Titlebook: Big-Data-Analytics in Astronomy, Science, and Engineering; 9th International Co Shelly Sachdeva,Yutaka Watanobe,Subhash Bhalla Conference p

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Cascaded Anomaly Detection with Coarse Sampling in Distributed Systemsects of limiting the number of parameters and the sampling rate reduction on the detection performance of selected classic ML algorithms. Moreover, an example of microservice architecture for coarse network anomaly detection for a network node is presented.

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Big Data Management for Policy Support in Sustainable Development requires a holistic perspective of several dimensions of human society and addressing them together. With the increasing proliferation of Big Data, Machine Learning, and Artificial Intelligence, there is increasing interest in designing Policy Support Systems (PSS) for supporting policy formulation

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Symbolic Regression for Interpretable Scientific Discoverytly from data. The combination of SR with deep learning (e.g. Graph Neural Network and Autoencoders) provides a powerful toolkit for scientists to push the frontiers of scientific discovery in a data-driven manner. We briefly overview SR, autoencoders and GNN and highlight examples where they have b

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A Front-End Framework Selection Assistance System with Customizable Quantification Indicators Based evolution and big variety. Prior research has revealed several indicators that developers consider important when selecting a framework. In this study, we propose and develop a system that assists developers in the selection process of a front-end framework, which collects data from repository and

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Autonomous Real-Time Science-Driven Follow-up of Survey Transientses for years to come. However, their data throughput has overwhelmed the ability to manually synthesize alerts for devising and coordinating necessary follow-up with limited resources. The advent of Rubin Observatory, with alert volumes an order of magnitude higher at otherwise sparse cadence, prese

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Deep Learning Application for Reconstruction of Large-Scale Structure of the Universerging method to measure large-scale intensity fluctuations of spectral lines emitted from galaxies and intergalactic medium. Observing their large-scale distributions enables us to study cosmology and galaxy formation and evolution. One of the problems with the LIM is observational noises and line i

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Identification of Distinctive Behavior Patterns of Bots and Human Teams in Soccert to examine whether is possible to assess similarity of play styles between different human teams and artificial teams in soccer. We rely on “behavior fingerprints” based on heat maps and their comparison using dot product. Our method shows no distinctive differences between the fingerprints of hum

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