Nature of Computation and Communication: 9th EAI International Conference, ICTCC 2023, Ho Chi Minh City, Vietnam, October 26-27, 2023, Proceedings

by Phan Cong Vinh (Editor), Hafiz Mahfooz Ul Haque (Editor)

Overview

This book constitutes the refereed post-conference proceedings of the 9^th International Conference on Nature of Computation and Communication, ICTCC 2023, held in Ho Chi Minh City, Vietnam, in October 2023.
The 12 revised full papers presented were carefully selected from 30 submissions. The papers of ICTCC 2023 cover formal methods for self-adaptive systems and discuss natural approaches and techniques for natural computing systems and their applications.

Product Details

ISBN-13:	9783031594618
Publisher:	Springer Nature Switzerland
Publication date:	05/03/2024
Series:	Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , #586
Edition description:	2024
Pages:	187
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

.- Advances in AI in Computing and communications.

.- Advancing Online Education: An Artificial Intelligence Applied System for Monitoring and Improving Employee Engagement in Financial Enterprise Information Systems.

.- Algebraic Semantics of Register Transfer Level in Synthesis of Stream Calculus-Based Computing Big Data in Livestream.

.- An Approach for Object Recognition in Videos for Vocabulary Extraction.

.- A Self-Organization Model for MAS based on Trust.

.- A Business Process and Data Modelling Approach to Enhance Cyber Security in Smart Cities.

.- Possibilities of using fuzz testing in smart cities applications.

.- Unified Smart City Domain Model for Central Europe.

.- Applying AI and ontologies to the Covid pandemic.

.- AMS: Applied Mathematics in sciences.

.- AMS: Applied Mathematics in sciences.

.- Reasoning With Words: Steps Towards Applying in Mobile System.

.- Applying design of experiments to evaluate the influence of parameters on the economic feasibility of the eco-industrial parks.

.- Comparing LSTM Models for Sk Market Prediction: A Case Study with Apple’s Historical Prices.