Proceedings of International Scientific Conference on Telecommunications, Computing and Control

TELECCON 2019
1. Auflage 2021
ISBN: 978-981-336-631-2
Verlag: Springer Nature Singapore

Buch, Englisch, Band 220, 541 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 992 g

Reihe: Smart Innovation, Systems and Technologies

This book provides a platform for academics and practitioners for sharing innovative results, approaches, developments, and research projects in computer science and information technology, focusing on the latest challenges in advanced computing and solutions introducing mathematical and engineering approaches. The book presents discussions in the area of advances and challenges of modern computer science, including telecommunications and signal processing, machine learning and artificial intelligence, intelligent control systems, modeling and simulation, data science and big data, data visualization and graphics systems, distributed, cloud and high-performance computing, and software engineering. The papers included are presented at TELECCON 2019 organized by Peter the Great St. Petersburg University during November 18–19, 2019.

Zielgruppe

Research

Autoren/Hrsg.

Voinov, Nikita

Khan, Sanowar

Schreck, Tobias

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken
• Technische Wissenschaften Elektronik | Nachrichtentechnik Nachrichten- und Kommunikationstechnik
• Mathematik | Informatik EDV | Informatik Angewandte Informatik
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1. Generative adversarial network for detecting cyber threats in industrial systems.- Chapter 2. Detection and prediction of safety faults in inter-device networks applying a set of data-driven methods.- Chapter 3. Development of an algorithm for determining the railway tracks on video image.- Chapter 4. Hardware and software system for collection, storage and visualization meteorological data from a weather stand.- Chapter 5. Plant disease recognition based on multi-dimensional features of leaf RGB images.- Chapter 6. Methodology of service development with a single Application Programming Interface.- Chapter 7. Using Symbolic Computing to Find Stochastic Process Duration Distribution Laws.- Chapter 8. Comparison of the Shape of Digital Models of Pump Components.- Chapter 9. Parametric oscillations of viscoelastic ortotropic rectangular plates of variable thickness.- Chapter 10. Methods and technologies for protecting pharmaceuticalproducts in polymer packaging from counterfeiting.

Über Autor(innen)

Nikita Voinov has been Associate Professor of the Higher School of Software Engineering at the Institute of Computer Science and Technology of Peter the Great St. Petersburg Polytechnic University since 2012, becoming Deputy Director for Science and Research in 2018. Dr. Voinov’s research interests run a gamut of topics including the technologies for developing mobile applications, information management and data storage, cloud infrastructure and services, and data science and analysis of big data. The current research projects he is participating in are “Technologies and toolset for reliable control of production areas of Internet of Things” (joint project with the Indian Institute of Technology Bombay, Mumbai, India) and “Methods and technologies for verification and development of software for modeling and calculations using HPC platform with extramassive parallelism.

Tobias Shreck has been Professor at the Institute of Computer Graphics and Knowledge Visualization at the Faculty for Computer Science and Biomedical Engineering of Graz University of Technology since 2015. His research interests concern visual data analysis and applied 3D object retrieval. Professor Shreck has acted as a principal investigator in several funded research projects, describing how large collections of data can be visually explored and analyzed for data understanding and decision-making. Another focus of research is how users can interactively search for visual patterns in data, assisted by similarity functions, visual quality measures, and novel search interfaces, including approaches based on user sketching and eye tracking, and how to interactively visualize and steer machine learning approaches like clustering and regression analysis by users, supporting effective and scalable data exploration. Potential applications include, among others, data exploration for engineering and industrial applications, in research data repositories, and digital libraries. Professor Shreck has served as a program co-chair for the IEEE Conference on Visual Analytics Science and Technology in 2017 and 2018, and is currently Associate Editor for IEEE Transactions on Visualization and Computer Graphics.

Sanowar Khan has been with the School of Mathematics, Computer Science and Engineering of City, University of London, since 1989. Professor Khan’s research interests cover mathematical modeling and CAD of sensors, actuators and devices, computational electromagnetics, magnetic shape memory smart materials, finite element modeling and numerical methods, and forward and inverse problems in tomographic imaging. Professor Khan is Honorary Professor of SPPU, Fellow of the Institution of Engineering and Technology, the Institute of Measurement and Control, and a member of the IEEE, IEEE Magnetics, Engineering in Medicine and Biology, and Instrumentation and Measurement societies. He is also a founder member of the International Compumag Society and a member of the Journal Editorial Committee of Measurement and Control. Professor Khan is Editor-in-Chief of the journal Sensor Review. He has been Associate Editor of the journal Measurement, and the International Journal on Measurement Technologies and Instrumentation Engineering.