This contributed volume discusses diverse topics to demystify the rapidly emerging and evolving blockchain technology, the emergence of integrated platforms and hosted third-party tools, and the development of decentralized applications for various business domains. It presents various applications that are helpful for research scholars and scientists who are working toward identifying and pinpointing the potential of as well as the hindrances to this technology.

Blockchain is an emerging technology that has the potential to significantly enhance the safety of transactions across a variety of transaction networks, including banking, supply chain, and others. By the year 2030, it is anticipated that Blockchain technology will have contributed $3.1 trillion in new company value. It serves as the foundation for a dynamic distributed ledger, which is something that can be used to cut down on the amount of time spent documenting transactions between parties, eliminate the expenses that are associated with intermediaries, and lower the danger of fraud and tampering. This book’s objective is to provide a comprehensive examination of the many ways in which blockchain technology might be adapted to, and used for practical business applications. Blockchain technology is gaining traction in all industries that do high-volume transactions daily. This book covers all there is to know about blockchain technology and may be used by computer science postgraduate students, researchers, and practitioners at both the fundamental and intermediate levels. It demonstrates the quick progress that has been accomplished in the current business model by employing the principles of blockchain technology. This book examines both the theoretical underpinnings of Blockchain technology as well as its practical implementations. Readers will get an understanding of the trust model, distributed ledger, and decentralized peer-to-peer network that are characteristics of Blockchain technology. They will also get familiar with the fundamental elements of Blockchain technology, including transactions, blocks, block headers, and chains; Blockchain's operations, including hashing, verification, validation, and consensus models; Blockchain's underlying algorithms; and the fundamentals of trust, including hard forks and soft forks. The principles of Smart Contracts, Proof of Work, and Proof of Stack will also be presented, along with the introduction of public and private Blockchain networks that are analogous to Bitcoin and Ethereum.

This book concentrates on the sustainable applications of the Blockchain Technology across multiple latest computational knowledge domains. It covers the feasible and practical collaboration of Blockchain Technology with latest Sustainable Smart Computing Technologies. It will target the vast applications of Blockchain in the field of Internet of Things, Artificial Intelligence, and Cybersecurity. The book effectively provides satisfactory information about the essentials of Blockchain and IoT to a typical pursuer alongside encouraging an examination researcher to distinguish some modern issue regions that rise up out of the intermingling of the two advancements. Besides, the creators talk about pertinent application zones, for example, smart city, e-social insurance, and so forth along the course of the book. • Covers the recent advancements in Blockchain technology • Discusses the applications of Blockchain technology for real life problems • Address the challenges related to implementation of Blockchain technology • Includes case studies • Includes the latest trends and area of research in Blockchain Technology This book is primarily aimed at graduates, researchers and professions working in the field of blockchain technology.

Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision. Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.

The rapid advancements in Artificial Intelligence (AI), specifically in Natural Language Processing (NLP) and Generative AI, pose a challenge for academic scholars. Staying current with the latest techniques and applications in these fields is difficult due to their dynamic nature, while the lack of comprehensive resources hinders scholars' ability to effectively utilize these technologies. Advanced Applications of Generative AI and Natural Language Processing Models offers an effective solution to address these challenges. This comprehensive book delves into cutting-edge developments in NLP and Generative AI. It provides insights into the functioning of these technologies, their benefits, and associated challenges. Targeting students, researchers, and professionals in AI, NLP, and computer science, this book serves as a vital reference for deepening knowledge of advanced NLP techniques and staying updated on the latest advancements in generative AI. By providing real-world examples and practical applications, scholars can apply their learnings to solve complex problems across various domains. Embracing Advanced Applications of Generative AI and Natural Language Processing Modelsequips academic scholars with the necessary knowledge and insights to explore innovative applications and unleash the full potential of generative AI and NLP models for effective problem-solving.

This book highlights the latest trends and advances in applications of digital technologies in construction engineering and management. A collection of chapters is presented, explicating how advanced technological solutions can innovatively address challenges and improve outcomes in the construction industry. Promising technologies that are highlighted include digital twins, virtual reality, augmented reality, artificial intelligence, robotics, blockchain, and distributed ledger technologies. The first section presents recent applications of extended reality technologies for construction education and advanced project control. The subsequent chapters explore Artificial Intelligence (AI), blockchain, and BIM-enabled digitalization in construction through a series of case studies, reviews, and technical studies. Innovative technologies and digitalized solutions are proposed for improved design, planning, training, monitoring, inspection, and operations management in Architectural, Engineering and Construction (AEC) contexts. In addition to the technological perspectives and insights presented, pressing issues such as decarbonization, safety, and sustainability in the built environment are also discussed. This book provides foundational knowledge and in-depth technical studies on emerging technologies for students, academics, and industry practitioners. The research demonstrates how the effective use of new technologies can enhance work methods, transform organizational structures, and bring profound advantages to construction project participants.

The three-volume set LNCS 12681-12683 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2021, held in Taipei, Taiwan, in April 2021. The total of 156 papers presented in this three-volume set was carefully reviewed and selected from 490 submissions. The topic areas for the selected papers include information retrieval, search and recommendation techniques; RDF, knowledge graphs, semantic web, and knowledge management; and spatial, temporal, sequence, and streaming data management, while the dominant keywords are network, recommendation, graph, learning, and model. These topic areas and keywords shed the light on the direction where the research in DASFAA is moving towards. Due to the Corona pandemic this event was held virtually.

Artificial Intelligence Technology in Healthcare: Security and Privacy Issues focuses on current issues with patients’ privacy and data security including data breaches in healthcare organizations, unauthorized access to patients’ information, and medical identity theft. It explains recent breakthroughs and problems in deep learning security and privacy issues, emphasizing current state-of-the-art methods, methodologies, implementation, attacks, and countermeasures. It examines the issues related to developing artifiicial intelligence (AI)-based security mechanisms which can gather or share data across several healthcare applications securely and privately. Features: Combines multiple technologies (i.e., Internet of Things [IoT], Federated Computing, and AI) for managing and securing smart healthcare systems. Includes state-of-the-art machine learning, deep learning techniques for predictive analysis, and fog and edge computing-based real-time health monitoring. Covers how to diagnose critical diseases from medical imaging using advanced deep learning-based approaches. Focuses on latest research on privacy, security, and threat detection on COVID-19 through IoT. Illustrates initiatives for research in smart computing for advanced healthcare management systems. This book is aimed at researchers and graduate students in bioengineering, artificial intelligence, and computer engineering.