Students’ performance dataset for using machine learning technique in physics education research by Purwoko Haryadi Santoso, Bayu Setiaji, Yohanes Kurniawan, Wahyudi, Syamsul Bahri, Fathurrahman, Mobinta Kusuma, Indah Urwatin Wusqo, Nuri Dewi Muldayanti, Arif Didik Kurniawan, Johan Syahbrudin

“…The SPHERE (Students’ Performance Dataset in Physics Education Research) is presented as an educational dataset of physics learning collected through research-based assessments (RBAs) established by the PER scholars. …”
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Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning by Damir Mulc, Jaksa Vukojevic, Eda Kalafatic, Mario Cifrek, Domagoj Vidovic, Alan Jovic

“…Using various machine learning (ML) classification models, we achieved up to 80% accuracy in distinguishing individuals with MDD from healthy controls. …”
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Unsupervised machine learning for automated corrosion staging using optical microscopy images by Ashwin RajKumar, Naveen Paluru, Raji Susan Mathew, Prathamesh Shenai, Dana Abdeen, Nicholas Laycock, Phaneendra K. Yalavarthy

“…This study presents an unsupervised automated corrosion staging method based on image processing and machine learning using optical microscopy (OM) images. …”
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Empowering Diagnostics: An Ensemble Machine Learning Model for Early Liver Disease Detection by Abdulrahman Ahmed Jasim, Hajer Alwindawi, Layth Rafea Hazim

“… Early and accurate detection of liver disease is critical to improving patient outcomes yet remains challenging due to class imbalance and noisy clinical data. In this study, we present a robust ensemble learning framework applied to the Indian Liver Patient Dataset, incorporating systematic data cleaning, normalization, and Synthetic Minority Over‑Sampling (SMOTE) to address missing values, outliers, and class skew. …”
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A deep-learning based method for accelerating dynamic reconfiguration of distribution networks by Yuxuan Wu, Tao Qian, Jingwen Ye, Qinran Hu, Qiangsheng Bu, Zhigang Ye

“…To address this issue, this paper presents a deep learning-based framework that converts the MIQP problem into a solvable quadratic program (QP), enabling accelerated DNR. …”
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Contribution of cooperative learning strategies to the improvement of the quality of students' native language knowledge by Semiz Marina Ž., Antonijević Radovan M., Čutović Mirjana M.

“…In this paper, we will present the results of the ex-post-facto research conducted to examine whether and to what extent the application of cooperative learning can improve the quality of factual, conceptual and procedural knowledge of students in their mother tongue. …”
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Enhancing Generative Class Incremental Learning Performance With a Model Forgetting Approach by Taro Togo, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama

“…This study presents a novel approach to Generative Class Incremental Learning (GCIL) by introducing the forgetting mechanism, aimed at dynamically managing class information for better adaptation to streaming data. …”
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How do Indonesian students respond to ethnomathematics-based learning in the digital era? by I Putu Ade Andre Payadnya, Kadek Adi Wibawa, I Gusti Agung Ngurah Trisna Jayantika, I Made Wena, Kadek Rahayu Puspadewi

“…The integration of ethnomathematics ((a combination of mathematical concepts with local culture) into education presents unique opportunities and challenges, particularly in the digital era where cultural and technological contexts converge. …”
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Traffic Signal Control via Reinforcement Learning: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Charalampos Rafail Lazaridis, Elias Kosmatopoulos

“…The current review presents a comprehensive analysis of high-impact reinforcement-learning-based traffic signal control methods, evaluating their contributions across numerous key dimensions: methodology type, multi-agent architectures, reward design, performance evaluation, baseline comparison, network scale, practical applicability, and simulation platforms. …”
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Teachers’ willingness to change in adapting to online learning during the covid-19 pandemic by Reni Herawati, Heru Kurnianto Tjahjono, Ika Nurul Qamari, Sri Handari Wahyuningsih

“…Teachers preferred to use task-based learning and resisted incorporating technology in the learning process. …”
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Blending Ensemble Learning Model for 12-Lead Electrocardiogram-Based Arrhythmia Classification by Hai-Long Nguyen, Van Su Pham, Hai-Chau Le

“…The increasing prevalence of heart diseases has driven the development of automated arrhythmia classification systems using machine learning and electrocardiograms (ECGs). This paper presents a novel ensemble learning method for classifying multiple arrhythmia types using 12-lead ECG signals through a blending technique. …”
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Digital Assistance Systems to Implement Machine Learning in Manufacturing: A Systematic Review by Jannik Rosemeyer, Marta Pinzone, Joachim Metternich

“…Implementing machine learning technologies in manufacturing environment relies heavily on human expertise in terms of domain and machine learning knowledge. …”
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Ensemble learning for multi-class COVID-19 detection from big data. by Sarah Kaleem, Adnan Sohail, Muhammad Usman Tariq, Muhammad Babar, Basit Qureshi

“…The model's efficacy was validated through a comprehensive analysis of predicted and actual values, and its performance was meticulously evaluated for accuracy, precision, recall, and F-measure, and compared to state-of-the-art models. The work presented here not only contributes to the ongoing fight against COVID-19 but also showcases the wider applicability and potential of ensemble learning techniques in healthcare.…”
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Multi-RIS-Assisted 3D Localization and Synchronization via Deep Learning by Alireza Fadakar, Maryam Sabbaghian, Henk Wymeersch

“…However, operation in multi-path scenarios is challenging from both complexity and performance perspectives. This study presents a two-stage low complexity method for joint three-dimensional (3D) localization and synchronization using multiple RISs. …”
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Comparisons of Machine Learning Methods in Ship Speed Prediction Based on Shipboard Observation by Weidong Gan, Dianguang Ma, Yu Duan

“…This study presents a novel approach to predicting ship speed based on real-time voyage observation data, aiming to enhance maritime safety and operational efficiency. …”
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The evolution of the nuclear emergency response plan using mechanisms of learning, innovation and communication by André Luiz Quadros

“…In this sense, this work aimed to identify and analyze the dynamics of preparation and response to possible emergencies in a nuclear power plant, based on the evolutionary change of an emergency plan and, aiming to understand the evolution of these plans, in light of the organizational learning processes, innovation and risk communication. …”
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Analysis of signals from air conditioner compressors with ordinal patterns and machine learning by Keila Barbosa, Alejandro C Frery, George DC Cavalcanti

“…A desirable outcome of this monitoring is identifying when the device will likely require maintenance. In this study, we present the use of Ordinal Patterns, a symbolic transformation of time series, which allows for the visual assessment of the type of operation. …”
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The Effect of BBC News Lessons on High School EFL Learners’ Vocabulary Learning by حسن علیزاده محمود علیلو, توران آهور

“…Foreign language vocabulary learning is challenging and requires using an appropriate method. …”
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Optimizing Biogas Power Plants through Machine-Learning-Aided Rotor Configuration by Andreas Heller, Héctor Pomares, Peter Glösekötter

“…In this research, we present a novel approach that leverages machine learning techniques to optimize the performance of biogas power plants through the strategic placement and configuration of rotors within the fermentation vessel. …”
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Motivational Dynamics in a Multilingual Context: University Students’ Perspectives on LOTE Learning by Ali Göksu, Vincent Louis

“…Despite increasing the focus on multilingualism within second-language acquisition (SLA) research, less research focuses on the motivational dynamics of multilingual learners in learning languages other than English (LOTE). Addressing this gap, the present study investigates the complex motivational factors influencing multilingual university students in learning French as an additional language and LOTE within the Belgian context. …”
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