Exploration of the relationships between the information and communication technology (ICT) and the education system in Morocco by Abdelkarim Taam, Amine Amar, Brahim Hmedna, Khalid Benabbes, El Menzhi Kaoutar, Rachid Daoudi, Adil El Makrani

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A Fast Logdet Divergence Based Metric Learning Algorithm for Large Data Sets Classification by Jiangyuan Mei, Jian Hou, Jicheng Chen, Hamid Reza Karimi

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Analysis of the TGT Cooperative Learning Model in Physics Learning: In Terms of The Implementation of Procedures and Principles by Alfajri Adha, Affan Rera, Salman Al Farisi

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Effects of cooperative learning on students’ learning outcomes in physical education: a meta-analysis by Hulusi Boke, Yalin Aygun, Sakir Tufekci, Fatma Hilal Yagin, Burak Canpolat, Goktug Norman, Pablo Prieto-González, Luca Paolo Ardigò

“…This meta-analysis examines the effect of Cooperative Learning (CL) interventions, compared to traditional instructional methods, on students’ learning outcomes across affective, cognitive, physical, and social domains in physical education (PE). …”
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Industrial multi-machine data aggregation, AI-ready data preparation, and machine learning for virtual metrology in semiconductor wafer and slider production by Feiyang Ou, Julius Suherman, Chao Zhang, Henrik Wang, Sthitie Bom, James F. Davis, Panagiotis D. Christofides

“…Smart Manufacturing is rooted in AI, Machine Learned (ML), and Data Synchronized (DS) modeling to tap into invaluable operating data. …”
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An Analysis of the Online Teaching and Learning in Clothing and Textiles Programmes in Zimbabwe’s Institutions of Higher Learning by Senzeni Tshuma, Chipo Chuma, Edlight Mutungwe

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Correlation Analysis of Misconceptions on Motivation, Learning Outcomes, and Critical Thinking Skills in Physics Learning by Nurul Afni, Abdul Halim, Evendi Evendi, Fitria Herliana, Lilia Halim

“…Several previous studies have shown that misconceptions are related to student achievement or learning outcomes and several latent variables. Therefore, the research aims to determine the relationship between misconceptions, motivation, learning outcomes, and critical thinking skills in learning physics on Newton's law material. …”
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Failure Analysis of Static Analysis Software Module Based on Big Data Tendency Prediction by Jian Zhu, Qian Li, Shi Ying

“…In the paper, static analysis software is taken as the research object, the errors or failures caused by the potential defects of the software modules are analyzed, and a software analysis method based on big data tendency prediction is proposed to use the software defects of the stacked noise reduction sparse analyzer to predict. …”
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Language task-based fMRI analysis using machine learning and deep learning by Elaine Kuan, Elaine Kuan, Elaine Kuan, Viktor Vegh, Viktor Vegh, Viktor Vegh, John Phamnguyen, John Phamnguyen, John Phamnguyen, Kieran O’Brien, Amanda Hammond, David Reutens, David Reutens, David Reutens, David Reutens

“…Data comprising of seven task-based language fMRI paradigms were collected from 26 individuals, and ML and DL models were trained to classify voxel-wise fMRI time series.ResultsThe general machine learning and the interval-based methods were the most promising in identifying language areas using fMRI time series classification. …”
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Advancing Alzheimer’s disease detection: a novel convolutional neural network based framework leveraging EEG data and segment length analysis by Md Nurul Ahad Tawhid, Siuly Siuly, Enamul Kabir, Yan Li

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Hamming Diversification Index: A New Clustering-Based Metric to Understand and Visualize Time Evolution of Patterns in Multi-Dimensional Datasets by Sarthak Pattnaik, Eugene Pinsky

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Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

“…To address these challenges, we propose the Sentiment Analysis and Seasonal Decomposition (SASD) framework, a novel approach to enhance livestock price forecasting by integrating sentiment analysis of news data with seasonal decomposition of historical price trends. …”
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Spatiotemporal Analysis of Human Mobility in Greater Tokyo Area Using Hourly 500 m Mobile Spatial Statistics from 2019 to 2021 by Thanakrit Yoongsomporn, Alvin Christopher Galang Varquez, Sunkyung Choi, Makoto Okumura, Shinya Hanaoka, Manabu Kanda

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Development of data driven models to accurately estimate density of fatty acid ethyl esters by Walid Abdelfattah, Munthar Kadhim Abosaoda, Hardik Doshi, H. S. Shreenidhi, Manoranjan Parhi, Devendra Singh, Prabhjot Singh, Abdolali Yarahmadi Kandahari

“…Results indicate that the dataset is highly well-suited for developing reliable models based on data. Analysis reveals that temperature exerts a considerable influence on density, with pressure also playing a critical role. …”
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Federated learning in food research by Zuzanna Fendor, Bas H.M. van der Velden, Xinxin Wang, Andrea Jr. Carnoli, Osman Mutlu, Ali Hürriyetoğlu

“…The use of machine learning in food research is sometimes limited due to data sharing obstacles such as data ownership and privacy requirements. …”
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GastroEndoNet: Comprehensive endoscopy image dataset for GERD and polyp detectionMendeley Data by Abu Kowshir Bitto, Md. Hasan Imam Bijoy, Kamrul Hassan Shakil, Aka Das, Khalid Been Badruzzaman Biplob, Imran Mahmud, Syed Md. Minhaz Hossain

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The problem of analysis of big web data and the use of data mining technology for processing and searching patterns in big web data on a practical example by K. V. Mulyukova, V. M. Kureichik

“…The study included a review of bibliographic sources on big data analysis problems.Data Mining technology was used to analyze large web data, as well as computer modeling of a practical problem using the C # programming language and creating a DDL database structure for accumulating web data.Results. …”
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Patch-Based Deep-Learning Model With Limited Training Dataset for Liver Tumor Segmentation in Contrast-Enhanced Hepatic Computed Tomography by Yuqiao Yang, Muneyuki Sato, Ze Jin, Kenji Suzuki

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Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data by Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam

“…To ensure reliability, robust data preprocessing was conducted using the Monte Carlo outlier detection (MCOD) method to recognize and manage data outliers. …”
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Deciphering the proteome of Escherichia coli K-12: Integrating transcriptomics and machine learning to annotate hypothetical proteins by Sagarika Chakraborty, Zachary Ardern, Habibu Aliyu, Anne-Kristin Kaster

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