A CNN-LSTM Phase Compensation Method for Unidirectional Two-way Radio Frequency Transmission System by Jiahui Cheng, Zhengkang Wang, Yaojun Qiao, Hao Gao, Chenxia Liu, Zhuoze Zhao, Jie Zhang, Baodong Zhao, Bin Luo, Song Yu

“…This is the first-time machine learning (ML) has been used to mitigate the effects of optical path asymmetry caused by temperature variations on radio frequency (RF) transmission systems. …”
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Noise Source Identification of the Carpet Tufting Machine Based on the Single Channel Blind Source Separation and Time-Frequency Signal Analysis by Xiaowei Sheng, Xiaoyan Fang, Yang Xu, Yize Sun

“…Noise source identification is the first key step to reduce the noise pressure level of the carpet tufting machine. For identifying the main noise sources of the carpet tufting machine, the single channel blind source separation (SCBSS) method is proposed to separate the acquired single channel noise, and the time-frequency signal analysis is applied to identify separated noise components. …”
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Simulation-Based Design and Machine Learning Optimization of a Novel Liquid Cooling System for Radio Frequency Coils in Magnetic Hyperthermia by Serhat Ilgaz Yöner, Alpay Özcan

“…This study proposes novel liquid cooling systems, leveraging the skin effect phenomenon, to improve thermal management and reduce coil size. Finite element method-based simulation studies evaluated coil electrical current and temperature distributions under varying applied frequencies, water flow rates, and cooling microchannel dimensions. …”
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Feasibility of real-time compression frequency and compression depth assessment in CPR using a “machine-learning” artificial intelligence tool by Hannes Ecker, Niels-Benjamin Adams, Michael Schmitz, Wolfgang A. Wetsch

“…This study explores the feasibility of incorporating an open-source “machine-learning” tool (artificial intelligence – AI), to evaluate the feasibility and accuracy in correctly detecting the actual compression frequency and compression depth in video footage of a simulated CPR. …”
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Frequency and Nutrient Content of Meals of the Mothers and the Birth Weight and Gestational Age of the Baby by Avinash H. Salunkhe, Asha Pratinidhi, Jyoti A. Salunkhe, S. V. Kakade, Vaishali R. Mohite, Prabhu Hiremath

“…A sub sample of 380 women was taken for the in-depth study of frequency of meals and nutrient content of food of pregnant women. …”
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What factors enhance students' achievement? A machine learning and interpretable methods approach. by Hui Mao, Ribesh Khanal, ChengZhang Qu, HuaFeng Kong, TingYao Jiang

“…Through interpretable AI techniques, we identify several key patterns: (1) Machine learning with explainability methods effectively reveals nuanced factor-achievement relationships; (2) Behavioral metrics (hw_score, ans_score, discus_score, attend_score) show consistent positive associations; (3) High-achievers demonstrate both superior collaborative skills and preference for technology-enhanced environments; (4) Gamification frequency (s&v_num) significantly boosts outcomes; while (5) Assignment frequency (hw_num) exhibits counterproductive effects. …”
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Machine learning-based inertia estimation in power systems: a review of methods and challenges by Santosh Diggikar, Arunkumar Patil, Siddhant Satyapal Katkar, Kunal Samad

“…This shift has significantly reduced rotational inertia, increasing the system’s vulnerability to frequency fluctuations during disturbances. Consequently, the accurate and adaptive estimation of inertia has become crucial for maintaining frequency stability and grid reliability. …”
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Discriminating and classifying odontocete echolocation clicks in the Hawaiian Islands using machine learning methods. by Morgan A Ziegenhorn, Kaitlin E Frasier, John A Hildebrand, Erin M Oleson, Robin W Baird, Sean M Wiggins, Simone Baumann-Pickering

“…This study shows how a machine learning toolkit can effectively mitigate this problem by detecting and classifying echolocation clicks using a combination of unsupervised clustering methods and human-mediated analyses. …”
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Acoustic response discrimination of phulae pineapple maturity and defects using factor analysis of mixed data and machine learning algorithms by Sujitra Arwatchananukul, Saowapa Chaiwong, Nattapol Aunsri, Sila Kittiwachana, Kietsuda Luengwilai, Tatiya Trongsatitkul, Pramod Mahajan, Jose Blasco, Rattapon Saengrayap

“…Acoustic response is non-destructive evaluation technique that replicates the conventional method for determining maturity by tapping the fruit. …”
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Analysis of Demographic, Familial, and Social Determinants of Smoking Behavior Using Machine Learning Methods by Joanna Chwał, Małgorzata Kostka, Paweł Stanisław Kostka, Radosław Dzik, Anna Filipowska, Rafał Jan Doniec

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Anomaly Detection Method With Rebar Response Suppression for Microwave Ground Penetrating Radar Pavement Inspection by Natsuki Akiyama, Takahide Morooka, Katsuyoshi Suzuki, Shouhei Kidera

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Segmental multi-frequency bioelectrical impedance analysis indicates dehydration status after exercise by Shuang Wang, Pengfei Zhang, Yang Hu, Yao Zheng, Hongyan Yang, Jiaheng Zhou, Xuyun Liu, Jie Xu, Hui Li, Yang Liu, Jia Li, Xing Zhang, Jing Lou, Ling Dong, Guiling Wu

“…Methods: A total of 43 young adults were recruited. …”
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Photovoltaic Array Fault Diagnosis and Localization Method Based on Modulated Photocurrent and Machine Learning by Yebo Tao, Tingting Yu, Jiayi Yang

“…To address this concern, this paper proposes a fault identification and localization approach for photovoltaic arrays based on modulated photocurrent and machine learning. By irradiating different frequency-modulated light, this method separates photocurrent and directly measures the photoelectric conversion efficiency of each panel, achieving both high accuracy and localization. …”
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Enhancing Low Frequency Oscillations Damping of a Power System by a TCSC Controlled with Sliding Mode Method by Hossein Amootaghi, Shahrokh Shojaeian, Ehsan Salleala Naeini

“…In this paper, sliding mode control is applied for improving the low frequency oscillations damping of a single machine connected to an infinite bus. …”
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Grouped machine learning methods for predicting rock mass parameters in a tunnel boring machine‐driven tunnel based on fuzzy C‐means clustering by Ruirui Wang, Yaodong Ni, Lingli Zhang, Boyang Gao

“…Based on fuzzy C‐means clustering, this paper proposes a grouped machine learning method for predicting rock mass parameters. …”
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A Decomposition-Integration Framework of Carbon Price Forecasting Based on Econometrics and Machine Learning Methods by Zhehao Huang, Benhuan Nie, Yuqiao Lan, Changhong Zhang

“…First, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is employed to decompose carbon price data into distinct modal components, each defined by specific frequency characteristics. …”
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Prediction of Parkinson Disease Using Long-Term, Short-Term Acoustic Features Based on Machine Learning by Mehdi Rashidi, Serena Arima, Andrea Claudio Stetco, Chiara Coppola, Debora Musarò, Marco Greco, Marina Damato, Filomena My, Angela Lupo, Marta Lorenzo, Antonio Danieli, Giuseppe Maruccio, Alberto Argentiero, Andrea Buccoliero, Marcello Dorian Donzella, Michele Maffia

“…A dataset comprising 81 voice samples (41 from healthy individuals and 40 from PD patients) was utilized to train and evaluate common machine learning (ML) models using various types of features, including long-term (jitter, shimmer, and cepstral peak prominence (CPP)), short-term features (Mel-frequency cepstral coefficient (MFCC)), and non-standard measurements (pitch period entropy (PPE) and recurrence period density entropy (RPDE)). …”
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Micro-electrical Discharge Machining of Micro-holes Based on Integrated Orthogonal Experiments and CNN Methods by Yuandong MO, Yazhi WANG, Shuqi HUANG, Jiajun ZHONG

“…For the taper angle in micro-hole machining, the hierarchy is feed rate, pulse duty cycle, spindle speed, and pulse frequency, and the optimal combination parameters is a feed rate of 0.05 mm/s, a spindle speed of 1 500 r/min, a pulse duty cycle of 60%, and a pulse frequency of 3 000 Hz. …”
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Under frequency load shedding aware unit commitment in island power systems by Miad Sarvarizadeh, Mohammad Rajabdorri, Enrique Lobato, Lukas Sigrist, Behzad Kazemtabrizi, Matthias Troffaes

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A fully automated hybrid approach for processing high-frequency surface settlement data by Changyu Wang, Zude Ding, Annan Zhou, Zekun Zhu

“…The proposed method minimises manual intervention and reduces reliance on empirical design through the integration of the Mel Frequency Cepstral Coefficient (MFCC) based Convolutional Neural Networks (CNN), Extreme Learning Machine (ELM), and Variational Modal Decomposition (VMD) algorithms. …”
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