Automated grading of oleaster fruit using deep learning by Aram Azadpour, Kaveh Mollazade, Mohsen Ramezani, Hadi Samimi-Akhijahani

“…The results of this study demonstrate the effectiveness of deep learning-based models in developing grading machines for the oleaster fruit.…”
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CONTENT AND LANGUAGE INTEGRATED LEARNING IN RUSSIAN TECHNICAL UNIVERSITIES by T. V. Sidorenko, S. V. Rybushkina

“…The efficacy of the approach made Russian educators look at its side taking into account the lack of «drag and drop» practices and the specificity of Russian university environment, including national specificity of the country in general.The aim of the article is to work out some recommendations for smooth implementation of CLIL in Russian higher education.Methodology and research methods. The methods involve system-based and comparative analysis, generalization and modeling.Results and scientific novelty. …”
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Construction and evaluation of a home rehabilitation nursing model for patients with benign paroxysmal positional vertigo based on Internet of Things technology (基于物联网技术的耳石症患者居家康复护... by LIU Huan (刘欢)

“…Objective To construct a home rehabilitation nursing model for patients with benign paroxysmal positional vertigo based on Internet of Things (IoT) technology, and to verify its effect on reducing the recurrence rate of the disease and improving the quality of life. …”
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Enhancing mosquito classification through self-supervised learning by Ratana Charoenpanyakul, Veerayuth Kittichai, Songpol Eiamsamang, Patchara Sriwichai, Natchapon Pinetsuksai, Kaung Myat Naing, Teerawat Tongloy, Siridech Boonsang, Santhad Chuwongin

“…This study introduces a self-supervised learning-based image classification model using the Bootstrap Your Own Latent (BYOL) algorithm, designed to enhance mosquito species identification efficiently. …”
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Deep reinforcement learning applications and prospects in industrial scenarios by JING TAN, Ligang YANG, Xiaorui LI, Zhaolin YUAN, Yunduan CUI, Chao YAO, Zongjie WANG, Xiaojuan BAN

“…The review begins with an introduction to the fundamental concepts of DRL, including the Markov decision process (MDP) framework and the Bellman equation for optimizing decision-making strategies, followed by an exploration of the latest advancements in both online and offline reinforcement learning algorithms. The paper systematically examines the background and challenges of industrial control systems, highlighting the limitations of traditional methods such as proportional–integral–derivative (PID) control and rule-based systems when faced with multi-variable, nonlinear, and dynamic processes. …”
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Integrated Approach to the Introduction of Blended Learning in Higher Education by A. V. Rajkhlina, M. V. Gromova, R. V. Kolesov

“…The article summarizes the theoretical developments on the issue of blended learning, emphasizes the relevance of the problem of its implementation, specifies the stakeholders and their positions, and formulates proposals for options for teaching in a blended format.Materials and methods: the first part of the article was written in line with a review study, namely, a quantitative analysis and comparison of the content of scientific publications on the topic under study. …”
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Graph representation learning via enhanced GNNs and transformers by Hongrui Mu, Chengchen Zhou, Qiancheng Yu, Qunyue Mu

“…To address the prevalent deficiencies in local feature learning and edge information utilization inherent to GTs, we propose EHDGT, a novel graph representation learning method based on enhanced graph neural networks (GNNs) and Transformers. …”
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Sensor-Based Gait Analysis: A Comparative Study of Ultrasonic and Laser Sensors for Gait Monitoring in Rollator-Assisted Walking by Ivan Omeko, Stefan Twieg, Martin Obert

“…A crucial aspect of this system is the detection and correction of the user's posture of legs. This is based on measuring the distance between the user and the rollator, among other methods. …”
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A Virtual Escape Room Plot to Enhance Undergraduate Dental Students’ Skills in Radiographic Differential Diagnosis by Fatma Fayez Badr, Hanadi M. Khalifa

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Unbalancing Datasets to Enhance CNN Models Learnability: A Class-Wise Metrics-Based Closed-Loop Strategy Proposal by Somayeh Shahrabadi, Victor Alves, Emanuel Peres, Raul Morais Dos Santos, Telmo Adao

“…The results showed that the proposed MbCL methods consistently outperformed linear training, achieving top-accuracies of 32% and 72% for both the encompassed dataset-related contexts, therefore, also indicating that classic and GAN-based augmentation approaches had a positive impact on inference performances as resampling strategies. …”
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Bionics Solution to Learn the Arm Reaching with Collision Avoidance by P. Gorce, P. Bendahan

“…Our simulation was based on the notion of Via Point, which postulates that the motion planning that is divided into specific successive position of the arm. …”
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Transforming EFL students' engagement: How AI-enhanced environments bridge emotional health challenges like depression and anxiety by Huili Yang, Yanping Rui

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Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value... by Jie Zhou

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Student's Readiness in Using Virtual Reality for Physics Learning by Rahmat Rizal, Irwan Muhammad Ridwan, Herni Yuniarti Suhendi, Ifa Rifatul Mahmudah

“…Students' readiness to use technology in learning serves as the basis for determining which steps should be prioritized to prepare for technology-enhanced learning, ensuring that the technology positively impacts the learning quality. …”
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Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data by Mirjam Sophia Glessmer, Rachel Forsyth

“…Since this is a new field, we have not been able to answer this confidently based on published literature, which depicts both very positive as well as highly cautionary accounts. …”
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Mental Health Issues and 24-Hour Movement Guidelines–Based Intervention Strategies for University Students With High-Risk Social Network Addiction: Cross-Sectional Study Using a Ma... by Lin Luo, Junfeng Yuan, Chen Xu, Huilin Xu, Haojie Tan, Yinhao Shi, Haiping Zhang, Haijun Xi

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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

“…Additionally, for almost all feature sets, the statistical significance-based feature reduction method improves the prediction performance in the most of classifiers, contributing elaborate EEG channel and feature analysis. …”
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Shapley additive explanations based feature selection reveals CXCL14 as a key immune-related gene in predicting idiopathic pulmonary fibrosis by Bin Chen, Lu Huan, Junyu Lu, Jinhe Yuan

“…Furthermore, the machine learning-based predictive model demonstrates strong clinical potential and merits further validation in prospective trials to assess its utility and therapeutic implications in real-world settings.…”
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The Efectiveness of Using Interactive Learning Media in Enhancing Learning Motivation and Science Literacy of 6th Grade Elementary School Student on the Topic of World Continents by Efi Tasfiyatul Millah, Dede Trie Kurniawan, Yunus Abidin

“…Based on the research results, it can be concluded that the use of interactive learning media is effective in improving students' learning motivation and science literacy …”
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Spectral Feature Extraction Using Partial and General Method by Bin Jiang, Xi Fang, Yang Liu, Xingzhu Wang, Jie Liu

“…In this paper, a novel gradient-based method together with principal component analysis is proposed for the extraction of partial features of stellar spectra, that is, a feature vector indicating obvious local changes in data, which corresponds to the element line positions in the spectra. …”
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