Acoustic-Based Machine Main State Monitoring for High-Speed CNC Drilling by Pimolkan Piankitrungreang, Kantawatchr Chaiprabha, Worathris Chungsangsatiporn, Chanat Ratanasumawong, Peemdej Chancharoen, Ratchatin Chancharoen

“…Advanced signal processing techniques, including spectrogram analysis and Fast Fourier Transform, extract dominant frequencies and acoustic patterns, while machine learning algorithms like DBSCAN clustering classify operational states such as cutting, breakthrough, and returning. …”
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Reverse Determination of Face-milling Cutter Radius of Curvilinear Cylindrical Gears Using Contact Pattern by Zhang Xuegang, Dong Yingjie

“…To design a curvilinear cylindrical gear with arbitrary tooth surface contact pattern, a method for determining the radius of a disc-shaped milling cutter for machining the curvilinear cylindrical gear was proposed based on the reverse determination of the required dimensions of the contact pattern. …”
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Predictors of depression among Chinese college students: a machine learning approach by Lin Luo, Junfeng Yuan, Chenghan Wu, Yanling Wang, Rui Zhu, Huilin Xu, Luqin Zhang, Zhongge Zhang

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THE PRODUCTION OF COMPLEX PROFILE DETAILS BY COMBINED METHOD OF LOST-WAX CASTING AND OF CONSUMABLE PATTERN MODELS by O. I. Shinsky, I. I. Maksyuta, Yu. G. Kvasnitskaya, E. V. Mikhnyan, A. V. Neyma

“…Besides this method allows to receive figurine castings with minimization of an allowance for machining of details, to increase their geometrical accuracy and to lower a roughness.…”
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Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning by Chengping Chai, Omar Marcillo, Monica Maceira, Junghyun Park, Stephen Arrowsmith, James O. Thomas, Joshua Cunningham

“…Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. …”
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A Comprehensive Evaluation of Machine Learning and Deep Learning Models for Churn Prediction by Nabil M. AbdelAziz, Mostafa Bekheet, Ahmad Salah, Nissreen El-Saber, Wafaa T. AbdelMoneim

“…Moreover, traditional machine learning models like XGBoost also produced competitive results for selected datasets. …”
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Machine learning algorithms to detect patient–ventilator asynchrony: a feasibility study by Guillermo Gutierrez, Kendrew Wong, Arun Jose, Jeffrey Williams

“…We explored the feasibility of using machine learning algorithms to replicate the assessment of breathing patterns by experienced clinicians, based on airway flow and pressure signals. …”
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Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

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Machine learning approach for Studying the multifunctionality of soil against global climate changes by Xiangng Hu, Yingying Xie, Qixing Zhou, Li Mu

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Decoding the brain-machine interaction for upper limb assistive technologies: advances and challenges by Sutirtha Ghosh, Rohit Kumar Yadav, Sunaina Soni, Shivangi Giri, Shivangi Giri, Suriya Prakash Muthukrishnan, Lalan Kumar, Lalan Kumar, Shubhendu Bhasin, Sitikantha Roy

“…This review aims to provide a comprehensive overview of recent progress in deciphering neural activity patterns associated with both physiological and assisted upper limb movements, highlighting avenues for future exploration in neurorehabilitation and brain-machine interface development.…”
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Using baseline MRI radiomics to predict the tumor shrinkage patterns in HR-Positive, HER2-Negative Breast Cancer by Lijia Wang, Yongchen Wang, Li Yang, Jialiang Ren, Qian Xu, Yingmin Zhai, Tao Zhou

“…A clinical model was established using Ki67 quantification and enhancement pattern. Radiomics features were extracted and analyzed using machine learning algorithms, including Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF). …”
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What drives the profitability of banking sectors in the European Union? The machine learning approach by Bernardelli Michał, Korzeb Zbigniew, Niedziółka Paweł

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Comparative Investigation of Machine Learning and Deep Learning Approaches for Air Quality Prediction by Zhang Borui

“…Machine learning offers easier interpretability with limited data but struggles with complex data relationships. …”
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Neutrosophic Set and Machine Learning Model for Identifying Botnet Attacks on IoT Effectively by Wasal S AL-Bash AL-Azzawi, Hassan W. Hilou, Nawfal H. warush, Hasan Meslmani, Ahmed A El-Douh, Ahmed Abdelhafeez

“…This work offers a thorough analysis that successfully detects botnet assaults on the Internet of Things by using machine learning techniques, including Random Forest and LSTM. …”
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APPLICATION OF A MACHINE LEARNING MODEL FOR FORECASTING FREIGHT RATE IN ROAD TRANSPORT by Artur, Maria

“…The analysis allowed to conclude that machine learning models can be effective in forecasting freight prices in the context of sustainable transport due to their ability to capture complex patterns and relationships in large datasets. …”
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A new benchmark for machine learning applied to powder X-ray diffraction by Sergio Rincón, Gabriel González, Mario A. Macías, Pablo Arbeláez

“…Abstract Although crystal parameter prediction from powder X-ray diffraction has recently attracted the interest of the machine learning community, most existing datasets for this task are private and lack structural diversity. …”
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The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data by Sudarmaji Saroji*, Ekrar Winata, Putra Pratama Wahyu Hidayat, Suryo Prakoso, Firman Herdiansyah

“…The support vector machine (SVM) algorithm has been applied successfully to the Damar field, Indonesia. …”
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Efficiency Monitoring of a Cooling Water Pump based on Machine Learning Techniques by Marta Casero, Miguel A. Sanz-Bobi, F. Javier Bellido-López, Antonio Muñoz, Daniel Gonzalez-Calvo, Tomas Alvarez-Tejedor

“…The method is based on monitoring the performance of the pumps over time using machine learning techniques that try to discover patterns in the data observed from the pumps. …”
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Efficient Human Activity Recognition Using Machine Learning and Wearable Sensor Data by Ziwei Zhong, Bin Liu

“…Human activity recognition and monitoring systems offer a powerful means of identifying daily movement patterns, which helps in understanding human behaviors and provides valuable insights for life management. …”
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Identification of key proteins and pathways in myocardial infarction using machine learning approaches by Chang Liu, Xing Zhang, Qian Xie, Binbin Fang, Fen Liu, Junyi Luo, Gulandanmu Aihemaiti, Wei Ji, Yining Yang, Xiaomei Li

“…This study combines proteomics, transcriptomics and machine learning (ML) to identify key proteins and pathways associated with AMI. …”
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