Transferable Deep Learning Models for Accurate Ankle Joint Moment Estimation during Gait Using Electromyography by Amged Elsheikh Abdelgadir Ali, Dai Owaki, Mitsuhiro Hayashibe

“…We verified and compared the performance of 1302 intrasubject models per subject on 597 steps from seven subjects using various architectures and feature sets. …”
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Evolutionary accumulation modeling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance by Jessica Renz, Kazeem A. Dauda, Olav N. L. Aga, Ramon Diaz-Uriarte, Iren H. Löhr, Bjørn Blomberg, Iain G. Johnston

“…We discuss how EvAM can learn the evolutionary pathways by which drug resistances and other AMR features (for example, mutations driving these resistances) are acquired as pathogens evolve, predict next evolutionary steps, identify influences between AMR features, and explore differences in MDR evolution between regions, demographics, and more. …”
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Presenting the Professional Competency Model of Teachers in the E-Learning Environment of Primary Schools: A Qualitative Study by Khatereh Nesari, Jaafar Rahmani, Gholamreza Sharifi Rad

“…Objective : Over time, there has been a transition from traditional learning environments to electronic learning environments. …”
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The analysis of marketing performance in E-commerce live broadcast platform based on big data and deep learning by Yuanyuan Wei, Xingchen Pan

“…Finally, the experimental design and implementation steps such as data collection, experimental environment setting, parameter setting, and performance evaluation are introduced in detail. …”
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Community Clustering and Recommendation Toward Elderly Health Records: Probabilistic Representation Learning and Large Graph Search by Huijiong Ding

“…We develop a probabilistic representation learning method to automatically divide a large-scale elderly population into distinct health management communities by leveraging shared health conditions, treatment preferences, and behavioral tendencies. …”
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Learning Condition-Invariant Scene Representations for Place Recognition across the Seasons Using Auto-Encoder and ICA by Tariqul Islam, Sheikh Rabiul Islam, Mahbubur Rahman

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NRNH-AR: A Small Robotic Agent Using Tri-Fold Learning for Navigation and Obstacle Avoidance by Carlos Vasquez-Jalpa, Mariko Nakano, Martin Velasco-Villa, Osvaldo Lopez-Garcia

“…We propose a tri-fold learning algorithm, called Neuroevolution of Hybrid Neural Networks in a Robotic Agent (acronym in Spanish, NRNH-AR), based on deep reinforcement learning (DRL), with self-supervised learning (SSL) and unsupervised learning (USL) steps, specifically designed to be implemented in a small autonomous navigation robot capable of operating in constrained physical environments. …”
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Financial Market Evaluation Utilizing an Optimized Deep-Learning Model: A Case Study of the Nikkei 225 by Karthikeyan M P

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What factors affect teacher professional learning: a qualitative meta-analysis based on the Onion model by Hanqiang Li

“…Design/methodology/approach – Based on the Onion model, 67 core literature in English and Chinese were coded through qualitative meta-analysis methods to explore environmental, behavioral, competence, belief, identity, mission and other factors that may impact teacher learning. Findings – It was found that the quantitative structure of the current relevant studies was in an inverted triangular shape with three levels of steps, respectively, which can be summarized as structural environment, core behaviors and dominant mission. …”
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A machine learning approach for the diagnosis of obstructive sleep apnoea using oximetry, demographic and anthropometric data by Zhou Hao Leong, Shaun Ray Han Loh, Leong Chai Leow, Thun How Ong, Song Tar Toh

“…Prospective studies with home-based oximeters and analysis of other oximetry variables are the next steps towards formal implementation.…”
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Context Aware Task Orchestration With Deep Reinforcement Learning in Real Time Fog Computing Simulation Environment by Alp Gokhan Hossucu, Suat Ozdemir

“…At the core of this contribution lies a novel task orchestration model that transforms the orchestration process into reinforcement learning training steps. The proposed approach offers substantial advantages in terms of task succession, energy efficiency, and resource utilization. …”
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LOTS and HOTS reading questions in EFL textbooks (Kurikulum Merdeka): unveiling every learning process purposes by Maria Kartika Widiastuti, Concilianus Laos Mbato

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Educational Potential of Student-Generated Visuals for Learning English as a Second Language in the Age of Artificial Intelligence by Svitlana Mykytiuk, Olena Lysytska, Oleksandr Chastnyk, Serhii Mykytiuk

“…The experimental group was tasked with creating personalized visual learning materials. The applied approach was structured in several steps, from creating simple forms including infographics and comparative charts to poster presentations and digital video passion projects. …”
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Beacon2Science: Enhancing STEREO/HI Beacon Data With Machine Learning for Efficient CME Tracking by J. Le Louëdec, M. Bauer, T. Amerstorfer, J. A. Davies

“…We then increase the time resolution of enhanced beacon images through learned interpolation to match science data's 40‐min resolution. …”
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Assessment of learning in Interprofessional Education in Health Higher Education: protocol for an integrative literature review on pedagogical approaches by Rafael Silvério de Moraes, Camila Mendes da Silva Souza, Valéria Marli Leonello

“…When introducing IPE into teaching experiences, it is also necessary to address the assessment of learning within this process. One of the critical issues in assessing learning in IPE is the pedagogical approach adopted by the educational program. …”
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Machine Learning Techniques for Predicting Typhoon‐Induced Storm Surge Using a Hybrid Wind Field by Changyu Su, Bishnupriya Sahoo, Miaohua Mao, Meng Xia

“…The prediction performances were analyzed for both spatial (e.g., single and multiple sites) and temporal (e.g., single and multiple steps) scale variability. ML is trained to overcome the residual error of the FVCOM, effectively reducing the inherent uncertainty of traditional methods. …”
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SlideTiler: A dataset creator software for boosting deep learning on histological whole slide images by Leonardo Barcellona, Lorenzo Nicolè, Rocco Cappellesso, Angelo Paolo Dei Tos, Stefano Ghidoni

“…The introduction of deep learning caused a significant breakthrough in digital pathology. …”
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Parallelizing Comprehensive Learning Particle Swarm Optimization by Open Computing Language on an Integrated Graphical Processing Unit by Xiang Yu, Yu Qiao, Qingpeng Li, Gang Xu, Chuanxiong Kang, Claudio Estevez, Chengzhi Deng, Shengqian Wang

“…Comprehensive learning particle swarm optimization (CLPSO) is a powerful metaheuristic for global optimization. …”
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ML-AMPSIT: Machine Learning-based Automated Multi-method Parameter Sensitivity and Importance analysis Tool by D. Di Santo, C. He, F. Chen, L. Giovannini

“…This paper points out how ML-AMPSIT can be an efficient tool for performing sensitivity and importance analysis for complex models, guiding the user through the different steps and allowing for a simplification and automatisation of the process.…”
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South Africa Crime Visualization, Trends Analysis, and Prediction Using Machine Learning Linear Regression Technique by Ibidun Christiana Obagbuwa, Ademola P. Abidoye

“…Diverse data analytics steps were applied to preprocess the datasets, and a machine learning algorithm (linear regression) was used to build a predictive model to analyze data and predict future crime. …”
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