Application of spectral characteristics of electrocardiogram signals in sleep apnea by Jiayue Hu, Liu Yang, Xintong Zhao, Haicheng Wei, Jing Zhao, Miaomiao Li

“…The random forest classifier achieved optimal performance, with 92.9% accuracy, 86.6% specificity, and 100% sensitivity.ConclusionThis study demonstrates that spectral features derived from single-lead ECG signals, combined with EEMD-ICA and time-frequency analysis, offer an efficient and accurate method for sleep apnea detection.…”
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Milling Tool Wear State Recognition by Vibration Signal Using a Stacked Generalization Ensemble Model by Yang Hui, Xuesong Mei, Gedong Jiang, Tao Tao, Changyu Pei, Ziwei Ma

“…In this study, vibration signals collected during the milling process are analyzed through the time domain, frequency domain, and time-frequency domain to extract signal features. …”
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Application of Ontology Matching Algorithm Based on Linguistic Features in English Pronunciation Quality Evaluation by Shan Zhu

“…Thanks to the continuous advancement of speech processing technology, computer-assisted language learning systems are becoming more intelligent, not only pointing out learners’ pronunciation errors but also assessing their overall pronunciation level. Method. This paper uses the method of tree kernel function to measure the similarity of two ontology trees. …”
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User authentication of industrial internet based on HHT transform of mouse behavior by Yigong ZHANG, Qian YI, Jian LI, Congbo LI, Aijun YIN, Shuping YI

“…The rapid development of the industrial internet had caused widespread concern about the network security, and the end-user authentication technology was considered a research hotspot.According to the characteristics of human-computer interaction in industrial internet, an experimental website was designed.24 users' mouse behavior data in an uncontrolled environment were collected within 2.5 years to conduct case studies.Hilbert-Huang transform (HHT) was used to extract frequency domain features of mouse behavior signals, combined with time domain features to form a time-frequency joint domain feature matrix of 163-dimensional to characterize user mouse behavior patterns.Bagged tree, support vector machine (SVM), Boost tree and K-nearest neighbor (KNN) were used to build a user authentication model， and the comparison result showed that the Bagged tree had the best internal detection effect in this case, with an average false acceptance rate (FAR) of 0.12% and an average false rejection rate (FRR) of 0.28%.In external detection, the FAR was 1.47%.Compared with the traditional mouse dynamics method, the frequency domain information of mouse behavior extracted by HHT can better realize the user authentication, and provide technical support the security of the industrial internet.…”
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Communication emitter individual identification based on 3D-Hibert energy spectrum and multi-scale fractal features by Jie HAN, Tao ZHANG, Huan-huan WANG, Dong-fang REN

“…For communication emitter identification,a novel method based on Hilbert-Huang transform (HHT) and multi-scale fractal features was proposed.First,the time frequency energy spectrum was derived via HHT,which was called a complicated curved surface in the three-dimension space,namely,3D-Hilbert energy spectrum.Then,the differential box dimension and the multi-fractal dimension was extracted to compose the feature vector under multi-scale segmentation using fractal theory.Finally,communication emitter individual identification was obtained using the two dimensions of features above and the support vector machine (SVM).Moreover,the novel method was compared with two existing methods to identify simulated and actual signals with different and the same modulation modes,respectively.Results show that the identification rate of the novel method is higher than that of the two other methods.The features extracted by the novel method have high stability,sufficiency,and identifiability,also outweigh the negative effects of the change of signal-to-noise ratio and the number of training samples and emitters.…”
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BEARING DEGRADATION STATE IDENTIFICATION OF LCD-HILBERT RELATIVE SPECTRUM ENTROPY by CHEN HuiHong

“…The practical vibration of bearing with inner race fault and outer race fault which in different degradation state are analyzed, and the support vector machine is further used to identification degradation state and the results demonstrate the ability of the proposed method.…”
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MFF: A Deep Learning Model for Multi-Modal Image Fusion Based on Multiple Filters by Yuequn Wang, Zhengwei Li, Jianli Wang, Leqiang Yang, Bo Dong, Hanfu Zhang, Jie Liu

“…The method involving low-frequency feature correlation and high-frequency feature non-correlation was used for image training and fusion purposes. …”
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Reversible Spectral Speech Watermarking with Variable Embedding Locations Against Spectrum-Based Attacks by Xuping Huang, Akinori Ito

“…In this paper, we focus on the digital watermarking method as a promising method to safeguard the authenticity of audio evidence. …”
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Antenna Optimization Design Based on Deep Gaussian Process Model by Xin-Yu Zhang, Yu-Bo Tian, Xie Zheng

“…When using Gaussian process (GP) machine learning as a surrogate model combined with the global optimization method for rapid optimization design of electromagnetic problems, a large number of covariance calculations are required, resulting in a calculation volume which is cube of the number of samples and low efficiency. …”
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Influence of the Inter Teeth Volumes on the Noise Generation in External Gear Pumps by Wiesław FIEBIG

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石膏墙板螺杆挤压机溢流加料情况下输送量与螺杆转速的关系研究 by 朱桂华, 李志鹏, 薛洋, 何将三

“…Gesso wallboard screw extrusion machine is the key parts of gesso product line,to achieve enough extrusion mete,overfill adding method is adopted. …”
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Seismic Attribute Extraction and Application Based on the Gabor Wavelet Transform by Ran Xiong, Xuri Huang, Liang Guo, Xuan Zou, Haonan Tian

“…This can be captured by machine learning and deep learning methods to stratigraphic segmentation as many people investigated in industry. …”
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A data driven approach using local measurements to locate turbine governors causing forced oscillations by Sigurd Hofsmo Jakobsen, Xavier Bombois, Santiago Sanchez Acevedo, Hallvar Haugdal, Salvatore D’Arco

“…We investigate how the method performs under different process noise levels and also the common assumption that frequency measurements are a sufficient approximation of the machine’s rotational speed. …”
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Vowel classification with combining pitch detection and one‐dimensional convolutional neural network based classifier for gender identification by Chia‐Hung Lin, Hsiang‐Yueh Lai, Ping‐Tzan Huang, Pi‐Yun Chen, Chien‐Ming Li

“…The Yet Another Algorithm for Pitch Tracking (YAAPT)‐based PD method was designed to extract the voice fundamental frequency (F0) from non‐stationary speaker's voice signals, allowing us to achieve gender identification, by distinguishing differences in F0 between adult females and males, and classify voices into adult and children groups. …”
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Guidance Preconditioning by an Impulse Sequence for Robust Residual Vibration Suppression by I. Antoniadis

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Predicting the Toxicity of Drug Molecules with Selecting Effective Descriptors Using a Binary Ant Colony Optimization (BACO) Feature Selection Approach by Yuanyuan Dan, Junhao Ruan, Zhenghua Zhu, Hualong Yu

“…Only those high-frequency features are used to train a support vector machine (SVM) and construct the structure–activity relationship (SAR) prediction model. …”
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Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

“…First, we applied preprocessing, Term Frequency-Inverse Document Frequency feature extraction methods, and then applied classification algorithms. …”
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A synergistic approach for enhanced eye blink detection using wavelet analysis, autoencoding and Crow-Search optimized k-NN algorithm by M. Chandralekha, N. Priyadharshini Jayadurga, Thomas M. Chen, Mithileysh Sathiyanarayanan, Kasif Saleem, Mehmet A. Orgun

“…This optimization method actively samples the search space to balance exploration and exploitation to identify the optimal configuration for the model. …”
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APPLICATION OF IMPROVED EXPERIENCE WAVELET TRANSFORM IN FAULT DIAGNOSIS OF WIND TURBINE GEARBOX by HU Xuan, LI Chun, YE KeHua

“…Finally, a feature vector set is formed and input to the support vector machine for fault diagnosis. The results show that the CASNEWT method retains the advantages of the EWT algorithm, which can effectively avoid the modal aliasing effect and the end effect, while greatly improving the robustness of the EWT decomposition algorithm to noise, removes the noise and retains the original signal characteristic information. …”
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Diagnosis of the Misaligned Faults of the Vertical Test Instrument of High-Precision Industrial Robot Reducer by Zhen Yu, Yuan Zhang

“…The combination of components at the rotation frequency (fr) and the additional components can be used to diagnose faults due to coupling misalignment.…”
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