New advances in dependability of networks and systems : proceedings of the seventeenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, June 27-July 1, 2022, Wrocław, Poland / Wojciech Zamojski, Jacek Mazurkiewicz, Jarosław Sugier, Tomasz Walkowiak, Janusz Kacprzyk, editors.
International Conference on Dependability of Computer Systems (17th : 2022 : Wrocław, Poland); Zamojski, Wojciech, editor.; Mazurkiewicz, Jacek (Professor of engineering), editor.; Sugier, Jarosław, editor.; Walkowiak, Tomasz, editor.; Kacprzyk, Janusz, editor.
2022
QA76.76.R44
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title New advances in dependability of networks and systems : proceedings of the seventeenth International Conference on Dependability of Computer Systems DepCoS-RELCOMEX, June 27-July 1, 2022, Wrocław, Poland / Wojciech Zamojski, Jacek Mazurkiewicz, Jarosław Sugier, Tomasz Walkowiak, Janusz Kacprzyk, editors.
Meeting Name International Conference on Dependability of Computer Systems (17th : 2022 : Wrocław, Poland)
ISBN 9783031067464 (electronic bk.)
3031067460 (electronic bk.)
9783031067457
3031067452
DOI https://doi.org/10.1007/978-3-031-06746-4
Published Cham, Switzerland : Springer, 2022.
Language English
Description 1 online resource (xiv, 400 pages) : illustrations (some color).
Other Standard Identifiers 10.1007/978-3-031-06746-4 doi
Call Number QA76.76.R44
Dewey Decimal Classification 004
Summary The book consists of papers on selected topics of dependability analysis in computer systems and networks which were discussed during the 17th DepCoS-RELCOMEX conference held in Wrocław, Poland, from June 27th to July 1st, 2022. Their collection will be an interesting source material for scientists, researchers, practitioners and students who are dealing with design, analysis and engineering of computer systems and networks and must ensure their dependable operation. Being probably the most complex technical systems ever engineered by man (and also, the most dynamically evolving ones), organization of contemporary computer systems and networks cannot be interpreted only as a structure built on the base of unreliable technical resources. Their evaluation must take into account a unique blend of interacting people, networks (together with mobile properties, cloud organization, Internet of Everything, etc.) and a large number of users dispersed geographically and constantly producing an unconceivable number of applications. Research methods being continuously developed for dependability analyses apply newest results of artificial and computational intelligence. Selection of papers in this book illustrates broad range of topics, often multi-disciplinary, which is considered in present-day dependability explorations; it also reveals an increasing role of the latest methods based on machine/deep learning and neural networks in these studies.
Note Includes author index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed June 3, 2022).
Added Author Zamojski, Wojciech, editor.
Mazurkiewicz, Jacek (Professor of engineering), editor.
Sugier, Jarosław, editor.
Walkowiak, Tomasz, editor.
Kacprzyk, Janusz, editor.
Series Lecture notes in networks and systems ; v. 484. 2367-3389
Available in Other Form Print version: 9783031067457
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Measures of Outlierness in High-Dimensional Data under Correlation of Features - with Application for Open-Set Classification, Szymon Datko, Henryk Maciejewski, Tomasz Walkowiak
Multiprocessor tasks scheduling - Fuzzy Logic Approach, Dariusz Dorota
Nonparametric tracking for time-varying nonlinearities using the kernel method, Purva Joshi, Grzegorz Mzyk
Embedded systems' startup code optimization, Patryk Pankiewicz
Influence of accelerometer placement on biometric gaitidentification, Aleksander Sawicki
An Impact of Data Augmentation Techniques on the Robustness of CNNs, Kamil Szyc
Dual Learning Model for Multiclass Brain Tumor classification, Rohit Thanki, Sanna Kaddoura.

Browse Subjects

Show more subjects...

Statistics

from
to
Export