CNN-Transformer-BiGRU: A Pump Fault Detection Model for Industrialized Recirculating Aquaculture Systems by Wei Shao, Chengquan Zhou, Dawei Sun, Chen Li, Hongbao Ye

“…Methods: It first uses the continuous wavelet transform to convert one-dimensional vibration signals into time–frequency images for input into a CNN to extract the time-domain and frequency-domain features. …”
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Graph Learning-Based Power System Health Assessment Model by Koji Yamashita, Nanpeng Yu, Evangelos Farantatos, Lin Zhu

“…To improve computational efficiency, this paper develops machine learning models with phasor measurement unit (PMU) data to monitor the power system health index, focusing on rotor angle stability and frequency stability. …”
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A Novel Multiscale Deep Health Indicator with Bidirectional LSTM Network for Bearing Performance Degradation Trend Prognosis by Han Wang, Gang Tang, Youguang Zhou, Yujing Huang

“…This paper proposes a novel strategy for bearing performance degradation trend prognosis, including health indicator construction techniques and a performance degradation trend prediction method. To more accurately represent the degradation trend, the multiscale deep bottleneck health indicator is proposed as a new synthesized health indicator to remove high-frequency detail signals from features, which can reduce possible fluctuations in conventional synthetic health indicators. …”
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Active Power Oscillation Property Classification of Electric Power Systems Based on SVM by Ju Liu, Wei Yao, Jinyu Wen, Haibo He, Xueyang Zheng

“…Twenty sampling points of the envelope curve are selected as the feature matrices to train and test the supporting vector machine (SVM). The tests on the 16-machine 68-bus benchmark power system and a real power system in China indicate that the proposed oscillation classification method is of high precision.…”
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Design and Evaluation of a Leader–Follower Isomorphic Vascular Interventional Surgical Robot by Pengfei Chen, Yutang Wang, Dapeng Tian

“…We classified operators with different operational experience using machine learning methods. The classification process includes time-frequency domain feature extraction, feature selection based on the Relief method and random forest (RF) method, and a BP neural network (NN) classifier. …”
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Deep Learning-Based Feature Extraction Technique for Single Document Summarization Using Hybrid Optimization Technique by Jyotirmayee Rautaray, Sangram Panigrahi, Ajit Kumar Nayak, Premananda Sahu, Kaushik Mishra

“…The proposed approach’s results were compared with existing methods, including CSO, QABC, PSO, GJO, FF, and machine learning techniques like SVM and RF. …”
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Improving Legibility of Motor Current Spectrum for Broken Rotor Bars Fault Diagnostics by Asad Bilal, Vaimann Toomas, Kallaste Ants, Rassõlkin Anton, Belahcen Anouar, Iqbal M. Naveed

“…The line current is calculated and frequency spectrum is investigated to segregate the spatial and fault frequencies using the proposed technique. …”
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A spatiotemporal learning approach to safety‐oriented individualized driving risk assessment in a vehicle‐to‐everything (V2X) environment by Jing Li, Xuantong Wang, Tong Zhang

“…This approach formulates a bi‐level risk indicator: one level measures the observable frequency of SCEs, while the other estimates their likelihood. …”
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The Acoustic Cue of Fear: Investigation of Acoustic Parameters of Speech Containing Fear by Turgut ÖZSEVEN

“…Speech emotion recognition is an important part of human-machine interaction studies. The acoustic analysis method is used for emotion recognition through speech. …”
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Building Equi-Width Histograms on Homomorphically Encrypted Data by Dragoș Lazea, Anca Hangan, Tudor Cioara

“…Histograms are widely used for summarizing data distributions, detecting anomalies, and improving machine learning models’ accuracy. However, traditional histogram-based methods require access to raw data, raising privacy concerns, particularly in sensitive IoT applications. …”
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Cycle Time-Based Fault Detection and Localization in Pneumatic Drive Systems by Vladimir Boyko, Jürgen Weber

“…The applicability of the proposed method and its detection limits in an industrial environment are examined using pneumatic assembly machines.…”
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Graphs Constructed from Instantaneous Amplitude and Phase of Electroencephalogram Successfully Differentiate Motor Imagery Tasks by Maliheh Miri, Vahid Abootalebi, Hamid Saeedi-Sourck, Dimitri Van De Ville, Hamid Behjat

“…To determine the most discriminative subspace, an exploratory analysis was conducted in the spectral domain of the graphs by ranking the graph frequency components using a feature selection method. …”
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Driving Intention Recognition of Electric Wheel Loader Based on Fuzzy Control by Qihuai Chen, Yuanzheng Lin, Mingkai Xu, Haoling Ren, Guanjie Li, Tianliang Lin

“…The working condition of the wheel loader is significantly different from that of the passenger car, with a high shifting frequency and severe load fluctuation. The driving intention recognition method of passenger cars is difficult to transplant directly. …”
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Error effect of executive elements movement of the lathe tool on forming motion paths by Vilor L. Zakovorotny, Valery E. Gvindzhiliya

“…Introduction. Any metal-cutting machine has errors of the executive elements movement depending on its geometric accuracy and state. …”
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Sound-Based Unsupervised Fault Diagnosis of Industrial Equipment Considering Environmental Noise by Jeong-Geun Lee, Kwang Sik Kim, Jang Hyun Lee

“…The influence of environmental noise is generally excluded during research on machine fault diagnosis using acoustic signals. This study proposes a fault diagnosis method using a variational autoencoder (VAE) and domain adaptation neural network (DANN), both of which are based on unsupervised learning, to address this problem. …”
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Metric-Based Few-Shot Learning With Triplet Selection for Adaptive GNSS Interference Classification by Felix Ott, Lucas Heublein, Tobias Feigl, Alexander Rugamer, Christopher Mutschler

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Multi-dimensional feature extraction of EEG signal and its application in stroke classification by Teng Wang, Wenhui Jia, Fenglian Li, Xirui Liu, Xueying Zhang, Fengyun Hu

“…Abstract Feature extraction based on EEG signals and construction of classification models using machine learning methods are key to intelligent assisted diagnosis of brain diseases (such as stroke classification). …”
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Exploring weft knit fabric defects based on their presence and quality impact: A case study by A. K. M. Mobarok Hossain, Md Imranul Islam

“…Quality data of single jersey, fleece and 1X1 rib were gathered and analyzed from an established knitting factory in Bangladesh over three months duration. A fabric inspection machine and 4-point inspection method were employed in this study. …”
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Reactor fault diagnosis based on common feature of multivariate vibration sequences by FU Ming, ZHU Ming, MEI Jie, ZHANG Jing, XIAO Li, ZHANG Zongxi

“…We construct the feature pool from the time domain, frequency domain and time-frequency domain. For single vibration sequences, we rank the features and select features preliminarily by SVM-RFE. …”
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Performance Analysis and Operation Parameter Optimization of Shaker-Type Harvesting for Camellia Fruits by Qiaoming Gao, Jianfeng Han, Shan Zeng, Yu Wang, Wei Wei, Dongxue Wang, Hang Ye, Jing Lu, Haoxiang Zeng

“…To this end, a dynamic model of the camellia osmantha tree and a self-developed shaker-type harvesting machine were used as research subjects. The first 24 natural frequencies and mode shapes of the camellia tree were solved using the finite element method, and the effects of vibration frequency, excitation position, and vibration duration on the harvesting rate and flower bud damage rate were quantitatively analyzed through an orthogonal experiment. …”
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