Anomaly Detection of Marine Diesel Engines: A Novel Approach using Transformer Neural Networks for Reconstruction and Residual Analysis by Qin Liang, Erik Vanem, Knut Erik Knutsen, Vilmar Æsøy, Houxiang Zhang

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A machine-learned model for predicting weight loss success using weight change features early in treatment by Farzad Shahabi, Samuel L. Battalio, Angela Fidler Pfammatter, Donald Hedeker, Bonnie Spring, Nabil Alshurafa

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Learning model of basic manipulative movements of throwing and catching: A developmental study through early childhood play by Endang Pratiwi, Hernawan Hernawan, Fahmy Fachrezzy, Norma Anggara, Hikmah Lestari, Aditya Gumantan, Y.Touvan Juni Samodra, M. Adam Mappaompo, Juhannis Juhannis, Albadi Sinulingga

“…This study aims to develop a model of learning basic manipulative movements of throwing and catching in Early Childhood. …”
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THE E-LEARNING IN FRENCH LANGUAGE AND LITERATURE DEPARTMENT OF THE UNIVERSITY OF MASCARA DURING THE COVID-19 CRISIS: QUANTITATIVE STUDY by Aouda MAZOT

“…This research aims to evaluate the steps, means and resources implemented by the French language and literature department at Mustapha Stambouli University, Mascara, for the “smooth” running of e-learning, during the containment imposed by the Algerian government and applied in all sectors including higher education and scientific research, following the Covid-19 pandemic. 232 students were surveyed, exploring their experiences of distance learning and their evaluation of the digital resources made available to them by the university. …”
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The Detection of Fake Text News using a Dense-based 1D-CNN Deep Learning Algorithm by Khalid Abood Kamel, Jumana Waleed

“…The goal of this ‎paper is the optimal use of deep learning algorithms to solve the problem of the paper. …”
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POST-SOVIET TERRITORIAL CONFLICTS IN MOLDOVA AND ESTONIA: WHEN POLITICAL ELITES CAN LEARN FROM THE MUTUAL MISTAKES by A. Yu. Sungurov, N. Belyavskaya

“…The detected interaction of political elites of Moldova and Transnistria is viewed from the perspective  of the concept of  “policy learning” by Hugh Heclo and Richard Rose.…”
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Predicting Diabetes Risk Using Machine Learning: A Comparative Study on the Yazd Health Study (YaHS) by Fateme Sefid, Nazanin Norouzi-Ghahjavarestani, Malihe Soleymani-Tabasi, Jamal Zarepour-Ahmadabadi, Ghasem Azamirad, Mohamah yahya Vahidi Mehrjardi, Masoud Mirzaei, Seyed Mehdi Kalantar

“…Extensive preprocessing steps, including data cleaning, class imbalance handling through Synthetic Minority Oversampling Technique and Edited Nearest Neighbors (SMOTEENN), and feature selection, are applied to enhance the performance of models. …”
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Polynomial Phase Signal Denoising via Sparse Representations Over a SMAF-Based Dictionary Learning Algorithm by Guojian Ou, Chenping Zeng, Jiaqiang Dong, Die Han

“…Our approach is based on sparse representation using a trained dictionary, which is obtained through the secondary moving average filtering (SMAF) dictionary learning algorithm. The proposed algorithm consists of two main steps: first, we utilize K-SVD or other dictionary learning algorithms to obtain the initial trained dictionary; second, we apply the SMAF method to modify the dictionary atoms, enabling them to behave more smoothly and effectively reducing the noise present in the atomic structures. …”
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Predicting practical reduction potential of electrolyte solvents via computational hydrogen electrode and interpretable machine-learning models by Zonglin Yi, Yi Zhou, Hao Liu, Li Li, Yan Zhao, Jiayuan Li, Yixuan Mao, Fangyuan Su, Cheng-Meng Chen

“…A computational hydrogen electrode model based on density functional theory calculation is generalized for calculating the reaction free energy of electrochemical elementary steps. Machine-learning models are trained based on the organic and inorganic electrolyte solvents that possess experimentally identified reduction mechanisms. …”
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CrackNet: A new deep learning-based strategy for automatic classification of road cracks after earthquakes by Fatih Demir, Erkut Yalcin, Mehmet Yilmaz

“…In the next stage, asphalt cracks were categorized with a new deep learning-based model. In the study, data reliability was increased with gradient-based preprocessing steps. …”
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Design of Teaching and Learning Sequences and Complex Educational Games: A Strategic Proposal for Mobilizing the Model of Educational Reconstruction by Michelle Garcia da Silva, Roberta Smania-Marques, Helaine Sivini Ferreira

“…To this end, we propose a Mobilize Strategy that recursively articulates three elements: the characteristics of teaching and learning environments; the design trajectory; and the pedagogical potentialities framework. …”
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Methodology for detecting anomalies in cyber attack assessment data using Random Forest and Gradient Boosting in machine learning by A. S. Kechedzhiev, O. L. Tsvetkova, A. I. Dubrovina

“…The work done is the result of a comprehensive analysis of a machine learning model designed to detect cyberattacks. It includes several key steps and methods that allow us to evaluate the effectiveness of the model, identify important features, and analyze performance for various attacks.…”
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The Effect of Various Text Representation Methods for Sentiment Analysis on Movie Review Data with Different Machine Learning Methods by Veysel Göç, Muhammet Sinan Başarslan

“…On the open source IMDB movie reviews dataset, we first undertake data cleaning and text representation with data preprocessing steps. Then, we apply sentiment classification using different ML models. …”
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Role-Playing Cards Learning Models Based on Madura Ethnic Entrepreneurship Values to Increasing Students' Interest in Entrepreneurship by Fajar Utomo, Disman, Abdul Azis Wahab, Didin Saripudin

“…The results showed that the RPC learning model based on the entrepreneurial values of the Madurese was operationalized through five learning steps assisted by media cards (question cards and solution cards) and scenario texts. …”
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Development of Android Applications SAJ (Sinau Aksara Jawa) as Javanese Script Learning Media Using the Addie Model by Sugito Sugito, I Nyoman Sudana Degeng, Ibut Priono Leksono

“…With this learning media, students are expected to be able to learn more effectively and efficiently because they can learn anytime and anywhere. …”
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Transforming primary education: balancing social skills and academic achievement through global inquiry-based learning models by Seprie, Wuri Wuryandani, Muthmainah

“…To maximize the benefits of IBL, the study recommends embedding IBL more fully into national curricula, providing targeted teacher training, and expanding access to digital learning tools. These steps are essential for equipping students with the critical thinking, autonomy, and interpersonal competencies required in the globalized 21st-century context.…”
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A machine learning-driven modeling and optimization approach for enhancing cassava mash production quality in cassava graters by Nana Yaa Serwaah Sarpong, Joseph Oppong Akowuah, Joseph Ofei Darko, Eric Asante Amoah

“…Machine performance modeling and optimization have emerged as crucial steps for process enhancement and efficiency. This study explored machine learning to model and optimize the cassava grating chamber of cassava grater for the quality production of gari. …”
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A Deep Learning Model Based on Bidirectional Temporal Convolutional Network (Bi-TCN) for Predicting Employee Attrition by Farhad Mortezapour Shiri, Shingo Yamaguchi, Mohd Anuaruddin Bin Ahmadon

“…If a company can predict the likelihood of an employee leaving, it can take proactive steps to address the issue. In this study, we introduce a deep learning framework based on a Bidirectional Temporal Convolutional Network (Bi-TCN) to predict employee attrition. …”
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Deep learning from three-dimensional lithium-ion battery multiphysics model part I: Data development by Yiheng Pang, Yun Wang, Zhiqiang Niu

“…Nowadays, Battery informatics are emerging as promising solutions by leveraging advanced machine learning tools to deliver accurate prediction of battery performance, health and safety, but is hurdled by a scarcity of data. …”
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A Unified Deep Learning Ensemble Framework for Voice-Based Parkinson’s Disease Detection and Motor Severity Prediction by Madjda Khedimi, Tao Zhang, Chaima Dehmani, Xin Zhao, Yanzhang Geng

“…This study presents a hybrid ensemble learning framework for the joint detection and motor severity prediction of Parkinson’s disease (PD) using biomedical voice features. …”
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