Analytical Inertia Identification of Doubly Fed Wind Farm with Limited Control Information Based on Symbolic Regression by Mengxuan Shi, Yang Li, Xingyu Shi, Dejun Shao, Mujie Zhang, Duange Guo, Yijia Cao

“…Finally, the effectiveness of the proposed method is validated in an IEEE three-machine nine-bus system containing a doubly fed wind power cluster. …”
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Research on a Visually Assisted Efficient Blind-Guiding System and an Autonomous Shopping Guidance Robot Arm Adapted to the Complex Environment of Farmers’ Markets by Mei Liu, Yunhua Chen, Jinjun Rao, Wojciech Giernacki, Zhiming Wang, Jinbo Chen

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DC Voltage Compensation and Anti-overlimit Control Strategy for Hybrid Energy Storage System of Virtual Synchronous Generator by LÜ Shixuan, WANG Wei, YANG Dongdong, LIU Zongwei, ZHENG Lijun

“…[Methods] The anti-overlimit control strategy utilizes the asymptotic nature of a hyperbolic tangent function to limit the maximum deviation of the DC voltage，and a linear correction coefficient is designed to ensure coupling linearity between the DC voltage and grid frequency. …”
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Design and Performance Analysis of Compliant Actuator Mechanism with Variable Stiffness by Liu Rong, Zheng Zhizhen, Qin Huibin, Li Zhongyi, Bai Shaoping

“…Through configuration analysis and structure design, the stiffness and torque models of the compliant actuator mechanism are established to reveal its stiffness behavior. The Lagrangian method is used to establish the dynamic model of the compliant actuator mechanism, and the frequency theoretical results are obtained by solving the average stiffness. …”
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An Efficient Quantized Message Passing Receiver Design for SCMA Systems by Hao Cheng, Min Zhang, Ruoyu Su

“…Simulation results show that the proposed quasi-uniform quantization method can significantly improve the BER performance of the SCMA decoder without modifying the resource nodes’ and variable nodes’ update rules in both the additive white Gaussian noise and the Rayleigh frequency selective channels, as compared to the uniform quantizer.…”
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Application of Fractional Fourier Transform and BP Neural Network in Prediction of Tumor Benignity and Malignancy by Xuanyu Liu, Nan Gao, Shuoran He, Lizhen Wang

“…Experimental results show that the proposed model achieves an accuracy of 93.177% in classifying benign and malignant tumors, outperforming the support vector machine (SVM) method. The integration of FrFT improves feature distinguishability and reduces dependence on manual extraction. …”
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Emerging Technologies of Natural Language-Enabled Chatbots: A Review and Trend Forecast Using Intelligent Ontology Extraction and Patent Analytics by Min-Hua Chao, Amy J. C. Trappey, Chun-Ting Wu

“…Some intelligent text-mining techniques are applied, including document term frequency analysis for key terminology extractions, clustering method for identifying the subdomains, and Latent Dirichlet Allocation for finding the key topics of patent set. …”
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Neural network eddy current non-destructive evaluation of conductive coatings thickness by ISLAM NACER EDDINE EL GHOUL, A.E. Lakhdari, S. Bensaid, S. Bensaid, A. Aissaoui, A.T. Ouamane

“…Two thousand and five hundred datasets with the eddy current method of different aluminum plate thicknesses above a steel plate and working frequencies of EC-sensor were generated using experimentally validated analytical models in our previous research. …”
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Road Event Detection and Classification Algorithm Using Vibration and Acceleration Data by Abiel Aguilar-González, Alejandro Medina Santiago

“…Traditional approaches often require complex feature engineering or the use of machine learning models, which can be computationally intensive, especially when dealing with real-time data from high-frequency vibration and acceleration sensors. …”
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LightGBM-Based Human Action Recognition Using Sensors by Yinuo Liu, Ziwei Chen

“…First, a feature extraction method for sensor data from both the time domain and frequency domain is designed to obtain more than 300 features, aiming to enhance the accuracy and stability of recognition. …”
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Music genre classification with parallel convolutional neural networks and capuchin search algorithm by Yuxin Zhang, Teng Li

“…The method makes use of discrete wavelet transform (DWT), mel frequency cepstral coefficients (MFCC), and short-time fourier transform (STFT) characteristics to provide a comprehensive framework for expressing stylistic qualities in music. …”
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Discriminative learning of receptive fields from responses to non-Gaussian stimulus ensembles. by Arne F Meyer, Jan-Philipp Diepenbrock, Max F K Happel, Frank W Ohl, Jörn Anemüller

“…Applied to small data samples, the method is shown to converge on smaller amounts of experimental recordings and with lower estimation variance than the generalized linear model and recent information theoretic methods. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD and SSAE by Baoxian Chang, Xing Zhao, Dawei Guo, Siyu Zhao, Jiyou Fei

“…To further enhance the accuracy of identifying rolling bearing faults, a fault diagnosis method is proposed. This method is based on the improved Dung Beetle Optimization (DBO) algorithm for optimizing Variational Mode Decomposition (VMD) combined with Stacked Sparse Autoencoder (SSAE). …”
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Multiple Feature Vectors Based Fault Classification for WSN Integrated Bearing of Rolling Mill by Bo Qin, Luyang Zhang, Heng Yin, Yan Qin

“…For rolling mill machines, the operation status of bearing has a close relationship with process safety and production effectiveness. …”
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Identification of Major Bleeding Events in Postoperative Patients With Malignant Tumors in Chinese Electronic Medical Records: Algorithm Development and Validation by Hui Li, Haiyang Yao, Yuxiang Gao, Hang Luo, Changbin Cai, Zhou Zhou, Muhan Yuan, Wei Jiang

“…Given the higher sensitivity of the LR method (89.47%) and the higher specificity of the CNN method (89.24%) in the test set, both models hold promise for practical application, depending on specific clinical priorities.…”
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Artificial intelligence for severity triage based on conversations in an emergency department in Korea by Jae Won Seo, Sung-Joon Park, Young Jae Kim, Jung-Youn Kim, Kwang Gi Kim, Young-Hoon Yoon

“…Based on the area under the receiver operating characteristic curve (AUROC) values, the support vector machine achieved the best performance among the term frequency-inverse document frequency-based conventional machine learning models with an AUROC of 0.764 (95% CI 0.019). …”
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Analysis and correcting pronunciation disorders based on artificial intelligence approach by Nataliia Melnykova, Bohdan Pavlyk, Oleh Basystiuk, Stepan Skopivskyi

“…The analysis of machine learning methods led to the selection of two experimental models: a Convolutional Neural Network (CNN) utilizing mel-spectrograms for image-based sound representation and a Long Short-Term Memory (LSTM) network combined with mel-frequency cepstral coefficients, aiming to explore the effectiveness of sequential data processing in the context of pronunciation disorder classification in post-traumatic military patients. …”
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CORPUS-BASED ANALYSIS OF TRANSITION WORDS by Satyawati Surya, M.Pd.

“…For this purpose, the researcher would like to find information about the frequency used among the transition words only. The researcher uses a sketch machine of BROWN Corpus to find the data. …”
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Research of clover-grater-and-scarificator KS-0.2 with oval type deck at seeds scarification by A. I. Burkov, M. V. Simonov, V. Ju. Mokiev

“…Determined the range of values of the studied parameters under which the observed agro technical requirements for the machine were met. As a result of research defined values are revealed of the constructive and technological parameters of the machine for extraction and scarification grass seed КБ-0.2 with the use of a oval type deck, providing the required quality parameters (degree of scarification of seeds higher than 95% and crushing of seeds less than 1.5%): frequency of rotation of the drum 850...950 min-1; productivity 0.2...0.3 t/h; clearances at the entrance - 6.0 mm, at the outlet - 3.0 mm.…”
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Recognition and classification techniques of marine mammal calls based on LSTM and expanded causal convolution by Wanlu Cheng, Wanlu Cheng, Hao Chen, Jiaming Jiang, Jiaming Jiang, Shuang Li, Shuang Li, Jingjing Wang, Jingjing Wang, Yanping Zhou

“…However, traditional machine learning methods struggle to capture complex acoustic patterns, while most existing deep learning approaches rely solely on frequency-domain features and require large datasets, which limits their performance on small-scale marine mammal datasets. …”
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