Investigating the Effects of Ground-Transmitted Vibrations from Vehicles on Buildings and Their Occupants, with an Idea for Applying Machine Learning by Marta Mikielewicz, Anna Jakubczyk-Gałczyńska, Robert Jankowski

“…The results of the study indicate that the proposed method of utilizing machine learning can be effectively applied for such purposes.…”
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Spatial sensitivity synthesis based on alternate projection for the machine‐learning‐based coding digital receiving array by Lei Xiao, Yubing Han, Shurui Zhang

“…Abstract Recently, a novel low‐cost coding digital receiving array based on machine learning (ML‐CDRA) has been proposed to reduce the required radio frequency channels in modern wireless systems. …”
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Adaptable Reduced-Complexity Approach Based on State Vector Machine for Identification of Criminal Activists on Social Media by Imran Shafi, Sadia Din, Zahid Hussain, Imran Ashraf, Gyu Sang Choi

“…The performance of the proposed method is evaluated against other popular feature selection/extraction algorithms like term frequency-inverse document frequency, Gini Index (GI), Chi square statistics, and PCA. …”
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Machine Learning Aided Resilient Spectrum Surveillance for Cognitive Tactical Wireless Networks: Design and Proof-of-Concept by Eli Garlick, Nourhan Hesham, MD. Zoheb Hassan, Imtiaz Ahmed, Anas Chaaban, MD. Jahangir Hossain

“…Conventional supervised machine learning (ML) algorithm’s capability to provide spectrum awareness is confronted by the requirement of labeled interference signals. …”
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Development of a High-Speed Precision Ultrasonic-Assisted Spindle for Ultra-Precision Optical Mold Machining by Dingwen Wang, Qiu Hong, Shaohui Yin

“…Ultrasonic vibration-assisted grinding is a critical method for machining ultra-hard optical molds. However, current ultrasonic-assisted grinding spindles, as essential foundational equipment, face limitations in maintaining ultra-high rotational speed, high precision, and a compact structure during ultrasonic operation. …”
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A New Fault Diagnosis Method of Rotating Machinery by Chih-Hao Chen, Rong-Juin Shyu, Chih-Kao Ma

“…An experimental study was performed to evaluate the proposed method and the results show that the method can effectively detect and recognize different kinds of faults of rotating machinery.…”
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A Numerical Systematic Review and Meta-Analysis of Diagnosing the Vibration Modes of the Cylindrical Shell in the MRI Machine by Hamidreza Mortazavy Beni, Fatemeh Aghaei, Ashkan Heydarian, Fatemeh Yekta Asaei, Hosein Samaram

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A machine learning optimized Dielectric Ultra-focused Oscillatory (DUO) electrode for low temperature electrosurgery by Bo H. Choi, Jun H. Heo, Min S. Kim, In S. Choi, Eun S. Lee

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Diagnosis of Encephalopathy Based on Energies of EEG Subbands Using Discrete Wavelet Transform and Support Vector Machine by Jisu Elsa Jacob, Gopakumar Kuttappan Nair, Thomas Iype, Ajith Cherian

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Evaluation of machine learning approaches for large-scale agricultural drought forecasts to improve monitoring and preparedness in Brazil by J. W. Gallear, M. Valadares Galdos, M. Zeri, A. Hartley

“…We show that machine learning methods such as gradient boosting methods are able to more easily forecast vegetation health in north and northeast Brazil than in south Brazil, and they perform better during La Niña events than El Niño events. …”
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Investigation of Machine Tool Developed Settings Influence on Productivity and Quality of Simultaneous Double-Sided Lens Processing by A. S. Kozeruk, Y. L. Malpica, A. A. Sukhotzkiy, M. I. Filonova, V. O. Kuznechik

“…In particular, the last case presupposes shaping by changing rotational frequencies of an input link in an executive mechanism of the machine tool w2and the lens wл. …”
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Machine learning of whole-brain resting-state fMRI signatures for individualized grading of frontal gliomas by Yue Hu, Xin Cao, Hongyi Chen, Daoying Geng, Kun Lv

“…Methods This retrospective study included 138 patients (78 LGGs, 60 HGGs) with left frontal gliomas. …”
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Detecting muscle fatigue during lower limb isometric contractions tasks: a machine learning approach by Jiaqi Sun, Cheng Zhang, Guangda Liu, Wenjie Cui, Yubing Sun, Chunyan Zhang

“…This paper introduces a machine learning approach to classify EMG signals for the automatic detection of muscle fatigue.MethodsTen adult participants performed isometric contractions of lower limb muscles. …”
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Research on Fault Diagnosis Method of Electro-Hydrostatic Actuator by Lei Zhufeng, Qin Lvjun, Wu Xiaodong, Jin Wen, Wang Caixia

“…After a variety of method comparisons, the method proposed in this paper has a fault time ratio accuracy of 96.7%, which provides a basis and a new way for the fault diagnosis of the hydraulic system.…”
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Study of Working Medium Performance by Acoustic Emission in EDM Machining of Ti6Al4V by Chengbo Guo, Shufa Sun, Shichun Di, Dongbo Wei

“…In electrical discharge machining (EDM), the working medium plays an important role in the material removal process. …”
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Speed Harmonic Based Saturation Free Inductance Modeling and Estimation of Interior PMSM Using Measurements Under One Load Condition by Guodong Feng, Yuting Lu, Zhe Tong, Beichen Ding, Guishan Yan, Chunyan Lai

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Advancing Maritime Safety: A Literature Review on Machine Learning and Multi-Criteria Analysis in PSC Inspections by Zlatko Boko, Ivica Skoko, Zaloa Sanchez Varela, Vice Milin

“…This literature review provides a structured quantitative analysis of existing research on the application of machine learning models (MLMs) and multi-criteria decision-making methods (MCDM) in the context of port state control (PSC). …”
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Agricultural GDP exposure to drought and its machine learning-based prediction in the Jialing River Basin, China by Xinzhi Wang, Qingxia Lin, Zhiyong Wu, Yuliang Zhang, Changwen Li, Ji Liu, Shinan Zhang, Songyu Li

“…This study integrates hydrological modeling, machine learning methods, and long-term agricultural economic data from 1991 to 2020 in the Jialing River Basin (JRB) to detect and forecast meteorological and agricultural droughts, as well as their impact on cropland. …”
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Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…Additionally, we propose optimizing special subframe configurations in TD-LTE networks using machine learning-based methods to effectively reduce ADI.…”
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Enhancing DDoS Attacks Mitigation Using Machine Learning and Blockchain-Based Mobile Edge Computing in IoT by Mahmoud Chaira, Abdelkader Belhenniche, Roman Chertovskih

“…We evaluate multiple machine learning models, including K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Transformer architectures, and LightGBM, using the CICDDoS2019 dataset. …”
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