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Traditional products are becoming smart products, and smart products are becoming connected. From smart homes to smart cities to smart farms, this trend in product design and development is likely to accelerate and will have a profound impact on the future.This accessible textbook/reference focuses on using the Internet of Things (IoT) to foster sustainability. It guides readers in a step-by-step manner through the creation of example applications designed to promote a clean and healthy environment. Additionally, the book serves as a lesson in systems design, taking the view that the IoT is best understood as an extension of the World Wide Web. Therefore, the exposition examines how the Web was designed and how its principles can be applied to IoT design.The book engages readers with modern IoT technologies, standards, and platforms. It connects sensors and actuators to the cloud, but in a way that is based on sound architectural principles.

Concise Guide to the Internet of Things : A Hands-On Introduction to Technologies Procedures and Architectures

This textbook provides a balanced coverage on software design, including design principles, methodologies, and techniques in contexts of designing modules of small and larger sizes with a multi-paradigm viewpoint emphasizing design trade-off. Commonly used design diagrams and patterns are also covered in terms of the design ideas behind and their effective use. The book also explores what (software) design thinking is, the role it plays in a design process, and ways to promote it. Despite object orientation being still the center of attention, there is a strong promotion throughout the book that software design should consider all appropriate design paradigms and methodologies.The book is organized in 10 chapters. Chapter 1 is dedicated to an exploration of what software design may be and entail. Next, chapters 2 and 3 are designed to help readers better understand object orientation, and the essentials of object-oriented design. Chapter 4 is then dedicated to the design of methods,while chapters 5, 6, and 8 respectively include topics about the design of objects, modeling with the Unified Modeling Language, and the use of design patterns. Larger software elements are often directly responsible for the formation of software architecture, thus chapter 7 covers four kinds of larger software elements: libraries, components, frameworks, and microservices, and their architectural implications. Chapter 9 finally brings the presentation of software design to an end with a coverage on software architecture focusing on software architectural views. Case studies are important in learning how to design software, hence chapter 10 then gathers some small design case studies that can be used in earlier chapters as appropriate. These case studies can be extended in different ways to provide additional design opportunities.This textbook book is intended for a junior level undergraduate course on software design, yet the depth of the book makes it also appropriate for a design course at beginning graduate level. Professionals may also find the book useful in their professional development.

An Introduction to Software Design : Concepts Principles Methodologies and Techniques

This textbook comprehensively covers both fundamental and advanced topics related to data science. Data science is an umbrella term that encompasses data analytics, data mining, machine learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to data science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in data science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, deep learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main data science programming languages, and shows in a completely new chapter practical data science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different machine learning and data mining tasks. An appendix explaining the basic mathematical concepts of data science completes the book.This textbook is suitable for advanced undergraduate and graduate students as well as for industrial practitioners who carry out research in data science. They both will not only benefit from the comprehensive presentation of important topics, but also from the many application examples and the comprehensive list of further readings, which point to additional publications providing more in-depth research results or provide sources for a more detailed description of related topics.&nbsp;

Data Science Concepts and Techniques with Applications : 2nd Edition

This book provides a comprehensive introduction to the foundations and frontiers of graph neural networks. In addition, the book introduces the basic concepts and definitions in graph representation learning and discusses the development of advanced graph representation learning methods with a focus on graph neural networks. The book providers researchers and practitioners with an understanding of the fundamental issues as well as a launch point for discussing the latest trends in the science. The authors emphasize several frontier aspects of graph neural networks and utilize graph data to describe pairwise relations for real-world data from many different domains, including social science, chemistry, and biology. Several frontiers of graph neural networks are introduced, which enable readers to acquire the needed techniques of advances in graph neural networks via theoretical models and real-world applications.

Advances in Graph Neural Networks

This textbook is about working in teams to create functioning software. It covers skills in agile software development methods, team working, version control and continuous integration and shows readers how to apply some of the latest ideas from lean, agile and Kanban.Part I, which focuses on&nbsp;People, describes various project roles and the skills needed to perform each role. This includes members of self-organizing teams, scrum masters, product owners and activities for managing other stakeholders. The skills needed to create&nbsp;Product&nbsp;artefacts are detailed in Part II. These include skills to create agile requirements, architectures, designs as well as development and security artefacts. The agile development&nbsp;Process&nbsp;to coordinate with co-workers is described in Part III. It introduces the skills needed to facilitate an incremental process and to use software tools for version control and automated testing. Eventually some more advanced topics are explained in Part IV. These topics include large projects comprising multiple cooperating teams, automating deployment, cloud software services, DevOps and evolving live systems.This textbook addresses significant competencies in the IEEE/ACM Computing Curricula Task Force 2020. It includes nearly 100 exercises for trying out and applying the skills needed for agile software development. Hints, tips and further advice about tackling the exercises are presented at the end of each chapter, and a case study project, with downloadable source code from an online repository, integrates the skills learned across the chapters. In addition, further example software projects are also available there. This way, the book provides a hands-on guide to working on a development project as part of a team, and is inspired by the needs of early career practitioners as well as undergraduate software engineering and computer science students.

Agile Software Engineering Skills

This book presents a guide for research methodology and scientific writing covering various elements such as finding research problems, writing research proposals, obtaining funds for research, selecting research designs, searching the literature and review, collection of data and analysis, preparation of thesis, writing research papers for journals, citation and listing of references, preparation of visual materials, oral and poster presentation in conferences, and ethical issues in research . Besides introducing library and its various features in a lucid style, the latest on the use of information technology in retrieving and managing information through various means are also discussed in this book. The book is useful for students, young researchers, and professionals.

Research Methodology and Scientific Writing : 2nd Edition

This self-contained introduction to modern cryptography emphasizes the mathematics behind the theory of public key cryptosystems and digital signature schemes. The book focuses on these key topics while developing the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Only basic linear algebra is required of the reader; techniques from algebra, number theory, and probability are introduced and developed as required. This text provides an ideal introduction for mathematics and computer science students to the mathematical foundations of modern cryptography. The book includes an extensive bibliography and index; supplementary materials are available online.The book covers a variety of topics that are considered central to mathematical cryptography. Key topics include: <ul><li>classical cryptographic constructions, such as Diffie–Hellmann key exchange, discrete logarithm-based cryptosystems, the RSA cryptosystem, anddigital signatures;</li><li> </li><li>fundamental mathematical tools for cryptography, including primality testing, factorization algorithms, probability theory, information theory, and collision algorithms;</li><li> </li><li>an in-depth treatment of important cryptographic innovations, such as elliptic curves, elliptic curve and pairing-based cryptography, lattices, lattice-based cryptography, and the NTRU cryptosystem.</li><li> </li></ul>The second edition of&nbsp;An Introduction to Mathematical Cryptography includes a significant revision of the material on digital signatures, including an earlier introduction to RSA, Elgamal, and DSA signatures, and new material on lattice-based signatures and rejection sampling. Many sections have been rewritten or expanded for clarity, especially in the chapters on information theory, elliptic curves, and lattices, and the chapter of additional topics has been expanded to include sections on digital cash and homomorphic encryption.&nbsp;Numerous new exercises have been included.

An Introduction to Mathematical Cryptography : 2nd Edition

This book addresses the fundamental technologies, architectures, application domains, and future research directions of the Internet of Things (IoT). It also discusses how to create your own IoT system according to applications requirements, and it presents a broader view of recent trends in the IoT domain and open research issues. This book encompasses various research areas such as wireless networking, advanced signal processing, IoT, and ubiquitous computing.&nbsp;Internet of Things: Theory to Practice&nbsp;discusses the basics and fundamentals of IoT and real-time applications, as well as the associated challenges and open research issues. The book includes several case studies about the use of IoT in day-to-day life. The authors review various advanced computing technologies?such as cloud computing, fog computing, edge computing, and Big Data analytics?that will play crucial roles in future IoT-based services. The book provides a detailed role of blockchain technology, Narrowband IoT (NB-IoT), wireless body area network (WBAN), LoRa (a longrange low power platform), and Industrial IoT (IIoT) in the 5G world. This book is intended for university/college students, as well as amateur electronic hobbyists and industry professionals who are looking to stay current in the IoT domain.

Internet of Things : Theory to Practice

The book emphasizes on building fundamentals of IoT networks by leveraging important and relevant concepts from Signal Processing, Communications, Networks and Machine learning. It focuses on IoT protocols, energy harvesting, control optimization, clustering, data fusion, data analytics, localization, fog computing, etc.

Fundamentals of Internet of Things

Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data is a challenge. Data Mining is the process of discovering patterns and knowledge from large data sets, and&nbsp;Data Mining with Python&nbsp;focuses on the hands-on approach to learning Data Mining. It showcases how to use Python Packages to fulfill the Data Mining pipeline, which is to collect, integrate, manipulate, clean, process, organize, and analyze data for knowledge.The contents are organized based on the Data Mining pipeline, so readers can naturally progress step by step through the process. Topics, methods, and tools are explained in three aspects: “What it is” as a theoretical background, “why we need it” as an application orientation, and “how we do it” as a case study.This book is designed to give students, data scientists, and business analysts an understanding of Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modified, and used for a more comprehensive learning experience, this book will help its readers to gain practical skills to implement Data Mining techniques in their work.

Data Mining with Python : Theory Application and Case Studies

Unlike the first edition, the new edition has been split into two books.Thoroughly revised and updated, this is the first book of the second edition of Introduction to Data Science: Data Wrangling and Visualization with R. It introduces skills that can help you tackle real-world data analysis challenges. These include R programming, data wrangling with dplyr, data visualization with ggplot2, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation with Quarto and knitr. The new edition includes additional material/chapters on data.table, locales, and accessing data through APIs. The book is divided into four parts: R, Data Visualization, Data Wrangling, and Productivity Tools. Each part has several chapters meant to be presented as one lecture and includes dozens of exercises. The second book will cover topics including probability, statistics and prediction algorithms with R.Throughout the book, we use motivating case studies. In each case study, we try to realistically mimic a data scientist’s experience. For each of the skills covered, we start by asking specific questions and answer these through data analysis. Examples of the case studies included in the book are: US murder rates by state, self-reported student heights, trends in world health and economics, and the impact of vaccines on infectious disease rates.This book is meant to be a textbook for a first course in Data Science. No previous knowledge of R is necessary, although some experience with programming may be helpful. To be a successful data analyst implementing these skills covered in this book requires understanding advanced statistical concepts, such as those covered the second book. If you read and understand all the chapters and complete all the exercises in this book, and understand statistical concepts, you will be well-positioned to perform basic data analysis tasks and you will be prepared to learn the more advanced concepts and skills needed to become an expert.

Introduction to Data Science : Data Wrangling and Visualization With R : 2nd Edition

Internet of things (IoT) is the connection and communication of physical objects (smart devices) over the internet. In this recent age, people’s daily lives are dependent on the internet through their smartphones, tablets, Smart TVs, micro-controllers, Smart Tags, computers, laptops, and cars to name a few. This book discusses different ways to create a better IoT network and/or IoT platforms to improve the efficiency and quality of these products and subsequently their users' lives. In addition, this book provides future research directions in energy, industry, and healthcare, and explores the different applications of IoT and its associated technologies. It provides an overview and explanation of the software architecture, middleware, data processing and data management as well as security, sensors, actuators and algorithms used to create a working IoT platform. The editors then go on to examine IoT networks and platforms as they relate to energy industry including, energy efficiency and management, intelligent energy management, smart energy through blockchain and energy-efficient/aware routing/scheduling challenges and issues. They then explore IoT as it applies to healthcare including biomedical image and signal analysis and disease prediction and diagnosis. Finally the editors examine the prospects and applications of IoT for industry through the concepts of smart industry, including architecture, blockchain, and Industry 4.0. This book is intended for senior undergraduate and graduate students, researchers and industry professionals working on IoT applications and infrastructure.

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Computer Science

Concise Guide to the Internet of Things : A Hands-On Introduction to Technologies Procedures and Architectures

An Introduction to Software Design : Concepts Principles Methodologies and Techniques

Data Science Concepts and Techniques with Applications : 2nd Edition

Advances in Graph Neural Networks

Agile Software Engineering Skills

Research Methodology and Scientific Writing : 2nd Edition

An Introduction to Mathematical Cryptography : 2nd Edition

Internet of Things : Theory to Practice

Fundamentals of Internet of Things

Data Mining with Python : Theory Application and Case Studies

Introduction to Data Science : Data Wrangling and Visualization With R : 2nd Edition

Internet of Things : Energy Industry and Healthcare