Machine Learning Approaches for Predicting Employee Turnover: A Systematic Review by Hojat Talebi, Amid Khatibi Bardsiri, Vahid Khatibi Bardsiri

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Comparative analysis of machine learning techniques for enhanced vehicle tracking and analysis by Seema Rani, Sandeep Dalal

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AI-powered machine learning models for monitoring and optimization of biodrying process by Abhisit Bhatsada, Panida Payomthip, Tanik Itsarathorn, Ye Nyi Nyi Lwin, Eka Wahyanti, Sirintornthep Towprayoon, Suthum Patumsawad, Chart Chiemchaisri, Komsilp Wangyao

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Development of Machine Learning Models for Sandface Pressure Prediction in Oil Well by Lorraine P. Oliveira, Raul M. Foronda, Alexandre V. Grillo, Brunno F. dos Santos

“…The Oil & Gas (O&G) industry is increasingly leveraging Machine Learning (ML) techniques to predict well performance indicators, estimate missing operational metrics, and mitigate unexpected operational failures. …”
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An optimize canny algorithm with traditional machine learning for edge detection enhancement by Russel Lafta, Zainab Sultani

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Image Based Detection of Coating Wear on Cutting Tools with Machine Learning by Jan Wolf, Nithin Kumar Bandaru, Martin Dienwiebel, Hans-Christian Möhring

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Enhancing distant low-resource neural machine translation with semantic pivot by Enchang Zhu, Yuxin Huang, Yantuan Xian, Junguo Zhu, Minghu Gao, Zhiqiang Yu

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Intelligent Machine Learning Based Internet of Things (IoT) Resource Allocation by Koushik Chakraborty, Dhiraj Kapila, Sumit Kumar, Bhupati, Nazeer Shaik, Akanksha Singh

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Smart Coffee: Machine Learning Techniques for Estimating Arabica Coffee Yield by Cleverson Henrique de Freitas, Rubens Duarte Coelho, Jéfferson de Oliveira Costa, Paulo Cesar Sentelhas

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MODELING OF HYDROMECHANICAL DRIVE SYSTEM OF WORKING BODY FOR MOBILE TECHNOLOGY MACHINE by A. R. Temirkanov, A. T. Rybak

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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

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Optimization of machining parameters in turning to steel using grey relational analysis by Wisam Naji Hasan, Dhyai H. Jawad Aljashaami

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Development of digital twin of CNC unit based on machine learning methods by Yu. G. Kabaldin, D. A. Shatagin, M. S. Anosov, A. M. Kuzmishina

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General and stable emulation of finite state machines with spiking neural networks by Ziyang Sun, Zhong Zheng, Binying Zhang, Hanle Zheng, Zikai Wang, Hao Guo, Lei Deng

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Machine Learning Methods for Predicting Cardiovascular Diseases: A Comparative Analysis by Aiym B. Temirbayeva, Arshyn Altybay

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Machine Learning with Tunicate Swarm Optimization for Improved Disc Herniation Prediction by Theofilos Gofas, Argyros Maris

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Translation Quality Regarding Low-Resource, Custom Machine Translations: A Fine-Grained Comparative Study on Turkish-to-English Statistical and Neural Machine Translation System... by Gökhan Doğru

“…While the automatic evaluation results suggest the SMT engines to perform better than NMT engines, all human evaluators rated the mixed-domain NMT engine as the highest performing one. …”
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An IMU-Based Machine Learning System for Container Collision Position Identification by Xin Zhang, Zihan Song, Do-Myung Park, Byung-Kwon Park

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Machine Reading Comprehension for the Tamil Language With Translated SQuAD by Anton Vijeevaraj Ann Sinthusha, Eugene Y. A. Charles, Ruvan Weerasinghe

“…It also enhances question-answering systems, benefiting educational tools, search engines, and help desks. The introduction of attention-based transformer models has significantly boosted MRC performance, especially for well-resourced languages such as English. …”
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Machine-learning synergy in high-entropy alloys: A review by Sally Elkatatny, Walaa Abd-Elaziem, Tamer A. Sebaey, Moustafa A. Darwish, Atef Hamada

“…In addition, this review examines the use of ML for performance-driven reverse engineering of HEA compositions, enabling the rapid identification of new high-performance alloy designs. …”
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