An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach by Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta

“…The machine learning algorithms showed high accuracy, precision, recall, and F1-score in detecting suicide patterns on social media data whereas SVM has the highest performance with an accuracy of 0.886.       …”
Get full text

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. …”
Get full text

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

Get full text

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. …”
Get full text

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.…”
Get full text

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

“…This would help conclude whether the varied patterns of the churn throughout different sectors to the level that affects the model performance and to what extent. …”
Get full text

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

Get full text

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. …”
Get full text

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. …”
Get full text

Environmental Data Analytics for Smart Cities: A Machine Learning and Statistical Approach by Ali Suliman AlSalehy, Mike Bailey

Get full text

Spatial Clusters of Gambling Outlet: A Machine Learning Tree-Based Algorithm by Salvador Martínez-Cava, Fernando A. López, MLuz Maté Sánchez-del-Val

“…The results reveal different spatial patterns regarding the locations of these two types of gambling establishments. …”
Get full text

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. …”
Get full text

What drives the profitability of banking sectors in the European Union? The machine learning approach by Bernardelli Michał, Korzeb Zbigniew, Niedziółka Paweł

Get full text

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

“…Deep learning captures nonlinear patterns more effectively but lacks interpretability and requires more data. …”
Get full text

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

“…These algorithms are examined, contrasted, and demonstrated to be very successful in identifying intricate patterns suggestive of botnet activity, leading to a notable enhancement in IoT security. …”
Get full text

Water resource forecasting with machine learning and deep learning: A scientometric analysis by Chanjuan Liu, Jing Xu, Xi’an Li, Zhongyao Yu, Jinran Wu

“…Water prediction plays a crucial role in modern-day water resource management, encompassing both hydrological patterns and demand forecasts. To gain insights into its current focus, status, and emerging themes, this study analyzed 876 articles published between 2015 and 2022, retrieved from the Web of Science database. …”
Get full text

Validation of sleep-based actigraphy machine learning models for prediction of preterm birth by Benjamin C. Warner, Peinan Zhao, Erik D. Herzog, Antonina I. Frolova, Sarah K. England, Chenyang Lu

“…Our findings suggest that actigraphy data can predict preterm birth outcomes with a degree of effectiveness, and that variability in sleep patterns is a relatively fair predictor of preterm birth.…”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text