Utilizing remote sensing technology to accurately and efficiently extract paddy rice planting area is crucial for ensuring food security. …”
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Parameter optimization of Mg reduction by thermo-silicon method using Taguchi method, grey relational analysis and preference selection index by Quyen Vu Viet

“…An Fe-Si ratio of 1.3 consistently production efficiency and reducing agent costs. The results demonstrates the efficacy of multi-criteria decision-making techniques in refining complex metallurgical processes and elucidates the interdependencies among operating parameters, offering actionable insights to enhance magnesium yield and ferrosilicon efficiency.…”
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Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example by Jiayuan She, Lin Shi, Peiqi Li, Ziling Dong, Renxing Li, Shengkai Li, Liping Gu, Zhao Tong, Zhuochang Yang, Yajie Ji, Liang Feng, Jiangang Chen

“…Our Dense-ReLU-Dropout model, using RF and PCA for feature selection, achieves high accuracy with greater computational efficiency compared to existing methods that require more complex models or larger datasets. …”
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Modern Trends and Recent Applications of Hyperspectral Imaging: A Review by Ming-Fang Cheng, Arvind Mukundan, Riya Karmakar, Muhamed Adil Edavana Valappil, Jumana Jouhar, Hsiang-Chen Wang

“…Environmental applications include PM2.5 pollution detection with 85.93% accuracy and marine plastic waste detection with 70–80% accuracy. …”
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LCCDMamba: Visual State Space Model for Land Cover Change Detection of VHR Remote Sensing Images by Junqing Huang, Xiaochen Yuan, Chan-Tong Lam, Yapeng Wang, Min Xia

“…Recently, with the advent of Mamba, which maintains linear time complexity and high efficiency in processing long-range data, it offers a new solution to address feature-fusion challenges in LCCD. …”
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Ambient Intelligence to Detect Misuse of Electricity Consumption Based on IoT Using Blockchain Technology by Soiful Hadi, Wahyul Amien Syafei, Adi Wibowo

“…Electricity abuse and energy inefficiencies are still open issues in smart grid systems, demanding high-performance anomaly detection mechanisms. In this paper, we propose an IoT-enabled electricity monitoring system that combines machine learning (LightGBM) and blockchain (Polygon network) for real-time anomaly detection, secure data storage, and transparent energy tracking. …”
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ABA-IDS: Attention-Based Autoencoder for Intrusion Detection in Assistive Mobility Robotic Network by Daniel Ayo Oladele, Elisha Didam Markus

“…This paper introduces ABA-IDS, a low-footprint IDS that uses a ConvLSTM autoencoder with an attention mechanism to detect anomalies in assistive mobility networks. The model’s design allows it to efficiently capture key spatial and temporal features of the network. …”
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A novel approach to skin disease segmentation using a visual selective state spatial model with integrated spatial constraints by Yu Bai, Hai Zhou, Hongjie Zhu, Shimin Wen, Binbin Hu, Haotian Li, Huazhang Wang, Daji Ergu, Fangyao Liu

“…To address limitations in existing approaches, we introduce a novel U-shaped segmentation architecture based on our Residual Space State Block. This efficient model, termed ‘SSR-UNet,’ leverages bidirectional scanning to capture both global and local features in image data, achieving strong performance with low computational complexity. …”
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Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy MCDM Approach: A Theoretical Framework by Fathia Sghayer Abdulgader, Rajeh Eid, Babak Daneshvar Rouyendegh

“…In complex decision making, using multicriteria decision-making (MCDM) methodologies is the most scientific way to ensure an informed and justified decision between several alternatives. …”
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Mechanisms for selective flotation separation of chalcopyrite and molybdenite using the novel depressant 2-(carbamimidoylthio)acetic acid: Experimental and DFT study by Xiangwen Lv, Anruo Luo, Xiong Tong, Jianhua Chen, Sheng Jian

“…This advancement addresses critical challenges in processing complex ores, offering environmental and economic benefits through reduced reagent consumption and improved resource utilization efficiency.…”
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Multi-head deep Q-learning for continuous beamforming with selective MC-CDMA operation in V2X highway communications by Nguyen Huu Trung, Nguyen Thuy Anh, Fuqiang Liu

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Hybrid YOLOv8 and Fast R-CNN for Accurate Schematic Detection in Power Distribution Networks by Aviv Yuniar Rahman, Zuhaina Zakaria

“…Conventional edge detection methods often struggle with the complexity and scale of modern PDNs, while standalone deep learning approaches face challenges in balancing real-time performance and high precision. …”
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Fast link-establishment method of integrated of communication and detection based on short-wave digital channelization by Guojun LI, Cuiling XIANG, Changrong YE, Zunli WANG

“…A link-establishment method based on short-wave digital channelized receiver was proposed for the traditional automatic link establishment technology in short-wave communications with the low accuracy of frequency selection, low efficiency of link establishment, and low utilization of resources, etc.The parallel receiving mechanism for full frequency band in short-wave communications was realized by using digital channelization.An integrated waveform of communication and detection was designed to deal with the time redundancy and equipment compatibility problems caused by waveform switching during link establishment.A fast link-establishment method was designed, to achieve a fast and robust connection in complex electromagnetic environments.The results show that the channelized structure can enhance the receiving performance of the link-establishment system, the link-establishment method has obvious advantages, channel parameter estimation method has a high estimation accuracy compared to the traditional link-establishment method and the applicability of the proposed method in practical short-wave channel environment is verified.…”
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Fast link-establishment method of integrated of communication and detection based on short-wave digital channelization by Guojun LI, Cuiling XIANG, Changrong YE, Zunli WANG

“…A link-establishment method based on short-wave digital channelized receiver was proposed for the traditional automatic link establishment technology in short-wave communications with the low accuracy of frequency selection, low efficiency of link establishment, and low utilization of resources, etc.The parallel receiving mechanism for full frequency band in short-wave communications was realized by using digital channelization.An integrated waveform of communication and detection was designed to deal with the time redundancy and equipment compatibility problems caused by waveform switching during link establishment.A fast link-establishment method was designed, to achieve a fast and robust connection in complex electromagnetic environments.The results show that the channelized structure can enhance the receiving performance of the link-establishment system, the link-establishment method has obvious advantages, channel parameter estimation method has a high estimation accuracy compared to the traditional link-establishment method and the applicability of the proposed method in practical short-wave channel environment is verified.…”
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