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Titlebook: Data Analytics and Management in Data Intensive Domains; 23rd International C Alexei Pozanenko,Sergey Stupnikov,Nadezhda Kiselyo Conference

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MLDev: Data Science Experiment Automation and Reproducibility Softwaregration of different open source tools for running research experiments. We implement our approach in a prototype open source MLDev software package and evaluate it in a series of experiments yielding promising results. Comparison with other state-of-the-art tools signifies novelty of our approach.
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Response to Cybersecurity Threats of Informational Infrastructure Based on Conceptual Modelsnsity of the data usage. For a successful exposure and the prevention of computer attacks the construction of complex models of the events and infrastructure is required. In this work, the question of the applicability of ontological models and reasoning for supporting response process is examined.
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Cross-Matching of Large Sky Surveys and Study of Astronomical Objects Apparent in Ultraviolet Band Os, but also to discover new and unique objects. In astronomy, cross-matching of catalogues is a standard tool for getting broader information on the objects by combining their data from the surveys performed at different wavelengths, and it allows to solve number of tasks like studying various popul
发表于 2025-3-24 06:14:06 | 显示全部楼层
The Diversity of Light Curves of Supernovae Associated with Gamma-Ray Bursts shown that a core-collapse supernova (SN) accompanies about 50 nearby GRB sources. We have collected about two dozen SNe’ multicolor light curves associated with GRBs. The sample is based on published data, obtained during observations of GRB-SN cases by ground-based observatories all around the wo
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Application of Machine Learning Methods for Cross-Matching Astronomical Cataloguesmatching are analyzed and machine learning methods applied are briefly discussed. The approach is applied for cross-matching of three catalogues: Gaia, SDSS and ALLWISE. Experimental results of application of several machine learning methods for cross-matching these catalogues are presented. Recomme
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Machine Learning Application to Predict New Inorganic Compounds – Results and Perspectivesethods limitations and the subject area peculiarities are considered that must be taken into account when using ML. Solved problems examples of new inorganic compounds design and the results of comparing predictions with new experimental data are given. Systems developed by the authors are considere
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