Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment by Apiwat Ditthapron, Emmanuel O. Agu, Adam C. Lammert

“…Prior speech separation methods analyzed raw audio. However, in order to preserve speaker privacy, passively recorded smartphone audio and machine learning-based speech assessment are often performed on derived speech features such as Mel-Frequency Cepstral Coefficients (MFCCs). …”
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Prediction of soil chemical properties using multispectral satellite images and wavelet transforms methods by Chaitanya B. Pande, Sunil A. Kadam, Rajesh Jayaraman, Sunil Gorantiwar, Mukund Shinde

“…Now a day’s machine learning programming is an easy to applied on the natural resources and agriculture studies. …”
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Defining Disease Phenotypes in Primary Care Electronic Health Records by a Machine Learning Approach: A Case Study in Identifying Rheumatoid Arthritis. by Shang-Ming Zhou, Fabiola Fernandez-Gutierrez, Jonathan Kennedy, Roxanne Cooksey, Mark Atkinson, Spiros Denaxas, Stefan Siebert, William G Dixon, Terence W O'Neill, Ernest Choy, Cathie Sudlow, UK Biobank Follow-up and Outcomes Group, Sinead Brophy

“…A machine learning based scheme was used to identify patients with rheumatoid arthritis from primary care EHRs via the following steps: i) selection of variables by comparing relative frequencies of Read codes in the primary care dataset associated with disease case compared to non-disease control (disease/non-disease based on the secondary care diagnosis); ii) reduction of predictors/associated variables using a Random Forest method, iii) induction of decision rules from decision tree model. …”
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Multi-Physics Simulation of 6/4 Switched Reluctance Motor by Finite Element Method by Renata R. C. Reis, Marcio L. M. Kimpara, João O. P. Pinto, Babak Fahimi

“…Afterwards, the natural frequencies and vibration modes were found through modal analysis. …”
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Comparison of Eddy Current Loss Calculation Techniques for Axial Flux Motors with Printed Circuit Board Windings by Andreas Bauer, Daniel Dieterich, Sven Urschel

“…A recommendation is provided for the method that offers the best balance between accuracy and computation time for the early-stage design of slotless axial flux machines.…”
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Performance Evaluation of Different Speech-Based Emotional Stress Level Detection Approaches by Jan Stas, Stanislav Ondas, Jozef Juhar

“…Both conventional feature-based methods and deep learning techniques, including transfer and self-supervised learning, are explored in the experimental part of this research. …”
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Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study by Yang Z, Liang X, Ji Y, Zeng W, Wang Y, Zhang Y, Zhou F

“…After calculating the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), voxel-mirrored homotopic connectivity (VMHC) and degree centrality (DC) imaging, the radiomic features (n = 819) of bilateral hippocampi were extracted from these images, respectively. …”
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From reactive to proactive: Machine learning models for continuous positive airway pressure adjustments using heart rate variability and oximetry-related parameters by Chih-Fan Kuo, Yi-Chih Lin, Ze-Yu Chen, Jiunn-Horng Kang, Cheng-Chen Chang, Zhihe Chen, Arnab Majumdar, Yen-Ling Chen, Yi-Chun Kuan, Kang-Yun Lee, Po-Hao Feng, Kuan-Yuan Chen, Hsin-Chien Lee, Wun-Hao Cheng, Wen-Te Liu, Cheng-Yu Tsai

“…Methods CPAP titration data were first collected from a sleep center in northern Taiwan. …”
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UHVDC Transmission Line Fault Identification Method Based on Generalized Regression Neural Network by XIE Jia, LIU Feng, KE Yanguo, YIN Zhen, RUAN Wei, YAO Jinming

“…Compared to traditional convolutional neural networks, generalized regression neural networks, support vector machines, and other methods, the fault recognition accuracy of the proposed method in this paper has been improved by 6. 6% , 0. 65% , and 7. 69% , respectively, meeting the requirements of protection speed and reliability.…”
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Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals by Bangbei Tang, Bangbei Tang, Yan Li, Yingzhang Wu, Yilun Li, Qizong Yue

“…Time-frequency domain features, including mean, variance, skewness, kurtosis, root mean square, and power spectral density, were extracted and analyzed using classification algorithms such as Back Propagation Neural Networks (BPNN), K-Nearest Neighbors (KNN), and Support Vector Machines (SVM), enabling precise identification of varying levels of tension and anger. …”
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Modal Analysis of the Key Components of RV Reducer by Sun Yongsen, Zhou Yanfei, Yang Xiao, Zhang Xiang, Xia Tian

“…By using the finite element method,modal analysis is conducted to get the natural frequency and vibration mode at each order of the cycloidal gear and the pinwheel in two working conditions. …”
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Speech Databases, Speech Features, and Classifiers in Speech Emotion Recognition: A Review by G. H. Mohmad Dar, Radhakrishnan Delhibabu

“…It has been done in the past using low-level descriptors (LLDs) like Mel-Frequency Cepstral Coefficients (MFCCs), linear predictive coding (LPC), and pitch-based features in methods like Support Vector Machines (SVM), Random Forests (RF), and Gaussian Mixture Models (GMM). …”
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Optimasi Algoritma Support Vector Machine Berbasis Kernel Radial Basis Function (RBF) Menggunakan Metode Particle Swarm Optimization Untuk Analisis Sentimen by Cucun Very Angkoso, Khozainul Asror, Ari Kusumaningsih, Andi Kurniawan Nugroho

“…The study investigates the effectiveness of the Particle Swarm Optimization (PSO) method for balanced and unbalanced datasets and how well it improves sentiment analysis accuracy when applied to the Support Vector Machine (SVM) algorithm when using Radial Basis Function (RBF) kernel. …”
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Unsupervised machine learning-based multi-attributes analysis for enhancing gas channel detection and facies classification in the serpent field, offshore Nile Delta, Egypt by Shaimaa A. El-Dabaa, Farouk I. Metwalli, Ali Maher, Amir Ismail

“…In this study, the single attribute (spectral decomposition attribute) highlighted the gas channel spatial distribution using three distinct frequency magnitude values. Subsequently, we employ principal component analysis (PCA) as an attribute selection method, discovering that combining seismic attributes such as sweetness, envelope, spectral magnitude, and spectral voice as input for SOM reflects an effective method to determine facies. …”
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A Fault Identification Method of Mechanical Element Action Unit Based on CWT-2DCNN by Hongyu Ge, Yujiao Guo, Tianyu Luo, Manzhi Yang, Chuanwei Zhang

“…Aiming at the problems of low recognition rate and human intervention in the traditional fault diagnosis of mechanical equipment, a fault identification method based on continuous wavelet transform (CWT) and two-dimensional convolutional neural network (2DCNN) is proposed. …”
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SICNN: Soft Interference Cancellation Inspired Neural Network Equalizers by Stefan Baumgartner, Oliver Lang, Mario Huemer

“…We compare the bit error ratio performance of the proposed NN-based equalizers with state-of-the-art model-based and NN-based approaches, highlighting the superiority of SICNNv1 over all other methods for SC-FDE. Exemplarily, to emphasize its universality, SICNNv2 is additionally applied to a unique word orthogonal frequency division multiplexing (UW-OFDM) system, where it achieves state-of-the-art performance. …”
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Discriminating Types of Volcanic Electrical Activity: Toward an Eruption Detection Algorithm by S. A. Behnke, H. E. Edens, J. Theiler, D. J. Swanson, S. Senay, A. R. Van Eaton, M. Iguchi, D. Miki

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Automated Design Method Based on Boosting Algorithms for Improving the Radiation Performance of Microstrip Antenna Arrays by Sina Hasibi Taheri, Ali Lalbakhsh, Amirhassan Zareanborji, Slawomir Koziel

“…This paper presents an automated design methodology to improve the radiation performance of microstrip antenna arrays using boosting-based machine learning (ML) algorithms in the X-band frequency range. …”
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RESEARCH ON FAULT DIAGNOSIS METHOD OF ROLLING BEAR BASED ON SYMBOLIC ANALYSIS OF INTRINSIC MODE FUNCTION by HOU HePing, XU ZhuoFei, LIU Kai

“…And then realize the fault diagnosis with the help of some kind of pattern recognize method. The results show that there is a good recognition effect for typical bearing fault and printing machine fault. …”
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Source-Grid Coordinated Planning Considering Network Node Inertia Level Differences Under Coal-Fired Power Unit Retirement by Yutao Xu, Chao Sun, Lu Liu, Houyi Zhang, Wenxia Liu, Zhukui Tan

“…First, a frequency response model based on a multi-machine equivalence approach and a differentiated inertia level model based on a virtual synchronous machine transformation approach for each network node are established, and a node inertia constraint model can be obtained. …”
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