Henry Horng-Shing Lu – författare

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics.

This book discusses the theory and practice of random number generators that are useful for computer simulation and computer security applications. In addition, the book provides up-to-date research on RNGs including a modern class of efficient RNGs and shows how to search for new RNGs with good quality and how to parallelize these RNGs.

This handbook delves into the multifaceted domain of blockchain technology and its applications, offering insights across technological, economic, and practical dimensions. It is divided into several parts, reflecting analysis techniques specific to different fields of application, including digital finance, security and supply chains, among others.The book begins with a foundational exploration of blockchain technology, providing a comprehensive understanding of its core mechanisms. The analysis extends to cutting-edge topics such as Non-Fungible Tokens (NFTs) and visualization technologies, which reveal the dynamic interplay between digital assets and technological innovation.Cryptocurrency liquidity and market dynamics are also examined, employing principles like Metcalfe's Law and Log-Periodic Power Laws to unravel complex market behaviors. Empirical studies shed light on volatility forecasting and the impact of sudden market jumps, enriching the predictive frameworks for cryptocurrency trading.In the realm of blockchain analytics, advanced methodologies like process mining are applied to uncover patterns in blockchain applications, while network analytics provide tools for fraud detection and heuristic evaluation. Decision-making in blockchain transactions is explored through the lens of mempool dynamics, providing practical insights for optimizing blockchain operations.The narrative extends to business applications, highlighting strategies for blockchain-driven development and the legal and financial implications of Distributed Ledger Technology (DLT). Blockchain’s transformative potential in healthcare is showcased, alongside a survey of federated learning frameworks that leverage blockchain for secure and decentralized machine learning.Security remains a pivotal theme, with a focus on the role of blockchain in cybersecurity and compliance functions. The investigation addresses decentralized finance (DeFi) vulnerabilities through case studies on attacks, offering lessons to enhance system robustness. Finally, the text envisions a future where decentralized models democratize foundational technologies, and blockchain facilitates innovations in maritime supply chains, driving efficiency and transparency in global logistics.This compilation serves as a gateway to understanding the theoretical and practical dimensions of blockchain, emphasizing its evolving role in reshaping industries and economic systems.

Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

Numerous fascinating breakthroughs in biotechnology have generated large volumes and diverse types of high throughput data that demand the development of efficient and appropriate tools in computational statistics integrated with biological knowledge and computational algorithms.

Now in its second edition, this handbook collects authoritative contributions on modern methods and tools in statistical bioinformatics with a focus on the interface between computational statistics and cutting-edge developments in computational biology.