Integrating Correlation-Based Feature Selection and Clustering for Improved Cardiovascular Disease Diagnosis by Agnieszka Wosiak, Danuta Zakrzewska

“…The obtained effects have been evaluated regarding the number of detected dependencies between parameters. Experiment results showed the advantage of the presented approach compared to other feature selection methods and without using clustering to support statistical inference.…”
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A New Method for Weak Fault Feature Extraction Based on Improved MED by Junlin Li, Jingsheng Jiang, Xiaohong Fan, Huaqing Wang, Liuyang Song, Wenbin Liu, Jianfeng Yang, Liangchao Chen

“…Because of the characteristics of weak signal and strong noise, the low-speed vibration signal fault feature extraction has been a hot spot and difficult problem in the field of equipment fault diagnosis. …”
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Optimization and Validation of Wafer Surface Defect Detection Algorithm Based on RT-DETR by Ao Xu, Yanwei Li, Hongbo Xie, Rui Yang, Jianjie Li, Jiaying Wang

“…Firstly, a dynamic snake convolutional layer is introduced to detect elongated scratches where conventional convolutional kernels fail to extract features effectively. …”
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A New Approach for Clustered MCs Classification with Sparse Features Learning and TWSVM by Xin-Sheng Zhang

“…We formulate this classification problem as sparse feature learning based classification on behalf of the test samples with a set of training samples, which are also known as a “vocabulary” of visual parts. …”
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DISEASES OF THE GENITOURINARY SYSTEM IN HIV INFECTION–A NEW PROBLEM OF MODERN UROLOGY by S. K. Yarovoy

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Method for extracting ship shaft rate features by fusing acoustic and magnetic field by Taotao Xie, Qing Ji, Peng Yu, Jiawei Zhang

“…Abstract To address the challenge of detecting small underwater targets, this paper proposes a detection method based on the fusion of acoustic and magnetic fields. …”
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Features of the development and clinical course of pneumothorax in patients with a new coronavirus infection by K. V. Medvedev, K. E. Borta, M. A. Protchenkov, E. I. Valyukh

“…New coronavirus infection (COVID-19) is a modern global problem that requires the rapid development of diagnostic and treatment methods, as well as the study of pathological effects on body tissues. …”
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Encrypted malicious traffic detection based on neural network by Xia Longfei, Zhang Qihao, Wu Xianyun, Zhu Xuetian, Gu Xin, Tian Min

“…A scalable window self-attention mechanism is designed, and the Transfomer neural network model is used to classify feature maps, achieving efficient detection of malicious traffic.Experimental results show that this method performs well in detection accuracy, recall rate, and model robustness, and provides a feasible solution to the problem of malicious behavior detection in encrypted traffic.…”
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Improved printed circuit board defect detection scheme by Lufeng Bai, Wen Hao Xu

“…Abstract In this paper, an improved printed circuit board(PCB)defect detection scheme named PD-YOLOv8 is proposed, which is specialized in the common and challenging problem of small target recognition in PCB inspection. …”
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Algorithm for Recognition of Small Air Targets by Trajectory Features in Passive Bistatic Radar by Dao Van Luc, A. A. Konovalov, Le Minh Hoang

“…Development of an algorithm for recognizing small air targets by trajectory features based on machine learning. Implementation and evaluation of the quality of decision-making methods in a given recognition problem.   …”
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Small target detection algorithm based on SAHI-Improved-YOLOv8 for UAV imagery: A case study of tree pit detection by Xiuhao Liang, Jun Xiang, Sheng Qin, Yundan Xiao, Lifen Chen, Dongxia Zou, Honglun Ma, Dong Huang, Yongxin Huang, Wei Wei

“…The application of deep learning in tree pit detection of unmanned aerial vehicle (UAV) images has problems such as dense distribution, high density, small size, false detections, missed detections, and high localization error. …”
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Semantic Features-Based Discourse Analysis Using Deceptive and Real Text Reviews by Husam M. Alawadh, Amerah Alabrah, Talha Meraj, Hafiz Tayyab Rauf

“…The final results indicate that semantically aware features inspire more confidence to detect deception in text.…”
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Optical-Theorem-Based Holography for Target Detection and Tracking by Mohammadrasoul Taghavi, Edwin A. Marengo

“…The development of robust, real-time optical methods for the detection and tracking of particles in complex, multiple-scattering media is a problem of practical importance in a number of fields, including environmental monitoring, air quality assessment, and homeland security. …”
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Time synchronization attack detection for industrial wireless network by Sichao ZHANG, Wei LIANG, Xudong YUAN, Yinlong ZHANG, Meng ZHENG

“…High-precision time synchronization is the basis for ensuring the secure and reliable transmission of industrial wireless network (IWN).Delay attacks, as a class of time synchronization attacks which cannot be solved by cryptographic techniques, seriously threaten the secure operation of IWN.Firstly, based on the in-depth analysis on the time synchronization mechanisms of IWN, three-time synchronization attack models were proposed, including the one-way full life cycle delay attack, two-way full life cycle delay attack, and one-way non-full-life cycle delay attack.Stealthier delay attacks could be realized by the attack models under the premise that target nodes were not captured.Secondly, considering the problem that existing detection algorithms are difficult to detect stealthier delay attacks without obvious changes in time features, an attack detection algorithm based on a Bayesian model was proposed that extracts four representative features, including transmission rate, transmission delay, transmission success rate and time synchronization interval.In addition, in order to ensure the accuracy of the attack detection and classification in the presence of noise interference, the noise model of wireless channel was introduced to the Bayesian feature information matrix.Experimental results show that the proposed algorithm can effectively detect three kinds of attacks in the presence of noise.…”
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Time synchronization attack detection for industrial wireless network by Sichao ZHANG, Wei LIANG, Xudong YUAN, Yinlong ZHANG, Meng ZHENG

“…High-precision time synchronization is the basis for ensuring the secure and reliable transmission of industrial wireless network (IWN).Delay attacks, as a class of time synchronization attacks which cannot be solved by cryptographic techniques, seriously threaten the secure operation of IWN.Firstly, based on the in-depth analysis on the time synchronization mechanisms of IWN, three-time synchronization attack models were proposed, including the one-way full life cycle delay attack, two-way full life cycle delay attack, and one-way non-full-life cycle delay attack.Stealthier delay attacks could be realized by the attack models under the premise that target nodes were not captured.Secondly, considering the problem that existing detection algorithms are difficult to detect stealthier delay attacks without obvious changes in time features, an attack detection algorithm based on a Bayesian model was proposed that extracts four representative features, including transmission rate, transmission delay, transmission success rate and time synchronization interval.In addition, in order to ensure the accuracy of the attack detection and classification in the presence of noise interference, the noise model of wireless channel was introduced to the Bayesian feature information matrix.Experimental results show that the proposed algorithm can effectively detect three kinds of attacks in the presence of noise.…”
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Automatic Fall Risk Detection Based on Imbalanced Data by Yen-Hung Liu, Patrick C. K. Hung, Farkhund Iqbal, Benjamin C. M. Fung

“…In this paper, we propose a pose estimation-based fall detection algorithm to detect fall risks. We use body ratio, acceleration and deflection as key features instead of using the body keypoints coordinates. …”
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Application of deep learning in malware detection: a review by Yafei Song, Dandan Zhang, Jian Wang, Yanan Wang, Yang Wang, Peng Ding

“…Future researchers will benefit from this review by better understanding current deep learning models in the field of malware detection. The review includes common methods such as convolutional neural networks, recurrent neural networks and generative adversarial networks, focusing on feature extraction techniques such as sequence features, image visualization and data enhancement. …”
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Center-Guided Network with Dynamic Attention for Transmission Tower Detection by Xiaobin Li, Zhuwei Liang, Jingbin Yang, Chuanlong Lyu, Yuge Xu

“…To address these problems, we propose the Center-Guided network with Dynamic Attention (CGDA) for detecting TTs from aerial images. …”
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Current Problems of the Forensic Analysis of Handwriting and Signatures Made with Modern Technical Means by N. A. Rybalkin

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Application of artificial intelligence in ophthalmology for solving the problem of semantic segmentation of fundus images by N.S. Demin, N.Y. Ilyasova, R.A. Paringer, D.V. Kirsh

“…Basic problems of using the neural network approach in biomedicine are formulated. …”
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