This handbook covers basic concepts of Information and mathematical theory that deals with the fundamental aspects of communication systems. The purpose of this Hand-Book is to develop the foundation ideas of information theory and to indicate where and how the theory can be applied in a real-time scenario and applications. The Handbook is categorized into two parts (PART - I & PART - II) The objectivesof this Handbook is to Explain the concepts of information source and entropy, Demonstrate the working of various Encoding Techniques, Discuss various source encoding algorithms, Illustrate the use of Cyclic and convolution codes. The readers reliability from this Handbook is to Build the basic concepts of information source and measure of information, Apply different Encoding Schemes for given applications, Develop the different Source Encoding Algorithm for given applications.

This book proposes new technologies and discusses future solutions for ICT design infrastructures, as reflected in high-quality papers presented at the 8th International Conference on ICT for Sustainable Development (ICT4SD 2023), held in Goa, India, on August 3–4, 2023. The book covers the topics such as big data and data mining, data fusion, IoT programming toolkits and frameworks, green communication systems and network, use of ICT in smart cities, sensor networks and embedded system, network and information security, wireless and optical networks, security, trust, and privacy, routing and control protocols, cognitive radio and networks, and natural language processing. Bringing together experts from different countries, the book explores a range of central issues from an international perspective.

Managing Unstructured Data: NoSQL Database Essentials-is a reference book and guide for teaching and reading skills to college faculty and students. In Chapter1 the fundamentals of database and relational data base are discussed. This chapter helps students to understand data management concepts by data modelling, schema design, data storage and retrieval. This chapter includes the foundational skills that are applicable across various industries and provides a stepping stone for further specialization and career development. The chapter 2 is all about unstructured data. Varying methods for managing, analysing, and storing data are needed for varying levels of organization and complexity, which are represented by structured, unstructured, and semi-structured data. This chapter provides a platform for students to understand the transition from structured to unstructured data in terms of data management and analysis and it is a pivotal aspect of modern data management. In chapter 3 concepts of NoSQL data base and the major differences with SQL & Relational data bases are highlighted. This chapter explains the adoptions of NoSQL with flexible schema, scalability, high performance and support for distributed architecture. Chapter 4 is all about NoSQL databases, or "Not Only SQL" databases which represent a diverse set of database technologies designed to address specific challenges not well served by traditional relational databases. A brief overview of the main types of NoSQL databases are discussed here. The four basic data models such as key-value pairs, document-oriented, columnar, and graph-based structures are represented in this chapter. Information on popular NoSQL database technologies is given in chapter 5. Details of technologies like Apache HBase, Apache CouchDB, Neo4j, Apache Cassandra and their comparison are also provided here. It includes the distributed architecture with fault tolerance, high availability, and disaster recovery capabilities for ensuring data integrity and business continuity. Chapter 6 discusses the overview of Mongo DB which is a document-oriented NoSQL database known for its flexibility, scalability, and ease of use. The features of Mongo DB including document store, MongoDB protocol, horizontal scalability, cross platform compatibility, replication and sharding are also covered here. Chapter 7 deals with Concurrency control in databases. It discusses about the methods to obtain concurrency in structured data, and then in unstructured data, challenges in concurrency control for unstructured data, commits in transaction and the different isolation levels. Chapter 8 discusses on how unstructured data are used in big data processing. It includes Query processing performance evaluation in big data systems, the types od dirty data. Data cleansing is explained in detail with the steps in cleansing, exploratory data analysis, and data visualization. Hope this book on Managing Unstructured Data: NoSQL Database Essentials will provide a handy and useful reference book for teachers and students on Unstructured Database.

THE AUTHOR(S) AND PUBLISHER OF THIS BOOK HAVE USED THEIR BEST EFFORTS IN PREPARING THIS BOOK. THESE EFFORTS INCLUDE THE DEVELOPMENT, RESEARCH ANDTESTING OF THE THEORIES AND PROGRAMS TO DETERMINE THEIR EFFECTIVENESS. THE AUTHORS AND PUBLISHER MAKES NO WARRANTY OF ANY KIND, EXPRESSED OR IMPLIEDWITH REGARD TO THESE PROGRAMS OR THE DOCUMENTATION CONTAINED IN THIS BOOK. THE AUTHORS AND PUBLISHER SHALL NOT BE LIABLE IN ANY EVENT FORINCIDENTAL OR CONSEQUENTIAL DAMAGES IN CONNECTION WITH, OR ARISING OUT OF, THE FURNISHING, PERFORMANCE, OR USE OF THESE PROGRAMS. COPYRIGHTS © 2023 BY MILESTONE RESEARCH PUBLICATIONS, INC. THIS EDITION IS PUBLISHED BY ARRANGEMENT WITH MILESTONE RESEARCH FOUNDATION, INC. THIS BOOK IS SOLD SUBJECT TO THE CONDITION THAT IT SHALL NOT, BY WAY OF TRADE OR OTHERWISE, BE LENT, RESOLD, HIRED OUT, OR OTHERWISE CIRCULATED WITHOUTTHE PUBLISHER'S PRIOR WRITTEN CONSENT IN ANY FORM OF BINDING OR COVER OTHER THAN THAT IN WHICH IT IS PUBLISHED AND WITHOUT A SIMILAR CONDITIONINCLUDING THIS CONDITION BEING IMPOSED ON THE SUBSEQUENT PURCHASER AND WITHOUT LIMITING THE RIGHTS UNDER COPYRIGHT RESERVED ABOVE, NO PART OF THISPUBLICATION MAY BE REPRODUCED, STORED IN OR INTRODUCED INTO RETRIEVAL SYSTEM, OR TRANSMITTED IN ANY FORM OR BY ANY MEANS (ELECTRONIC, MECHANICAL,PHOTOCOPYING, RECORDING AND OTHERWISE) WITHOUT THE PRIOR WRITTEN PERMISSION OF BOTH THE COPYRIGHT OWNER AND THE ABOVE MENTIONED PUBLISHER OFTHIS BOOK.

Database management courses introduce students to languages, applications and programming used for the design and maintenance of business databases. One of the basic skills covered in database management courses is the use of Structured Query Language (SQL), the most common database manipulation language. Students learn to write programs with packages, debugging procedures, triggers and database structures using SQL. Database management courses may also cover Visual Basic programming language skills for program design. Other database management skills include the use of data and object modeling, relational algebra, relational data models and applications programming. The physical characteristics of databases, reliability and system performance are additional topics in database management. In database concepts classes, the emphasis is on normalization, data dictionaries and data integrity. Students' skill set upon course completion should include designing and implementing normalized databases using database reports and creating forms and tables. Students completing database applications classes will have the skills necessary to create multiple table systems with screens, updates and reports.

This book is an introductory textbook on Analog Electronics and circuits for undergraduate, Post graduate and beginner students. It aims at exploring the basic electronic devices such as clippers, clampers, oscillators, and Operational Amplifiers. It also explores the applications of clipper circuits in relevant places to inculcate interest among readers. It is probably no longer possible to cover everything in a single semester. Because of this, we have structured the book so that readers can find easy to understand the basic electronic circuits.

Real-time systems are computer systems that are designed to respond to external events within a specified time constraint. These systems are used in a variety of applications, including control systems, communication systems, multimedia systems, and embedded systems. Real-time systems must be able to respond to events in a timely and deterministic manner, meaning that the response time must be guaranteed and consistent. One of the main challenges in designing real-time systems is ensuring that they are predictable and reliable. Real-time systems must be able to handle a wide range of input conditions, from normal operation to extreme conditions, without crashing or failing to meet their deadlines. This requires careful design and implementation, as well as testing and verification to ensure that the system behaves as intended. Real-time systems often have unique requirements that differ from those of traditional computer systems. For example, real-time systems may need to operate in harsh environments, such as extreme temperatures or high radiation levels. They may also need to communicate with other systems in real-time, which requires low-latency communication protocols and high bandwidth. In addition to these technical challenges, there are also legal and ethical considerations when designing real-time systems. For example, systems used in safety-critical applications, such as medical devices or transportation systems, must meet strict regulatory requirements and undergo rigorous testing and certification processes. Overall, the design and implementation of real-time systems is a complex and challenging task that requires a deep understanding of the system's requirements, its environment, and the technologies available. In this textbook, we will explore the key concepts, principles, and techniques used in the design and analysis of real-time systems. We will cover topics such as scheduling, synchronization, communication, fault-tolerance, and performance analysis, and provide examples and case studies to illustrate these concepts. By the end of this book, readers will have a solid understanding of real-time systems and the skills needed to design and implement them effectively.

Reinforcement learning (RL) is a subfield of machine learning that deals with how an agent should learn to take actions in an environment to maximize some notion of cumulative reward. In other words, reinforcement learning is a learning paradigm where an agent learns to interact with an environment by taking actions and observing the feedback it receives in the form of rewards or penalties. It is a feedback-based Machine learning technique in which an agent learns to behave in an environment by performing the actions and seeing the results of actions. For each good action, the agent gets positive feedback, and for each bad action, the agent gets negative feedback or penalty.

The fourth volume of Rudolf Ahlswede’s lectures on Information Theory is focused on Combinatorics. Ahlswede was originally motivated to study combinatorial aspects of Information Theory via zero-error codes: in this case the structure of the coding problems usually drastically changes from probabilistic to combinatorial. The best example is Shannon’s zero error capacity, where independent sets in graphs have to be examined. The extension to multiple access channels leads to the Zarankiewicz problem. A code can be regarded combinatorially as a hypergraph; and many coding theorems can be obtained by appropriate colourings or coverings of the underlying hypergraphs. Several such colouring and covering techniques and their applications are introduced in this book. Furthermore, codes produced by permutations and one of Ahlswede’s favourite research fields -- extremal problems in Combinatorics -- are presented. Whereas the first part of the book concentrates on combinatorial methods in order to analyse classical codes as prefix codes or codes in the Hamming metric, the second is devoted to combinatorial models in Information Theory. Here the code concept already relies on a rather combinatorial structure, as in several concrete models of multiple access channels or more refined distortions. An analytical tool coming into play, especially during the analysis of perfect codes, is the use of orthogonal polynomials. Classical information processing concerns the main tasks of gaining knowledge and the storage, transmission and hiding of data. The first task is the prime goal of Statistics. For transmission and hiding data, Shannon developed an impressive mathematical theory called Information Theory, which he based on probabilistic models. The theory largely involves the concept of codes with small error probabilities in spite of noise in the transmission, which is modeled by channels. The lectures presented in this work are suitable for graduate students in Mathematics, and also for those working in Theoretical Computer Science, Physics, and Electrical Engineering with a background in basic Mathematics. The lectures can be used as the basis for courses or to supplement courses in many ways. Ph.D. students will also find research problems, often with conjectures, that offer potential subjects for a thesis. More advanced researchers may find questions which form the basis of entire research programs.

Aimed at graduate students and researchers interested in information theory and the analysis of algorithms, this book explores problems of information and learning theory, demonstrating how to use tools from analytic combinatorics to discover and analyze precise behavior of source codes.