Complex, Intelligent and Software Intensive Systems

This book aims to deliver a platform of scientific interaction between the three interwoven challenging areas of research and development of future ICT-enabled applications: Software intensive systems, complex systems, and intelligent systems.
Software intensive systems are systems which heavily interact with other systems, sensors, actuators, devices, other software systems and users. More and more domains are involved with software intensive systems, e.g., automotive systems, telecommunication systems, embedded systems in general, industrial automation systems, and business applications. Moreover, the outcome of web services delivers a new platform for enabling software intensive systems.
Complex systems research is focused on the overall understanding of systems rather than their components. Complex systems are very much characterized by the changing environments in which they act by their multiple internal and external interactions. They evolve and adapt through internal and external dynamic interactions.
The development of intelligent systems and agents which can be characterized by ontologies and their logical foundations builds a fruitful impulse for both software intensive systems and complex systems. Recent research in the field of intelligent systems, robotics, neuroscience, artificial intelligence, and cognitive sciences are very important factors for the future development and innovation of software intensive and complex systems.

Presents recent research on complex, intelligent, and software intensive systems Includes the proceedings of the 19th International Conference on Complex, Intelligent, and Software Intensive Systems Written by experts in the field

Inhalt

A Study on Measurement and Analysis of Harbor Garbage at Night Using Artificial Intelligence Algorithms.- Leveraging Explainable Artificial Intelligence for Colorectal Cancer Prediction Result Analysis on Metagenomic Data.- AD-ZeroNAS: Zero-Shot Proxies for Efficient Neural Architecture Search via Activation Diversity Function on Histopathological Use Cases.- CARL: Efficient Deep Reinforcement Learning via Contrastive Replay.- Optimizing Head Movement Classification Under Varying Lighting Using Spatial and Channel Attention in EfficientNet v2.- Building Ontology from Requirement Boilerplates Using Natural Language Processing.- Hydro-Net: Integrating AI and Satellite Imagery for Precision Canal Building.- Evaluating Machine Learning Models for Predicting NCAA Division I Basketball Wins.- Comparing LLM-Based Query Rewriting Strategies within RAG pipelines for Domain-Routed Legal Question Answering.- Gold Price Analysis based on Machine Learning.