Zobrazeno 1 - 10
of 11
pro vyhledávání: '"M. V. Golosova"'
Autor:
S. A. Bobkov, A. B. Teslyuk, O. Yu. Gorobtsov, O. M. Yefanov, R. P. Kurta, V. A. Ilyin, M. V. Golosova, I. A. Vartanyants
Publikováno v:
Компьютерные исследования и моделирование, Vol 7, Iss 3, Pp 631-639 (2015)
The paper presents the results of application of machine learning methods: principle component analysis and support vector machine for classification of diffraction images produced in experiments at free-electron lasers. High efficiency of this appro
Externí odkaz:
https://doaj.org/article/026a09910ad34b489acf80e620f72819
Autor:
M. V. Golosova, Ruslan P. Kurta, Sergey Bobkov, Oleksandr Yefanov, A. B. Teslyuk, O. Yu. Gorobtsov, V. A. Ilyin, I. A. Vartanyants
Publikováno v:
Компьютерные исследования и моделирование, Vol 7, Iss 3, Pp 631-639 (2015)
The paper presents the results of application of machine learning methods: principle component analysis and support vector machine for classification of diffraction images produced in experiments at free-electron lasers. High efficiency of this appro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94203e4a30fc828f79a67c02c1d6f51a
https://doi.org/10.20537/2076-7633-2015-7-3-631-639
https://doi.org/10.20537/2076-7633-2015-7-3-631-639
Publikováno v:
Journal of Physics: Conference Series. 1085:032013
Contemporary scientific experiments produce significant amount of data as well as scientific publications based on this data. Since volumes of both are constantly increasing, it becomes more and more problematic to establish a connection between a gi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3d1cf55d633a4537f15c77c8f4e91f03
https://doi.org/10.1088/1742-6596/1085/3/032013
https://doi.org/10.1088/1742-6596/1085/3/032013
Publikováno v:
Journal of Physics: Conference Series. 1015:032055
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ccc5afaa8f6b4a6deaf16f25023210b3
https://doi.org/10.1088/1742-6596/1015/3/032055
https://doi.org/10.1088/1742-6596/1015/3/032055
In recent years the concepts of Big Data became well established in IT. Systems managing large data volumes produce metadata that describe data and workflows. These metadata are used to obtain information about current system state and for statistica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c80cdb2f5f9c050be044b92d7f67f7ee
http://cds.cern.ch/record/2134566
http://cds.cern.ch/record/2134566
Publikováno v:
Journal of Physics: Conference Series. 762:012017
Large-scale scientific experiments produce vast volumes of data. These data are stored, processed and analyzed in a distributed computing environment. The life cycle of experiment is managed by specialized software like Distributed Data Management an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::53472a848d7b31200e0bfaae57e4b09f
https://doi.org/10.1088/1742-6596/762/1/012017
https://doi.org/10.1088/1742-6596/762/1/012017
Publikováno v:
Procedia Computer Science. :448-457
The PanDA (Production and Distributed Analysis) workload management system (WMS) was developed to meet the scale and complexity of LHC distributed computing for the ATLAS experiment. PanDA currently distributes jobs among more than 100,000 cores at w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2f107eddbc526ba3c7e5e4691750b4dd
Publikováno v:
Journal of Physics: Conference Series; Oct2018, Vol. 1085 Issue 3, p1-1, 1p
Publikováno v:
Journal of Physics: Conference Series; 2018, Vol. 1015 Issue 3, p1-1, 1p
Publikováno v:
Journal of Physics: Conference Series; 2016, Vol. 762 Issue 1, p1-1, 1p