Mobile Devices for Arabic Learning in Junior High Schools: The Teachers’ Perspective by Azkia Muharom Albantani, Imam Fitri Rahmadi

“…The present study aims to identify teachers' perceptions of mobile devices use in Arabic learning at junior high schools. …”
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Attitudes Towards Learning English Among The Aliya Madrasah Students in Bangladesh by Abu Rashed Md Mahbuber Rahman, Ilyana Jalaluddin, Zalina Mohd Kasim, Ramiza Darmi

“…However, the results presented no significant difference in the students’ attitudes towards learning English in relation to gender. …”
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Transfer Learning Fusion Approaches for Colorectal Cancer Histopathological Image Analysis by Houda Saif ALGhafri, Chia S. Lim

“…These models outperformed individual transfer learning approaches (<i>p</i> = 0.009), with performance differences attributed to the characteristics of the datasets. …”
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An Efficient Deep Learning Approach for Malaria Parasite Detection in Microscopic Images by Sorio Boit, Rajvardhan Patil

“…<b>Objective:</b> This paper presents EDRI, which is a novel hybrid deep learning model that integrates multiple architectures for malaria detection from red blood cell images. …”
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Securing the metaverse: Machine learning–based perspectives on risk, trust, and governance by Krishnashree Achuthan, Sasangan Ramanathan, Raghu Raman

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Artificial worlds and artificial minds: Authenticity and language learning in digital lifeworlds by Blair Matthews

“…Language learning is increasingly being extended into digital and online spaces that have been enhanced by simulated reality and augmented with data and artificial intelligence. …”
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Deep Learning in motion analysis for false start detection in speedway racing by Jacek Krakowian, Łukasz Jeleń

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Towards automated recipe genre classification using semi-supervised learning. by Nazmus Sakib, G M Shahariar, Md Mohsinul Kabir, Md Kamrul Hasan, Hasan Mahmud

“…Furthermore, we have demonstrated traditional machine learning, deep learning and pre-trained language models to classify the recipes into their corresponding genre and achieved an overall accuracy of 98.6%. …”
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Integrating challenge-based learning and agile methodologies to transform vocational training by Fernando González-Ferriz

“…Purpose: This article aims to provide the scholars in the XXI century with an innovative perspective, based on agile methodologies, enabling them to adapt the traditional teaching-learning process to present and future needs. The objective is to employ a practical approach to train teachers, so that they can redesign traditional methods into dynamic learning experiences which are adapted to new generations. …”
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Impact of transfer learning methods and dataset characteristics on generalization in birdsong classification by Burooj Ghani, Vincent J. Kalkman, Bob Planqué, Willem-Pier Vellinga, Lisa Gill, Dan Stowell

“…Abstract Animal sounds can be recognised automatically by machine learning, and this has an important role to play in biodiversity monitoring. …”
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Federated Learning for Brain Tumor Diagnosis: Methods, Challenges and Future Prospects by Ma Yuhan

“…However, traditional methods face challenges such as data privacy, model interpretability, and data heterogeneity. This paper presents a detailed literature review of the application of Federated Learning (FL) in brain tumor classification, focusing on the necessity of privacy-preserving ML using Magnetic Resonance Imaging (MRI) technology. …”
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Influence of Mind Wandering and Increased Attentional Demands on Multitasking and Implicit Learning by Cameron G. Wittschen, Christopher A. Was

“…The goal of the current study was to replicate resent findings that suggest mind wandering is associated with impaired explicit learning but not implicit learning, and to extend those finding by investigating whether explicit learning is impaired under attentional load, but implicit learning is not. …”
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Enhancing entrepreneurial skills through experiential learning in IoT, AI, and cybersecurity by Livinus Obiora Nweke, Uchenna Franklin Okebanama, Gibson Uwaezuoke Mba

“…Abstract The integration of Internet of Things (IoT), Artificial Intelligence (AI), and cybersecurity presents new opportunities for innovation and entrepreneurship, yet traditional educational approaches often lack the interdisciplinary and applied focus required to develop these competencies. …”
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Distance Learning under the Covid-19 Conditions within Architectural Education by Emel Unver, Asli Sungur

“…Distance learning is one of the means of education used in various levels, from primary school to college. …”
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Innovative Learning Activities for Ethnically Diverse Students in Macedonian Science Education by Katerina Rusevska, Lambe Barandovski, Vladimir Petruševski, Aleksandra Naumoska, Slavica Tofilovska, Marina Stojanovska

“…Working in teams or groups encourages students to exchange their opinions, to try to find solutions together or to win a game. In this way, they learn and improve skills such as collaboration and responsibility. …”
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Trading Strategy of the Cryptocurrency Market Based on Deep Q-Learning Agents by Chester S. J. Huang, Yu-Sheng Su

“…However, most RL-based optimal trading strategies adopted in the cryptocurrency market focus on trading one type of cryptocurrency, whereas most traders in the cryptocurrency market often trade multiple cryptocurrencies. Therefore, the present study proposes a method based on deep Q-learning for identifying the optimal trading strategy for multiple cryptocurrencies. …”
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Promoting Conceptual Learning Using Scaffolded Activities That Incorporate Interactive Simulations by Pooja Ajayan, Raymond Cao, Jack F. Eichler

“…However, incorporating simulation-based activities into large-enrollment gateway courses presents challenges. In an effort to address this, we effectively utilized discussion/recitation sections to implement simulation-based collaborative concept development activities to promote pre-class learning. …”
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Estimating Automobile Crash Characteristics from Images using Deep Learning by Daniel Silver, Hardik Manek, Matthew Kay, Paul Travis

“…Based on the predicted severity levels of injury, insurance companies can estimate the claim’s cost and better plan their financial reserves. We present a promising approach for accurately predicting Delta-V and LOC using deep learning methods, without the need for a forensic crash reconstruction. …”
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Leveraging Deep Learning for Real-Time Coffee Leaf Disease Identification by Opeyemi Adelaja, Bernardi Pranggono

“…This study aims to address existing methods’ limitations and provide a more efficient, reliable, and cost-effective solution for coffee leaf disease identification. It presents a novel approach to the real-time identification of coffee leaf diseases using deep learning. …”
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Machine Learning-Based Forecasting Active Power Loss in Distribution Systems by Haider Waseem, Batool Seema, Milazzo Federica, Ha Quang P.

“…This paper presents an ensemble learning approach to predict the active power losses during the allocation and sizing of distributed generation (DG) units in power distribution networks. …”
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