Xiaobo Zhou – författare

Here are the refereed proceedings of the EUC 2006 workshops, held in conjunction with the IFIP International Conference on Embedded and Ubiquitous Computing in Seoul, Korea, August 2006. The book presents 102 revised papers spanning six workshops: network-centric ubiquitous systems (NCUS 2006), security in ubiquitous computing systems (SecUbiq 2006), RFID and ubiquitous sensor networks (USN 2006), trustworthiness, reliability and services in ubiquitous and sensor networks (TRUST 2006), embedded software optimization (ESO 2006), and multimedia solution and assurance in ubiquitous information systems (MSA 2006).

This book, LNCS 15225, constitutes the refereed proceedings of the 19th International Conference on Green, Pervasive, and Cloud Computing, GPC 2024, which took place in Macao, China, during September 27–30, 2024.

This book serves as a pivotal guide for professionals and researchers within the industrial computing domain, offering an extensive examination of edge computing in industrial environments.

This book aims to provide a comprehensive overview of how artificial intelligence (AI) and big data analytics are transforming bioinformatics and biomedical research. It covers a wide range of computational methods applied to biomedical big data, including genomics, transcriptomics, proteomics, and imaging data, with a focus on their role in precision medicine.The book is structured to guide readers from foundational AI models and data integration techniques to advanced applications in systems biology and drug discovery. It explores key topics such as single-cell and spatial omics analysis, genetic variation studies, and computational modeling of disease processes. Additionally, it highlights cutting-edge approaches in synthetic biology, mRNA optimization, and small molecule generation.Designed for researchers, bioinformaticians, and clinicians, this book bridges the gap between computational sciences and biomedical applications. It aims to equip readers with the necessary knowledge to develop AI-driven solutions for diagnosing diseases, predicting treatment responses, and designing novel therapeutics. By integrating theoretical insights with real-world applications, the book serves as both an educational resource and a reference for ongoing advancements in AI-driven biomedical research.

This book offers a comprehensive and timely guide to advancing the use of AI agents in biomedical data analysis, precision diagnostics, and the development of novel therapeutics. Biomedical AI agents are intelligent software systems that leverage artificial intelligence (AI) and machine learning (ML) to learn, analyze, and perform complex tasks in biomedical research and clinical medicine.The book is structured around two key components: single AI agents and multi-agent AI systems. Core topics include foundational concepts in machine learning, large language models (LLMs), and autonomous AI agents; as well as cutting-edge applications such as AI-powered single-cell analysis, multi-omics data integration, drug discovery, synthetic biology, whole-body digital twins, and autonomous scientific discovery.By bridging computational science and biomedical research, this book fosters collaboration among AI researchers, data scientists, biologists, clinicians, and industry experts, driving innovation in AI-driven biomedical science and healthcare solutions.