• Aucun résultat trouvé

Preface

N/A
N/A
Protected

Academic year: 2022

Partager "Preface"

Copied!
1
0
0

Texte intégral

(1)

Distributed Information-Computational Resources. XVII International Conference (DICR-2019).

This volume contains the selected papers of the International Conference “Distributed Information- Computational Resources”. The Conference is the latest in a series of events held in different locations across Siberia since 2004. In 2019 the Conference was held in Novosibirsk from the 03th to the 06th of December.

The papers were presented in four sections: Information and computing technologies in medicine and biology, Methods of data processing and analysis, extraction of facts and knowledge, Technologies for building distributed information and computing systems and electronic libraries and digital collections.

Every day of the Conference started with two keynote talks that together represent the main directions of research in distributed information and computing systems in Russia.

The meetings of the Conference were broadcast live on the Internet.

Program Committee

Committee Chair: Academician Yurii I. Shokin, Institute of Computational Technologies SB RAS Deputy Chairmen:

Prof. Dr. Oleg L. Zhizhimov, Institute of Computational Technologies SB RAS Dr. Andrey V. Yurchenko, Institute of Computational Technologies SB RAS Committee Secretary:

Dr. Yurii I. Molorodov, Institute of Computational Technologies SB RAS Committee Members:

Academician Victor V. Alt, Siberian Federal Research Center for Agrobiotechnologies of the RAS Academician Igor V. Bychkov, Matrosov Institute for System Dynamics and Control Theory SB RAS Academician Amanbek Zh. Zhainakov

Dr. Fedor A. Kolpakov

Academician Maksat N. Kalimoldayev Prof. Dr. Vadim P. Potapov

Corresponding member of RAS Sergey I. Smagin Dr. Igor Yu. Turchanovsky

Corresponding member of RAS Anatoly M. Fedotov Corresponding member of RAS Vladimir V. Shaidurov Prof. Dr. A. Fionov

Prof. Dr. Boris Rybko

Références

Documents relatifs

Data Envelopment Analysis (DEA) is a relatively new “data oriented” non-parametric approach for evaluating the performance of complex entities called Decision Making

Pure stream rea- soning systems cannot react to state changes within the matching context (e.g., time window) and the stateless complex event processing system EP-SPARQL would have

The general objective of this subject is that, from the general knowledge of chemistry, biology, inorganic chemistry and biochemistry acquired in previously studied subjects,

Based on the findings here, it suggests that SMEs and large organisations in some ways are focusing on different factors when taking decisions for the adoption of

As a high school mathematics teacher, I approached Analysing Cycles in Biology and Medicine not from the perspective of a biology specialist, but instead from the perspective of

This stage of parametrically related stream data processing and analysis in the information technology logical chain allows us to obtain data stream fractal nature and

In the system under development, a computational and analytical unit for processing and analyzing geological quantitative information is organized in the form of a set of

– Adaptation Quality: While in our previous research, we developed methods that enable the automatic adaptation of workflows by using adaptation knowledge au- tomatically acquired