• Aucun résultat trouvé

Preface

N/A
N/A
Info
Télécharger
Protected

Academic year: 2022

Partager "Preface"

Copied!
1
0
0

Chargement.... (Voir le texte intégral maintenant)

Texte intégral

(1)

Spatial Data Processing for Monitoring of Natural and Antropogenic Processes (SDM-2019) This volume contains the proceedings of the All-Russian Conference “Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes”. The Conference is the latest in a series of events held in different locations across Siberia since 2008. In 2019 the Conference was held in Berdsk from the 26th to the 30th of August.

The papers were presented in three sections: Integrated Geoinformational Technologies and Systems for Monitoring Applications, Operative Regional Satellite Monitoring of the Environment, and Modelling and Monitoring of Ecological Processes and Systems. Every day of the Conference started with two keynote talks that together represent the main directions of research in spatial data processing in Russia.

Program Committee

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

Academician Victor V. Alt, Siberian Federal Research Center for Agrobiotechnologies of the Russian Academy of Sciences

Academician Igor V. Bychkov, Matrosov Institute for System Dynamics and Control Theory SB RAS Prof. Dr. Oleg I. Potaturkin, Institute of Automation and Electrometry SB RAS

Committee Secretary:

Dr. Igor A. Pestunov, Institute of Computational Technologies SB RAS Committee Members:

Dr. Sergey M. Borzov Dr. Yury I. Vinokurov Dr. Sayana Zh. Vologzhina Prof. Dr. Evgeny P. Gordov

Prof. Dr. Alexander P. Guk Dr. Nikolay N. Dobretsov

Academician Amanbek Zh. Zhainakov Academician Maksat N. Kalimoldayev Prof. Dr. Anatoly A. Lagutin

Prof. Dr. Vladimir V. Moskvichev Prof. Dr. Lyudmila F. Nozhenkova Prof. Dr. Vadim P. Potapov

Prof. Dr. Aleksandr V. Puzanov Prof Dr. Irina N. Rotanova Dr. Gennady M. Ruzhnikov

Corresponding member of RAS Sergey I. Smagin Academician Victor A. Soifer

Academician Alexander L. Stempkovsky Prof. Dr. Igor A. Sutorikhin

Academician Arnold K. Tulokhonov Dr. Igor Yu. Turchanovsky

Corresponding member of RAS Anatoly M. Fedotov Prof. Dr. Gennady M. Tsibulskiy

Dr. Tumen N. Chimitdorzhiev

Corresponding member of RAS Vladimir V. Shaidurov Dr. Oleg E. Yakubailik

Références

Télécharger maintenant ( PDF - 1 Page - 40.43 KB )

Documents relatifs

The Workshop Programme Methodologies and Resources for Processing Spatial Language

This is particularly relevant to the development of language interfaces for spatial systems where the types of representation and reasoning used by applications such as robots

Proceedings of the EAA Spatial Audio Signal Processing symposium

LINEAR BINAURAL AMBISONICS DECODING Due to the signal- and frequency-dependent nature of the proposed algorithm (described in Section 3) it is assumed that the input ambisonic

An Interactive Enironment for Modeling the Processes of ERS Data Processing and Analysis

Remote sensing, information systems, satellite data processing, processes mod- eling, interactive modeling environment, algorithmic sequence, information query, end us- er.. 1

Methods of Spatial Data Processing Based on Bayesian Approach for Environmental Monitoring

In [3] was shown that the problem of ensemble smoothing can be solved sequentially in time by using the available data at each time step to estimate val- ues over the given

Distributed Data Processing of the Compass Experiment

Since the summer of 2017, the data processing system has been working in a production mode, distributing jobs to two traditional Grid sites: CERN and JINR.. There

Approach to the Algorithms for the Analysis and Processing of Data from IT-Services Monitoring System

Within the framework of the current level of IT monitoring system development, the data volume in MCC JSC Russian Railways is 11 terabytes, and this value

The Framework for Hypothesis Verification and Analysis of Natural Language Processing Results for the Russian Language

Ivashchenko M.V.: Analiz metodov avtomatizirovannogo vydeleniya klyuchevyh slov iz tekstov na estestvennom yazyke [Analysis of methods for automated ex- traction of keywords from

Data gathering and analysis for the monitoring of the Russian labour market

This project’s aim is to provide country-level monitoring and analysis of the labour market basing on the publicly available data on job offers, CVs and