Learning the Value of Character Education from Indonesian Animation Series: Adit & Sopo Jarwo by Viviani Nurmala, Sujarwo, Aprilia Tina Lidyasari, Ikhlasul Ardi Nugroho, Banu Setyo Adi, Sekar Purbarini Kawuryan

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Machine Learning for Accurate Office Room Occupancy Detection Using Multi-Sensor Data by Yusuf Ibrahim, Umar Yusuf Bagaye, Abubakar Ibrahim Muhammad

“…In this paper, we present a comparative study of several machine learning (ML) approaches for accurate office room occupancy detection through the analysis of multi-sensor data. …”
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Deep learning network for NMR spectra reconstruction in time-frequency domain and quality assessment by Yao Luo, Wenhan Chen, Zhenhua Su, Xiaoqi Shi, Jie Luo, Xiaobo Qu, Zhong Chen, Yanqin Lin

“…In this study, a joint time-frequency domain deep learning network, referred to as JTF-Net, is proposed. …”
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Hybrid data-driven and physics-informed regularized learning of cyclic plasticity with neural networks by Stefan Hildebrand, Sandra Klinge

“…An extendable, efficient and explainable Machine Learning approach is proposed to represent cyclic plasticity and replace conventional material models based on the Radial Return Mapping algorithm. …”
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This is not the way: global directional cues do not improve spatial learning in an immersive virtual environment by Ece Yüksel, Zachary Boogaart, Steven M. Weisberg

“…For example, a compass provides a global reference direction and bearing, showing where north is but may not result in a more accurate representation of an environment without the compass. We present two experiments evaluating whether people learned a large-scale, immersive virtual environment better when provided with a global reference direction. …”
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SPATIAL STORYTELLING AS A CONVERGENCE OF E-LEARNING, VIDEO GAMES, ARCHAIC, AND IMMERSIVE JOURNALISM by Тетяна Анатоліївна Зінов’єва

“… This study explores the convergence of video games, game-based learning (GBL), and immersive journalism through various storytelling models, including Joseph Campbell's Hero’s Journey.  …”
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Project-Based Learning with Paired Expert and Beginner Models to Develop Innovative Thinking Skills by Aynin Mashfufah, Intan Sari Rufiana, Slamet Arifin, Ratna Ekawati, Dian Ratna Sari, Haerul Salam

“…The results of project completion show that on average, innovative thinking skills have developed well. The contextualized learning environment by presenting real problems related to the learning process of students in elementary schools is able to stimulate students' ability to solve problems. …”
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KPMapNet: Keypoint Representation Learning for Online Vectorized High-Definition Map Construction by Bicheng Jin, Wenyu Hao, Wenzhao Qiu, Shanmin Pang

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A Review on Trending Machine Learning Techniques for Type 2 Diabetes Mellitus Management by Panagiotis D. Petridis, Aleksandra S. Kristo, Angelos K. Sikalidis, Ilias K. Kitsas

“…Numerous research articles as well as systematic reviews have been conducted to produce innovative findings and summarize current developments and applications of data science in the life sciences, medicine and healthcare. The present review is conducted in the context of T2DM and Machine Learning, examining relatively recent publications using tabular data and demonstrating the relevant use cases, the workflows during model building and the candidate predictors. …”
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ARCS: Adaptive Reinforcement Learning Framework for Automated Cybersecurity Incident Response Strategy Optimization by Shaochen Ren, Jianian Jin, Guanchong Niu, Yang Liu

“…The increasing sophistication and frequency of cyber attacks necessitate automated and intelligent response mechanisms that can adapt to evolving threats. This paper presents ARCS (Adaptive Reinforcement learning for Cybersecurity Strategy), a novel framework that leverages deep reinforcement learning to optimize automated incident response strategies in cybersecurity systems. …”
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Traffic light detection and recognition based on deep learning for autonomous-rail rapid tram by XIONG Qunfang, LIN Jun, YUAN Xiwen, XU Yanghan, YUE Wei, LI Yuanzhengyu

“…However, existing means for traffic light detection and recognition often fall short of meeting the detection requirements in the automatic operation environments characterized by customized traffic lights, with only a few regular signals. This paper presents study efforts in this field through the application of a deep learning algorithm. …”
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Heart Rate Detection and Classification from Speech Spectral Features Using Machine Learning by Mohammed USMAN, Mohammed ZUBAIR, Zeeshan AHMAD, Monji ZAIDI, Thafasal IJYAS, Muneer PARAYANGAT, Mohd WAJID, Mohammad SHIBLEE, Syed Jaffar ALI

“…A comparison of machine learning algorithms in terms of heart rate estimation and classification accuracy is also presented. …”
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Empowering and Promoting Children’s Rights by Implementing Skills Labs Using Engaging Learning Activities by Charikleia Pitsou, Ioannis G. Katsantonis, Argyrios Katsantonis, Georgios S. Gorozidis

“…Next, the educational innovation of Skills Labs in Greek education is introduced, and the TPB’s foundation on designing learning activities is briefly explained. To clarify our proposal, three sample Skills Labs with example learning activities are presented, adhering to the three main HRE objectives of gaining knowledge–taking responsibility–taking action to protect and consolidate children’s rights. …”
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Data-Driven Diagnostics for Pediatric Appendicitis: Machine Learning to Minimize Misdiagnoses and Unnecessary Surgeries by Deborah Maffezzoni, Enrico Barbierato, Alice Gatti

“…Pediatric appendicitis remains a challenging condition to diagnose accurately due to its varied clinical presentations and the non-specific nature of symptoms, particularly in younger patients. …”
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Instructional Design of the Micro-learning Framework in Educational Programs: A Scoping Review Study by Fatemeh Keshmiri, Atefe sadat Heidari, Amir Houshang Mehrparvar

“…The study aimed to identify the key principles that should guide the design of content and instructional flow in the microlearning framework. Method: The present study is a scoping review. A comprehensive search was performed using relevant keywords, including "microlearning," "instructional design," "micro-content," and "learning flow," in the PubMed, Google Scholar, and Scopus databases, without any time restrictions. …”
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Comparison of Machine Learning Algorithms for Daily Runoff Forecasting with Global Rainfall Products in Algeria by Rayane Bounab, Hamouda Boutaghane, Tayeb Boulmaiz, Yves Tramblay

“…In Algeria, to identify a relevant modeling approach using this new source of rainfall information, the present research aims to (i) compare a conceptual model (GR4J) and seven machine learning algorithms (FFNN, ELM, LSTM, LSTM2, GRU, SVM, and GPR) and (ii) compare different types of precipitation inputs, including four satellite products (CHIRPS, SM2RAIN, GPM, and PERSIANN), one reanalysis product (ERA5), and observed precipitation, to assess which combination of models and precipitation data provides the optimal performance for river discharge simulation. …”
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Effects of AI-generated drawing on students’ learning achievement and creativity in an ancient poetry course by Hui-Chun Chu, Chia-Ying Hsu, Chun-Chieh Wang

“…Therefore, a generative Artificial Intelligence (GenAI) drawing mode is proposed in the present study. In this learning mode, students describe the characters, events, and scenes in the poems in words, and GenAI creates visual representations to immerse students in the contexts of the ancient poems. …”
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Automation of information distribution in adaptive electronic document management systems using machine learning by A. D. Obukhov

“…A new method of the automated information distribution based on machine learning technologies including a mathematical description of the information distribution rules is proposed. …”
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The Impact of Digital Storytelling-Based Learning Environment on Young Children's Science Process Skills by Ali A. Al-Barakat, Omayya M. Al-Hassan, Rommel M. AlAli, Nahla A. Ibrahim

“…The present study aimed at examining the effects of digital storytelling-based learning environment on children’s science process skills such as observation, classification and prediction. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…This study presents a novel approach to the end-of-line (EoL) quality inspection of brushless DC (BLDC) motors by implementing a deep learning model that combines MEL diagrams, convolutional neural networks (CNNs) and bidirectional gated recurrent units (BiGRUs). …”
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