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

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Fast Predictions of Lattice Energies by Continuous Isometry Invariants of?Crystal Structuresakes weeks of supercomputer time because of slow energy minimizations for millions of simulated crystals. The lattice energy is a key physical property, which hints at thermodynamic stability of a crystal but has no simple analytic expression. Past machine learning approaches to predict the lattice

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Image Recognition for Large Soil Maps Archive Overview: Metadata Extraction and Georeferencing Tool rge national soil surveys which lasted for several decades with the efforts of the former USSR. Such labor-intensive expeditions on countries scale were not repeated since then. The question of future soil dynamics as Earth’s fertile layer became crucial with global population growth and causes larg

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Cross-Lingual Plagiarism Detection Method collection are split into fragments of fixed size. These fragments are indexed in a special inverted index, which maps words to a bit array. Each bit in the bit array shows whether a . sentence contains this word. This index is used for the retrieval of candidate fragments. We employ bit arrays sto

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A System for?Information Extraction from?Scientific Texts in?Russiannd-to-end manner: term recognition, extraction of relations between terms, and term linking with entities from the knowledge base. These tasks are extremely important for information retrieval, recommendation systems, and classification. The advantage of the implemented methods is that the system do

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勉勵(lì)

Interoperability and?Architecture Requirements Analysis and?Metadata Standardization for?a?Research collect, organize, and present the collected requirements; workflows are annotated on the basis of metadata standards for research data provenance, by which requirements for domain ontologies in catalysis are deduced.

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Fast Predictions of Lattice Energies by Continuous Isometry Invariants of?Crystal Structures guarantees a small difference of energies. We compare several kernel methods for invariant-based predictions of energy and achieve the mean absolute error of less than 5?kJ/mole or 0.05?eV/atom on a dataset of 5679 crystals.

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1865-0929 e Domains, DAMDID/RCDL 2021, held in Moscow, Russia, in October 2021*..The 16 revised full papers were carefully reviewed and selected from 61 submissions. The papers are organized in the following topical sections:?problem solving infrastructures, experiment organization, and machine learning appli