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

by Henry Han (Editor)

Overview

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 focus on AI security in next-generation data science and address a range of challenges, from protecting sensitive data to mitigating adversarial threats.

Product Details

ISBN-13:	9783031678714
Publisher:	Springer-Verlag New York, LLC
Publication date:	08/22/2024
Series:	Communications in Computer and Information Science , #2158
Sold by:	Barnes & Noble
Format:	eBook
File size:	33 MB
Note:	This product may take a few minutes to download.

Table of Contents

.- 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.