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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Analytical Methods and Determinants of Frequency and Severity of Road Accidents: A 20-Year Systematic Literature Review by Carlos M. Ferreira-Vanegas, Jorge I. Vélez, Guisselle A. García-Llinás

“…In this systematic literature review (SLR), we use a series of quantitative bibliometric analyses to (1) identify the main papers, journals, and authors of the publications that make use of statistical analysis (SA) and machine learning (ML) tools as well as technological elements of smart cities (TESC) and Geographic Information Systems to predict road traffic accidents (RTAs); (2) determine the extent to which the identified methods are used for the analysis of RTAs and current trends regarding their use; (3) establish the relationship between the set of variables analyzed and the frequency and severity of RTAs; and (4) identify gaps in method use to highlight potential areas for future research. …”
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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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Impact of Alarm Frequency on Dialysis Adequacy using Online Clearance Monitor System in Haemodialysis Machine: A Cross-sectional Study by S Swadeeshwaran, P Hemanth, Aksa Shibu

“…Alarms frequently interrupt treatments, making it important to understand the relationship between alarm frequency and dialysis adequacy (Kt/V). Aim: To evaluate the impact of HD machine alarm frequency on dialysis adequacy using the Online Clearance Monitor (OCM). …”
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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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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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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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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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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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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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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We investigated the impact of using different feature extraction (spectro‐temporal measurements, linear and Mel‐frequency cepstral coefficients (MFCC), as well as highly comparative time‐series analysis) and classification methods (discriminant function analysis, neural networks, random forests (RF), and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. …”
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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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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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Ultrasonic-vibration-assisted reflow machining of ceramic gels by Junyan Mao, Shunzo Shimai, Haohao Ji, Jian Zhang, Xiaojian Mao, Shiwei Wang

“…This paper presents a novel ultrasonic vibration-assisted machining method for ceramic gels (wet green bodies), aiming to overcome the limitations of conventional ceramic machining methods, which often cause defects such as chipping and cracking owing to the low strength of dried green bodies and the brittleness of pre-sintered and sintered ceramics. …”
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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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A Machine Vision Perspective on Droplet‐Based Microfluidics by Ji‐Xiang Wang, Hongmei Wang, Huang Lai, Frank X. Liu, Binbin Cui, Wei Yu, Yufeng Mao, Mo Yang, Shuhuai Yao

“…This method enables rapid and precise detection (detection relative error < 4% and precision > 94%) across various scales and scenarios, including real‐world and simulated environments. …”
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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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