Название: Cyber-Physical Systems: Data Science, Modelling and Software OptimizationАвтор: Alla G. Kravets, Alexander A. Bolshakov
Издательство: Springer
Год: 2024
Страниц: 229
Язык: английский
Формат: pdf (true), epub
Размер: 37.2 MB
This book is devoted to new approaches to modeling and design of cyber-physical systems. Nowadays, cyber-physical systems become widely used in different domains. Scientific society suggests new approaches to engineering and optimization of cyber-physical systems, however, there are still open questions that need to be covered by research and development.
It presents results and findings in the field of Data Science and digital twin engineering for cyber-physical systems. This book provides scientific, practical, and methodological approaches to modeling of complex processes for cyber-physical systems. The authors highlight essential results on software optimization in cyber-physical systems.
The first part focuses on Data Science solutions for cyber-physical systems. It covers topics such as analyzing industrial cyber-physical systems, methods for processing and analyzing large data streams, patent array analysis using a combination of ClickHouse and HDFS, and utilizing patient medical descriptions to enhance the feature space in cyber-physical breast cancer identification systems. Additionally, it discusses comparing feature extraction models for images with multiple annotations and developing a knowledge base for assessing the risks of road accidents during vehicle operation.
The second part is dedicated to modelling in cyber-physical systems. This includes examples of modelling the operation of digital twins, simulating agricultural unmanned vehicles, modelling the flexibility of administrative documents, mathematical modelling of electrolysis technology for hydrogen production, and modelling hydroelastic vibrations of channel walls. Furthermore, this section addresses the optimization of heterogeneous cargo transportation using UAVs with different priority schemes for delivery tasks.
The third part deals with optimizing cyber-physical systems software. It presents a new method for automatically increasing the efficiency of vectorization, selecting stochastic parameters of parallel population algorithms and the ranging impact on the solution's quality, and genetic quantum algorithms.
This chapter considers the use of vectorization in computing as one of the key approaches to improving software efficiency. First, we analyzed the existing approaches to vectorization, their problems and limitations, and the capabilities of modern optimizing compilers for automatic generation of vectorized code using the example of the Intel C++ Compiler. Based on the analysis, we have proposed a new software design method that is used at the initial stages of design and is designed to improve the algorithms of vectorization of calculations in software development. Next, we applied this method to the BLAS operation of multiplying a vector by a matrix, resulting in algorithms for solving this problem optimized for SSE and AVX computing vectorization technologies. The use of these algorithms can significantly reduce the execution time of the program, which is confirmed by the results of computational experiments.
In conclusion, this book offers readers a comprehensive understanding of key aspects of cyber-physical systems, ranging from Data Science to modelling and software optimization. It will be valuable for researchers, engineers, and students interested in this rapidly evolving field.
- Provides the comprehensive review of CPS cyber-core implementation technologies
- Outlines challenging areas in the field of text mining and feature extraction for images
- Describes cyber-physical systems modeling: developing mathematical models as well as designing digital twins
Скачать Cyber-Physical Systems: Data Science, Modelling and Software Optimization