Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Blockchain in Supply Chain Management
Blockchain in Supply Chain Management: Real-World Applications explores how blockchain technology revolutionizes supply chain management. This book details how blockchain provides a decentralized, secure database, transforming how organizations handle data. Blockchain's encrypted blocks create a single, chronological data source, enhancing transparency, reliability, and integrity. We discuss blockchain's impact on the global economy, addressing current complexities in supply chains. The technology ensures data availability, visibility, and trust through permissioned blockchain solutions, making it easier to transfer funds globally without traditional banks. One of blockchain's key benefits is its immutable records, boosting supply chain transparency. The book analyzes blockchain applications across various supply chain industries, including food and beverages, trade finance, and auto retail. We explore the synergy between blockchain and other technologies like IoT, big data, and artificial intelligence. This comprehensive guide is essential for students, academic scholars, and professionals interested in supply chain management.
Advances in Artificial Intelligence and Data Engineering
This book presents selected peer-reviewed papers from the International Conference on Artificial Intelligence and Data Engineering (AIDE 2019). The topics covered are broadly divided into four groups: artificial intelligence, machine vision and robotics, ambient intelligence, and data engineering. The book discusses recent technological advances in the emerging fields of artificial intelligence, machine learning, robotics, virtual reality, augmented reality, bioinformatics, intelligent systems, cognitive systems, computational intelligence, neural networks, evolutionary computation, speech processing, Internet of Things, big data challenges, data mining, information retrieval, and natural language processing. Given its scope, this book can be useful for students, researchers, and professionals interested in the growing applications of artificial intelligence and data engineering.
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications
Machine Learning and Deep Learning in Medical Data Analytics and Healthcare Applications introduces and explores a variety of schemes designed to empower, enhance, and represent multi-institutional and multi-disciplinary machine learning (ML) and deep learning (DL) research in healthcare paradigms. Serving as a unique compendium of existing and emerging ML/DL paradigms for the healthcare sector, this book demonstrates the depth, breadth, complexity, and diversity of this multi-disciplinary area. It provides a comprehensive overview of ML/DL algorithms and explores the related use cases in enterprises such as computer-aided medical diagnostics, drug discovery and development, medical imaging,...
Exploring ESG Challenges and Opportunities
The number of companies that are adopting sustainability strategies and disclosing information related to Environmental, Social and Corporate governance (ESG) issues is on the rise. This special volume encapsulates the transformative journey businesses undertake to balance profitability with responsibility.
Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity
The growth of innovative cyber threats, many based on metamorphosing techniques, has led to security breaches and the exposure of critical information in sites that were thought to be impenetrable. The consequences of these hacking actions were, inevitably, privacy violation, data corruption, or information leaking. Machine learning and data mining techniques have significant applications in the domains of privacy protection and cybersecurity, including intrusion detection, authentication, and website defacement detection, that can help to combat these breaches. Applications of Machine Learning and Deep Learning for Privacy and Cybersecurity provides machine and deep learning methods for ana...
Data Analytics and Learning
This book presents new theories and working models in the area of data analytics and learning. The papers included in this volume were presented at the first International Conference on Data Analytics and Learning (DAL 2018), which was hosted by the Department of Studies in Computer Science, University of Mysore, India on 30–31 March 2018. The areas covered include pattern recognition, image processing, deep learning, computer vision, data analytics, machine learning, artificial intelligence, and intelligent systems. As such, the book offers a valuable resource for researchers and practitioners alike.
Handbook of Research on Technical, Privacy, and Security Challenges in a Modern World
More individuals than ever are utilizing internet technologies to work from home, teach and learn, shop, interact with peers, review medical records, and more. While it is certainly convenient to conduct such tasks via the internet, this increased internet presence has also led to a rise in the search and availability of personal information, which in turn is resulting in more cyber-attacks, privacy breaches, and information leaks. Cyber criminals are using such opportunities to attack governments, organizations, and individuals, making it necessary to anticipate, assess, and mitigate privacy and security threats during this infodemic. The Handbook of Research on Technical, Privacy, and Secu...
IoT Sensors, ML, AI and XAI: Empowering A Smarter World
Zusammenfassung: This book uncovers and presents various real-life applications in the areas of transportation, smart cities, manufacturing, agriculture, disaster management, finance, health care and in other areas by using cutting-edge advanced Machine Learning (ML) techniques such as Deep Learning and Explainable AI (XAI) models using IoT sensor data. The book provides various examples of analyzing large amounts of data, detecting patterns, and making predictions in real-time applications and detailed case studies with practical solutions using various state-of-the-art machine learning and IoT sensor data and all these aspects will benefit the stakeholders. The book is useful for academics, researchers, upper-undergraduate, master and Ph.D. students, engineers and practitioners in sensor/IoT and AI/ML technologies, methods, applications, and related areas, and it also offers valuable insights by suggesting future research directions and providing recommendations within the fields of AI and IoT
Renewable Energy: Generation and Application
The book covers the current status of renewable energy technology, such as solar, wind, hydro and geothermal power engineering and biomass conversion. It focusses on technical challenges and potential future developments in electricity generation. electrical vehicles, heating and cooling, industrial processes and rural electrification. Keywords: Solar Energy, Wind Energy, Wind Farms. Hydropower, Hydroelectric Dams, Geothermal Energy, Biomass Energy, Agricultural Residues, Organic Waste, Electricity Transportation, Global Energy Systems.
Emerging Technologies in Data Mining and Information Security
The book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2018) held at the University of Engineering & Management, Kolkata, India, on February 23–25, 2018. It comprises high-quality research by academics and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, case studies related to all the areas of data mining, machine learning, IoT and information security.
