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This book discusses the trust models for next-generation Blockchain ecosystems. The book provides a comprehensive discussion on various trust factors involving security, anonymization, reputation, governance, economic models, and other relevant determinants. The book covers various topics in breadth and depth. In addition, it sets the foundation to involve the readers in understanding the core theories supplemented with technical and experimental discussion. The book starts by laying out the foundations of trust models in Blockchain ecosystems. The authors then provide a study of existing trust models Blockchain networks. They then provide identification of trust factors and discuss each trust factor. The book concludes with a future outlook of trust-enabling Blockchain ecosystems. Outlines the trust models for next-generation Blockchain ecosystems; Covers the trust issues in various Blockchain ecosystems running in public, private, consortium, and cloud environments; Features issues such has privacy, security, scalability, and requirements in Blockchain.
This book constitutes the thoroughly refereed post conference papers of the 4th International Conference on Blockchain and Trustworthy Systems, Blocksys 2022, held in Chengdu, China, in August 2022. The 26 full papers were carefully reviewed and selected from 56 submissions. The papers are organized in topical sections: Trustworthy Systems; Blockchain; Private Computing.
The four volume set LNCS 9947, LNCS 9948, LNCS 9949, and LNCS 9950 constitues the proceedings of the 23rd International Conference on Neural Information Processing, ICONIP 2016, held in Kyoto, Japan, in October 2016. The 296 full papers presented were carefully reviewed and selected from 431 submissions. The 4 volumes are organized in topical sections on deep and reinforcement learning; big data analysis; neural data analysis; robotics and control; bio-inspired/energy efficient information processing; whole brain architecture; neurodynamics; bioinformatics; biomedical engineering; data mining and cybersecurity workshop; machine learning; neuromorphic hardware; sensory perception; pattern recognition; social networks; brain-machine interface; computer vision; time series analysis; data-driven approach for extracting latent features; topological and graph based clustering methods; computational intelligence; data mining; deep neural networks; computational and cognitive neurosciences; theory and algorithms.
The three volume set LNCS 8834, LNCS 8835, and LNCS 8836 constitutes the proceedings of the 21st International Conference on Neural Information Processing, ICONIP 2014, held in Kuching, Malaysia, in November 2014. The 231 full papers presented were carefully reviewed and selected from 375 submissions. The selected papers cover major topics of theoretical research, empirical study, and applications of neural information processing research. The 3 volumes represent topical sections containing articles on cognitive science, neural networks and learning systems, theory and design, applications, kernel and statistical methods, evolutionary computation and hybrid intelligent systems, signal and image processing, and special sessions intelligent systems for supporting decision, making processes, theories and applications, cognitive robotics, and learning systems for social network and web mining.
Artificial Intelligence (AI) and Machine Learning (ML) are set to revolutionize all industries, and the Intelligent Transportation Systems (ITS) field is no exception. While ML, especially deep learning models, achieve great performance in terms of accuracy, the outcomes provided are not amenable to human scrutiny and can hardly be explained. This can be very problematic, especially for systems of a safety-critical nature such as transportation systems. Explainable AI (XAI) methods have been proposed to tackle this issue by producing human interpretable representations of machine learning models while maintaining performance. These methods hold the potential to increase public acceptance and trust in AI-based ITS. FEATURES: Provides the necessary background for newcomers to the field (both academics and interested practitioners) Presents a timely snapshot of explainable and interpretable models in ITS applications Discusses ethical, societal, and legal implications of adopting XAI in the context of ITS Identifies future research directions and open problems
This book presents the latest techniques, algorithms, research accomplishments and trend in computer science and engineering. It collects together 222 peer reviewed papers presented at the 11th Joint International Computer Conference. The theme of this year is “IT: Intellectual Capital for the Betterment of Human Life”. The articles in this book cover a wide range of active and interesting areas such as Digital Entertainment, Grid Computing, Embedded System, Web Service and Knowledge Engineering. This book serves as a good reference not only for researchers but also for graduate students in corresponding fields.The proceedings have been selected for coverage in:•Index to Scientific & Technical Proceedings (ISTP CDROM version / ISI Proceedings)•CC Proceedings — Engineering & Physical Sciences
Explains the theory behind Machine Learning and highlights how Mathematics can be used in Artificial Intelligence Illustrates how to improve existing algorithms by using advanced mathematics and discusses how Machine Learning can support mathematical modeling Captures how to simulate data by means of artificial neural networks and offers cutting-edge Artificial Intelligence technologies Emphasizes the classification of algorithms, optimization methods, and statistical techniques Explores future integration between Machine Learning and complex mathematical techniques
This book aims to provide practical aspects of, and an introduction to, the applications of various technological advancement tools, such as AI, machine learning to design, big data, cloud computing, and IoT, to model, characterize, optimize, forecast, and do performance prediction of renewable energy exploitation. It further discusses new avenues for energy sources such as hydrogen energy generation and energy storage technologies including existing policies and case studies for a better understanding of renewable energy generation. Features: Covers technologies considered to explore, predict, and perform operation and maintenance of renewable energy sources Aids in the design and use of re...
Blockchain is a type of distributed ledger technology that consists of a growing list of records that are securely linked together using cryptography and numerous applications in every field, including healthcare. Blockchain for Healthcare 4.0: Technology, Challenges, and Applications presents an overview of the recent advances in blockchain technology which have led to new breakthroughs in the healthcare industry, the application of artificial intelligence (AI) with blockchain, challenges, and prospects. Key Features: • Highlights blockchain applications in the biomedical and pharmaceutical industries and remote healthcare. • Discusses applications and advancement in blockchain framewor...
This book constitutes the refereed post-conference proceedings of the 24th International Conference on Enterprise Information Systems, ICEIS 2022, This conference was held virtually due to the COVID-19 crisis, during April 25-27, 2022. The 20 full papers included in this book were carefully reviewed and selected from 197 submissions. They were organized in topical sections as follows: Databases and Information Systems Integration; Artificial Intelligence and Decision Support Systems; Information Systems Analysis and Specification; Human-Computer Interaction; and Enterprise Architecture.