DEVELOPING A CELIOTM PROGRAMMING LEARNING TOOL TO FACILIATE TEACHING AND LEARNING DATA STRUCTURE CONCEPTS IN C++ FOR NOVICE PROGRAMMERS by Adam B. Mtaho, Masoud M. Masoud, Leonard J. Mselle

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VisualCodeMOOC: A course platform for algorithms and data structures integrating a conversational agent for enhanced learning through dynamic visualizations by Mingyuan Li, Duan Wang, Erick Purwanto, Thomas Selig, Qing Zhang, Hai-Ning Liang

“…The abstract nature of algorithms and data structures poses challenges for students, and the integration of visualization into comprehensive learning systems remains underexplored. …”
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Latent space improved masked reconstruction model for human skeleton-based action recognition by Enqing Chen, Xueting Wang, Xin Guo, Ying Zhu, Dong Li

“…These help the encoder learn deeper data structures and more discriminative and generalized feature representations. …”
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Enhancing privacy and traceability of public health insurance claim system using blockchain technology by Andry Alamsyah, I. Putu Sadhu Setiawan

“…The physical data architecture provides a class diagram detailing data structures and actor relationships. A proof-of-concept prototype was developed to demonstrate the core functionalities of the new system.ResultsBy integrating blockchain technology, our prototype ensures authorized access, bolsters data privacy, and maintains data integrity in the NHI claim workflow. …”
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Isolation of Karanjin from Pongamia Pinnata and Its Identification by Difference Analytical Techniques by Sushil Kumar Dhanmane, Faisal A. Salih

“…From TLC, HPL, IR, 1HNMR, 13CNMR spectra data, structure elucidation was done and the structure was confirmed as karanjin. …”
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Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

“…To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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Reach&Grasp: a multimodal dataset of the whole upper-limb during simple and complex movements by Dario Di Domenico, Inna Forsiuk, Simon Müller-Cleve, Simone Tanzarella, Florencia Garro, Andrea Marinelli, Michele Canepa, Matteo Laffranchi, Michela Chiappalone, Chiara Bartolozzi, Lorenzo De Michieli, Nicolò Boccardo, Marianna Semprini

“…The data is organized following the Brain Imaging Data Structure standard format and have been validated to ensure its reliability. …”
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The fault systems that control the occurrences of iron ore deposits in northeastern Aswan, Egypt by Mohamed Abd El-Wahed, Ibrahim A. Salem, Mohamed Attia, Dina Younis

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WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis by Carolyn B. McNabb, Ian D. Driver, Vanessa Hyde, Garin Hughes, Hannah L. Chandler, Hannah Thomas, Christopher Allen, Eirini Messaritaki, Carl J. Hodgetts, Craig Hedge, Maria Engel, Sophie F. Standen, Emma L. Morgan, Elena Stylianopoulou, Svetla Manolova, Lucie Reed, Matthew Ploszajski, Mark Drakesmith, Michael Germuska, Alexander D. Shaw, Lars Mueller, Holly Rossiter, Christopher W. Davies-Jenkins, Tom Lancaster, C. John Evans, David Owen, Gavin Perry, Slawomir Kusmia, Emily Lambe, Adam M. Partridge, Allison Cooper, Peter Hobden, Hanzhang Lu, Kim S. Graham, Andrew D. Lawrence, Richard G. Wise, James T. R. Walters, Petroc Sumner, Krish D. Singh, Derek K. Jones

“…Data are organised using the Brain Imaging Data Structure (BIDS). In addition to raw data, we provide brain-extracted T1-weighted images, and quality reports for diffusion, T1- and T2-weighted structural data, and blood-oxygen level dependent functional tasks. …”
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Analysis of ChatGPT-Generated Codes Across Multiple Programming Languages by Sally Almanasra, Khaled Suwais

“…The study addresses key questions related to the performance, code quality, and error management of AI-generated code by analyzing solutions for 300 data structure problems and 300 problems from the LeetCode platform. …”
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Peningkatan Performa Komputasi Sistem Navigasi Transportasi Publik Pada Perangkat Bergerak Melalui Penerapan Teknik Kompresi Data dan Penyederhanaan Graf by Aryo Pinandito, Agi Putra Kharisma, Muhammad Aminul Akbar, Mochamad Chandra Saputra

“…The plans are generated from the implementation of Dijkstra's algorithm, which is modeled in the graph data structure. This study determines the effectiveness of using JSON format, the bandwidth saved for distributing data on the Internet from Zlib data compression and Base64 encoding, and analyzes additional memory usage due to compression and the impact of data simplification through a visual approach on transport network graphs with the Douglas-Peucker algorithm. …”
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Advances in machine learning applications to resource technology for organic solid waste by Hongzhi MA, Yichan LIU, Jihua ZHAO, Fan FEI, Ming GAO, Qunhui WANG

“…Furthermore, selecting the right ML model for a specific task requires careful consideration of the data structure, the complexity of the problem, and the desired outcomes. …”
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