Dynamic Performance Analysis of High-Frequency Signal Injection Based Sensorless Methods for Interior Permanent Magnet Synchronous Motors by Ahmadreza Alaei, Dong Hee Lee, Jin woo Ahn, Sayed Morteza Saghaeian Nejad

“…Some efforts have been performed to compare such high frequency signal injection based methods from viewpoint of some parameters such as injection frequency, voltage magnitude and so on. …”
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Time-domain virtual tapping machine method for numerical evaluation of transient acoustic performance in cruise cabins by Yingying Zuo, Deqing Yang, Jian Xiao

“…In this paper, a general time-domain virtual tapping machine method for numerical evaluation of transient acoustic performance in cruise cabins is proposed. …”
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LEVERAGING MACHINE LEARNING METHODS IN PREDICTING AND ANALYZING THE ASSOCIATION BETWEEN DIETARY INFLAMMATORY INDEX AND ALOPECIA by Mohammed Sarwat M Salih, Hawal Lateef Fateh, Soran Abdulkarim Pasha, Hassan M Tawfiq

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Evaluating Factors Affecting Flood Susceptibility in the Yangtze River Delta Using Machine Learning Methods by Kaili Zhu, Zhaoli Wang, Chengguang Lai, Shanshan Li, Zhaoyang Zeng, Xiaohong Chen

“…This research developed an index system comprising 10 indicators associated with factors and environments that lead to disasters, and used machine learning methods to assess flood susceptibility. …”
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Analytical Frequency Security Indicators for Two-Region Interconnected Power Systems by Qiang Zhang, Xinwei Li, Guorong Lan, Xiangxu Wang, Jiakai Shen, Hui Zeng, Peng Yuan, Xiaoheng Zhang, Weidong Li

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High frequency resonance mitigation of microgrid-connected PV units using novel adaptive control based on virtual impedance and machine learning algorithm by Mohammad Hossein Nemati, Mohammad Hossein Shaabani, Navid Dehghan, Gevork B. Gharehpetian

“…This study proposes a novel adaptive control framework that combines virtual impedance (VI) methods with a machine learning-based tuning strategy using K-Nearest Neighbors (KNN) algorithm. …”
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Fault Diagnosis of a Hydraulic Pump Based on the CEEMD-STFT Time-Frequency Entropy Method and Multiclass SVM Classifier by Wanlin Zhao, Zili Wang, Jian Ma, Lianfeng Li

“…Second, the time-frequency analysis methods, which include the Short-Time Fourier Transform (STFT) and time-frequency entropy calculation, are applied to realize the robust feature extraction. …”
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MODAL ANALYSIS OF CARRIER SYSTEM FOR HEAVY HORIZONTAL MULTIFUNCTION MACHINING CENTER BY FINITE ELEMENT METHOD by Yu. V. Vasilevich, S. S. Dovnar, I. I. Shumsky

“…Modal FEM-analysis has revealed eight resonance modes that embrace the whole machine tool. They form a frequency interval from 12 to 75 Hz which is undesirable for machining. …”
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Shock Signal Trend Term Error Correction Method Based on Discrete Wavelet Transform and Low-Frequency Oscillator Combination by Peng Wang, Ming Yan, Lei Zhang, Ning Yang

“…A discrete wavelet transform (DWT) and low-frequency oscillator combination method is proposed for correcting shock signals in this paper. …”
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Time–Frequency-Domain Fusion Cross-Attention Fault Diagnosis Method Based on Dynamic Modeling of Bearing Rotor System by Shiyu Xing, Zinan Wang, Rui Zhao, Xirui Guo, Aoxiang Liu, Wenfeng Liang

“…Deep learning (DL) and machine learning (ML) have advanced rapidly. This has driven significant progress in intelligent fault diagnosis (IFD) of bearings. …”
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Identification of Elephant Rumbles in Seismic Infrasonic Signals Using Spectrogram-Based Machine Learning by Janitha Vidunath, Chamath Shamal, Ravindu Hiroshan, Udani Gamlath, Chamira U. S. Edussooriya, Sudath R. Munasinghe

“…It is experimentally found that the combination of the Mel-frequency cepstral coefficient (MFCC) feature extraction method and the ridge classifier machine learning algorithm give the highest accuracy of 97% in detecting infrasonic elephant rumbles hidden in seismic signals. …”
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Optimizing the primary stability of dental implants in type IV bone: in-vitro comparison of machine-driven and ratcheting insertion protocols by Nuri Mert Tayşi, Ayşegül Erten Tayşi, Pınar Erçal, Soner Şişmanoğlu

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Fault Diagnosis Method of Bearing based on LCD Cross Approximate Entropy and Relevance Vector Machine by Tan Jingjing, Gao Feng, Zhang Qiantu

“…Aiming at the fault diagnosis problem of rolling bearing,a fault diagnosis method of rolling bearing based on local characteristic-scale decomposition（LCD） cross approximate entropy（CAE） and relevance vector machine（RVM） is proposed. …”
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Intelligent Diagnosis Method for Centrifugal Pump System Using Vibration Signal and Support Vector Machine by Hongtao Xue, Zhongxing Li, Huaqing Wang, Peng Chen

“…This paper proposed an intelligent diagnosis method for a centrifugal pump system using statistic filter, support vector machine (SVM), possibility theory, and Dempster-Shafer theory (DST) on the basis of the vibration signals, to diagnose frequent faults in the centrifugal pump at an early stage, such as cavitation, impeller unbalance, and shaft misalignment. …”
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Research on CNC Machine Tool Spindle Fault Diagnosis Method Based on DRSN–GCE Model by Xiaoxu Li, Jiahao Wang, Jianqiang Wang, Jixuan Wang, Jiaming Chen, Xuelian Yu

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Channel-Wise Characterization of High Frequency Oscillations for Automated Identification of the Seizure Onset Zone by Dakun Lai, Xinyue Zhang, Wenjing Chen, Heng Zhang, Tongzhou Kang, Han Yuan, Lei Ding

“…High frequency oscillations (HFOs) in intracranial electroencephalography (iEEG) recordings are a promising clinical biomarker that can help define the epileptogenic regions in the brain. …”
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Functional Connectivity Metrics in Temporal Lobe Epilepsy: A Machine Learning Perspective With MEG by M. V. Suhas, N. Mariyappa, A. Karunakar Kotegar, M. Ravindranadh Chowdary, K. Raghavendra, Ajay Asranna, L. G. Viswanathan, H. Anitha, Sanjib Sinha

“…Various machine learning models demonstrate high classification performance, with accuracies reaching up to 100% in particular frequency bands in agreement with the Chi2 feature importance analysis. …”
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Diagnosis of Stator Inter-Turn Short Circuit Faults in Synchronous Machines Based on SFRA and MTST by Junsheng Ding, Zhongyong Zhao

“…Finally, the performance of the proposed method is tested and verified. It concludes that the proposed method has the potential for classifying and diagnosing the inter-turn short circuit of stators in synchronous machines.…”
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Ensemble Machine Learning Model Prediction and Metaheuristic Optimisation of Oil Spills Using Organic Absorbents: Supporting Sustainable Maritime by Le Quang Dung, Pham Duc, Bui Thi Anh Em, Nguyen Lan Huong, Nguyen Phuoc Quy Phong, Dang Thanh Nam

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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

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