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Green M: Cryptography for Everyone

Cryptography for Everyone

Cybersecurity for Healthcare Systems in the Internet of Medical Things Era

Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

As data continues to grow exponentially, knowledge of data science and machine learning has become more crucial than ever. Machine learning has grown exponentially, however, the abundance of resources can be overwhelming

Using SAS Enterprise Miner

Data Science and Machine Learning for Non-Programmers

This unique compendium presents the basics of the theory of computing at a level and in a manner that can be easily understood by computer science students in a large university. It offers the student a firm foundation in logical reasoning and covers many traditional topics in unconventional ways.The useful reference text benefits professionals, academics, researchers and undergraduate students in the area of theoretical computer science.

Foundation Of Computation: Languages And Machines

Advanced Intelligence Methods for Data Science and Optimization covers the latest research trends and applications of AI topics such as deep learning, reinforcement learning, evolutionary algorithms, Bayesian optimization, and swarm intelligence. The book is a comprehensive guide that provides readers with theoretical concepts and case studies for applying advanced intelligence methods to real-world problems. Authored by a team of renowned experts in the field, the book offers a holistic approach to understanding and applying intelligence methods across various domains. It explores the fundamental concepts of data science and optimization, providing a strong foundation for readers to build upon, and will be a welcomed resource for AI researchers, data scientists, engineers, and developers on key topics such as evolutionary optimization techniques, reinforcement learning, Natural Language Processing, Bayesian optimization, advanced analytics for large-scale data, fuzzy logic, quantum computing, graph theory, convex optimization, differential evolution, and more.

Advanced Intelligence Methods for Data Science and Optimization

The Times Puzzle Books

300 Compelling and Addictive Codewords

The Times Bumper Book of Codewords Book 2

Cognitive Approaches in Cloud and Edge Computing.

Foundations, Challenges and Opportunities

Deep Learning Models towards Health Informatics Management

Cybersecurity Implications in Blockchain Architecture

Written by authors, who are recognized experts in their respective fields, this accessible manual is a timely resource for educators. Each chapter is filled with practical examples and teacher tips, stimulating discussion points, and ready-to-use lesson plans tailored for students in fifth and sixth grades.

A Cyber Safety Training Program Built for Teachers and Designed for Children (Book 4)

From Street-smart to Web-wise®

Lecture Notes Series on Computing

The domination problem in graph theory is to find a minimum sized vertex subset in a graph such that every vertex not in this set is adjacent to at least one vertex in this set. The domination problem and its variations serve as good models for many real problems including location problems in operations research.This comprehensive volume introduces domination and its variations in graphs from an algorithmic point of view. It examines the structures of various graph classes, including trees, chordal graphs, strongly chordal graphs, interval graphs, comparability graphs, permutation graphs, distance-hereditary graphs and generalizations of these graphs. These structure properties provide concepts for designing the algorithms.This useful reference text benefits researchers, academics, and graduate students in theoretical computer science, combinatorics, and operations research.

Algorithmic Aspects Of Domination In Graphs

A complete and up-to-date overview of popular and practical erasure codes in distributed storage In Distributed Storage in Practice, a team of distinguished researchers delivers a comprehensive discussion on distributed storage coding and distributed storage systems. Divided into two parts, the book first explores distributed storage coding technology based on Maximum Distance Separable (MDS) codes, including array codes, Reed-Solomon codes, locally repairable codes, and regenerating codes. It then goes on to examine the challenges presented by repairing distributed data in real-world scenarios. Distributed Storage in Practice uses two perspectives: practical optimization of distributed storage coding and emerging technologies such as blockchain. It discusses the technical foundations of blockchain and integrates blockchain into distributed storage systems. It also offers an overview of several popular blockchain-based storage systems. It also includes: <ul> <li>A thorough introduction to the current development of quantum technology, including its fundamentals, quantum memory, quantum computers, quantum security, and quantum networks</li> <li>Comprehensive explorations of data recovery methods for specific networked distributed storage scenarios</li> <li>Practical integrations of theory and practice, including classic techniques and the most recent advancements in storage coding</li> <li>A practical example of a distributed secure storage system integrated with blockchain technology</li> </ul> Perfect for researchers and undergraduate and graduate students studying computer science, Distributed Storage in Practice will also benefit blockchain professionals.

Distributed Storage in Practice

This book is a comprehensive introduction to applied cryptography and cybersecurity, covering both the critical theoretical foundations and the practical aspects, including labs. It does not require prior knowledge in mathematics, cryptography or theory of computer science. The topics covered include shared and public key cryptosystems, authentication schemes and protocols, integrity (hashing, Merkle trees/accumulators and blockchains), signatures and key exchange, resiliency to corruptions, the Transport Layer Security (TLS) and Secure Sockets Layer (SSL) protocols, public key infrastructure (PKI), including certificate transparency (CT), human-centered security and cryptography, and (post)quantum cryptography.This text is a useful reference for self-study or as a course textbook.

Applied Introduction To Cryptography And Cybersecurity

Integration of Federated Learning and Blockchain for Smart Cities

Cryptography for Everyone

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