Recent Advances in Next-Generation Data Science Third Southwest Data Science Conference, SDSC 2024, Waco, TX, USA, March 22, 2024, Revised Selected Papers /

This book constitutes the refereed proceedings of the Third Southwest Data Science Conference, on Recent advances in next-generation data science, SDSC 2024, held in Waco, TX, USA, in March 22, 2024. The 15 full papers presented were carefully reviewed and selected from 59 submissions. These papers...

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Detaylı Bibliyografya
Müşterek Yazar: SpringerLink (Online service)
Diğer Yazarlar: Han, Henry (Editör)
Materyal Türü: Elektronik Ekitap
Dil:İngilizce
Baskı/Yayın Bilgisi: Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Edisyon:1st ed. 2024.
Seri Bilgileri:Communications in Computer and Information Science, 2158
Konular:
Online Erişim:https://doi.org/10.1007/978-3-031-67871-4
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505 0 |a  -- Wasserstein graph convolutional network with attention for imbalanced scRNA-seq data knowledge discovery. -- Toward a Unified Cybersecurity Knowledge Graph: Leveraging Ontologies and Open Data Sources. -- How does normalization impact clustering?. -- Quantitative Stock Market Modeling Using Multivariate Geometric Random Walk. -- Disease Similarity and Disease Clustering. -- Composition analysis and identification of ancient glass products. -- Data entropy-based imbalanced learning. -- Analysis of the changes in microbial community during the fermentation of Feng-flavour Baijiu. -- EnhanciGraph: Visualizing Enhancer-Gene Interactions. -- Event-triggered Control for Synchronization of Chaotic Delayed Lur’e Systems with Stochastic cyber-attacks. -- In-game Win Prediction Models for Cricket. -- Finite-time outer average synchronization between two coupled heterogeneous complex dynamical networks and its application in secure communication. -- Classification of in-situ Solar Wind Data Measured by Solar Orbiter/SWA-PAS and HIS using Machine Learning. -- Node classification with Multi-hop Graph Convolutional Network. -- PyDaskShift: Automatically Convert Loop-Based Sequential Programs to Distributed Parallel Programs. 
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