How to Improve Fine Motor Skill Learning in Dentistry by Mohamed El-Kishawi, Khaled Khalaf, Tracey Winning

“…Factors including the amount and timing of instructions provided, cognitive abilities, and practice schedule of learning trials may have significant implications on the design of fine motor skill learning exercises.…”
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Global Geomagnetic Perturbation Forecasting Using Deep Learning by Vishal Upendran, Panagiotis Tigas, Banafsheh Ferdousi, Téo Bloch, Mark C. M. Cheung, Siddha Ganju, Asti Bhatt, Ryan M. McGranaghan, Yarin Gal

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Channel estimation for OFDM system based on deep learning by Yun ZHANG, Jing ZHOU, Jingwei HUANG, Shujuan YU, Liya HUANG

Subjects: “…deep learning…”
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Research on the Application of Reinforcement Learning in Traffic Flow Prediction by Hu Yiquan

“…The paper provides a detailed review of the latest developments in Deep RL in the field of TFP, including the application of Q-learning and its variants in traffic signal control. …”
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Parents’ Impression On Quality Of Children In Learning Process At Classroom by Dinda Salsabilah Siregar, Melina Putri Septiani Nasution, Thalya Marchanda Tarigan, Soechi Kurnia, Bambang Nur Alamsyah Lubis

“…The result of this study was the role of parents did not influence student learning in class, due to a lack of supporting factors. …”
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Performance evaluation metric for statistical learning trading strategies by Jiawei He, Roman N. Makarov, Jake Tuero, Zilin Wang

Subjects: “…statistical learning…”
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Ionospheric TEC Prediction Based on Ensemble Learning Models by Yang Zhou, Jing Liu, Shuhan Li, Qiaoling Li

Subjects: “…machine learning…”
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Machine Learning in Information and Communications Technology: A Survey by Elias Dritsas, Maria Trigka

Subjects: “…machine learning…”
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Use of Instagram as learning media in senior high school by Muhammad Nur Iman Hadiyana Setia, Monica Fajriana

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Contextualized embeddings for semantic change detection: Lessons learned by Andrey Kutuzov, Erik Velldal, Lilja Øvrelid

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Application of machine learning in the fake user identification of IoT by Rongfang ZHANG, Dandan XU, Yuanguang WANG, Siyu PAN, Zhengmao LI

“…The purpose was to use machine learning models to identify users who have high suspiciousness effectively. …”
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Research on metacognitive strategies of children’s self-regulated learning by NARENGAOWA, Orosoo Tungalag

“…# Background Learning involves numerous self-regulatory processes, and self-regulated learning includes a few metacognitive strategies. …”
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Joint embedding–classifier learning for interpretable collaborative filtering by Clémence Réda, Jill-Jênn Vie, Olaf Wolkenhauer

“…Results We introduce the novel Joint Embedding Learning-classifier for improved Interpretability (JELI). …”
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Applications of Deep Learning to MRI Images: A Survey by Jin Liu, Yi Pan, Min Li, Ziyue Chen, Lu Tang, Chengqian Lu, Jianxin Wang

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An Event Causality Identification Framework Using Ensemble Learning by Xiaoyang Wang, Wenjie Luo, Xiudan Yang

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PERCEPTION OF ONLINE VERSUS PHYSICAL LEARNING AMONGUNIVERSITY STUDENTS by Ramna Shafique, Muhammad Abdullah, Tooba Nasir, Sundas Salim, Sabrina Jam, Bina Fawad

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A Bibliometric Analysis of E-Learning Research Trends by Regina Deti, Virginia Mandasari

Subjects: “…e-learning…”
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Social context affects sequence modification learning in birdsong by Lioba Fortkord, Lena Veit

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User Model for Virtual Learning Based on Adaptive Gamification by Intan Yusrina Zairon, Tengku Siti Meriam Tengku Wook, Syahanim Mohd Salleh, Hadi Affendy Dahlan

Subjects: “…Learning style…”
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Learning with semantic ambiguity for unbiased scene graph generation by Shanjin Zhong, Yang Cao, Qiaosen Chen, Jie Gong

“…In response to these challenges, we propose a model-agnostic method named Mixup and Balanced Relation Learning (MBRL). This method assigns soft labels to samples exhibiting semantic ambiguities and optimizes model training by adjusting the loss weights for fine-grained and low-frequency relation samples. …”
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