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Modeling Software with Finite State Machines A Practical Approach

Modeling Software with Finite State Machines A Practical Approach

Modeling Software with Finite State Machines: A Practical Approach explains how to apply finite state machines to software development. It provides a critical analysis of using finite state machines as a foundation for executable specifications to reduce software development effort and improve quality. This book discusses the design of a state machine and of a system of state machines. It also presents a detailed analysis of development issues relating to behavior modeling with design examples and design rules for using finite state machines. This volume describes a coherent and well-tested framework for generating reliable software for even the most complex tasks. The authors demonstrate that the established practice of using a specification as a basis for coding is wrong. Divided into three parts this book opens by delivering the authors' expert opinions on software covering the evolution of development as well as costs methods programmers and the development cycle. The remaining two parts encourage the use of state machines: promoting the virtual finite state machine (Vfsm) method and the StateWORKS development tools. | Modeling Software with Finite State Machines A Practical Approach

GBP 56.99
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Intelligent Data Analytics IoT and Blockchain

Intelligent Data Analytics IoT and Blockchain

This book focuses on data analytics with machine learning using IoT and blockchain technology. Integrating these three fields by examining their interconnections Intelligent Data Analytics IoT and Blockchain examines the opportunities and challenges of developing systems and applications exploiting these technologies. Written primarily for researchers who are working in this multi-disciplinary field the book also benefits industry experts and technology executives who want to develop their organizations’ decision-making capabilities. Highlights of the book include: Using image processing with machine learning techniques A deep learning approach for facial recognition A scalable system architecture for smart cities based on cognitive IoT Source authentication of videos shared on social media Survey of blockchain in healthcare Accident prediction by vehicle tracking Big data analytics in disaster management Applicability limitations and opportunities of blockchain technology The book presents novel ideas and insights on different aspects of data analytics blockchain technology and IoT. It views these technologies as interdisciplinary fields concerning processes and systems that extract knowledge and insights from data. Focusing on recent advances the book offers a variety of solutions to real-life challenges with an emphasis on security.

GBP 150.00
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Software Engineering with UML

Software Engineering with UML

This book presents the analysis design documentation and quality of software solutions based on the OMG UML v2. 5. Notably it covers 14 different modelling constructs including use case diagrams activity diagrams business-level class diagrams corresponding interaction diagrams and state machine diagrams. It presents the use of UML in creating a Model of the Problem Space (MOPS) Model of the Solution Space (MOSS) and Model of the Architectural Space (MOAS). The book touches important areas of contemporary software engineering ranging from how a software engineer needs to invariably work in an Agile development environment through to the techniques to model a Cloud-based solution. | Software Engineering with UML

GBP 42.99
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Securing IoT in Industry 4.0 Applications with Blockchain

Securing IoT in Industry 4.0 Applications with Blockchain

The Industry 4. 0 revolution is changing the world around us. Artificial intelligence and machine learning automation and robotics big data Internet of Things augmented reality virtual reality and creativity are the tools of Industry 4. 0. Improved collaboration is seen between smart systems and humans which merges humans' critical and cognitive thinking abilities with highly accurate and fast industrial automation. Securing IoT in Industry 4. 0 Applications with Blockchain examines the role of IoT in Industry 4. 0 and how it can be made secure through various technologies including blockchain. The book begins with an in-depth look at IoT and discusses applications architecture technologies tools and programming languages. It then examines blockchain and cybersecurity as well as how blockchain achieves cybersecurity. It also looks at cybercrimes and their preventive measures and issues related to IoT security and trust. Features An overview of how IoT is used to improve the performance of Industry 4. 0 systems The evolution of the Industrial Internet of Things (IIoT) its proliferation and market share and some examples across major industries An exploration of how smart farming is helping farmers prevent plant disease The concepts behind the Internet of Nano Things (IoNT) including the nanomachine and nanonetwork architecture and nano-communication paradigms A look at how blockchains can enhance cybersecurity in a variety of applications including smart contracts transferring financial instruments and Public Key Infrastructure An overview of the structure and working of a blockchain including the types evolution benefits and applications of blockchain to industries A framework of technologies designed to shield networks computers and data from malware vulnerabilities and unauthorized activities An explanation of the automation system employed in industries along with its classification functionality flexibility limitations and applications

GBP 115.00
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Practical AI for Cybersecurity

Practical AI for Cybersecurity

The world of cybersecurity and the landscape that it possesses is changing on a dynamic basis. It seems like that hardly one threat vector is launched new variants of it are already on the way. IT Security teams in businesses and corporations are struggling daily to fight off any cyberthreats that they are experiencing. On top of this they are also asked by their CIO or CISO to model what future Cyberattacks could potentially look like and ways as to how the lines of defenses can be further enhanced. IT Security teams are overburdened and are struggling to find ways in order to keep up with what they are being asked to do. Trying to model the cyberthreat landscape is a very laborious process because it takes a lot of time to analyze datasets from many intelligence feeds. What can be done to accomplish this Herculean task? The answer lies in Artificial Intelligence (AI). With AI an IT Security team can model what the future Cyberthreat landscape could potentially look like in just a matter of minutes. As a result this gives valuable time for them not only to fight off the threats that they are facing but to also come up with solutions for the variants that will come out later. Practical AI for Cybersecurity explores the ways and methods as to how AI can be used in cybersecurity with an emphasis upon its subcomponents of machine learning computer vision and neural networks. The book shows how AI can be used to help automate the routine and ordinary tasks that are encountered by both penetration testing and threat hunting teams. The result is that security professionals can spend more time finding and discovering unknown vulnerabilities and weaknesses that their systems are facing as well as be able to come up with solid recommendations as to how the systems can be patched up quickly.

GBP 44.99
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Applied Edge AI Concepts Platforms and Industry Use Cases

Applied Edge AI Concepts Platforms and Industry Use Cases

The strategically sound combination of edge computing and artificial intelligence (AI) results in a series of distinct innovations and disruptions enabling worldwide enterprises to visualize and realize next-generation software products solutions and services. Businesses individuals and innovators are all set to embrace and experience the sophisticated capabilities of Edge AI. With the faster maturity and stability of Edge AI technologies and tools the world is destined to have a dazzling array of edge-native people-centric event-driven real-time service-oriented process-aware and insights-filled services. Further on business workloads and IT services will become competent and cognitive with state-of-the-art Edge AI infrastructure modules AI algorithms and models enabling frameworks integrated platforms accelerators high-performance processors etc. The Edge AI paradigm will help enterprises evolve into real-time and intelligent digital organizations. Applied Edge AI: Concepts Platforms and Industry Use Cases focuses on the technologies processes systems and applications that are driving this evolution. It examines the implementation technologies; the products processes platforms patterns and practices; and use cases. AI-enabled chips are exclusively used in edge devices to accelerate intelligent processing at the edge. This book examines AI toolkits and platforms for facilitating edge intelligence. It also covers chips algorithms and tools to implement Edge AI as well as use cases. FEATURES The opportunities and benefits of intelligent edge computing Edge architecture and infrastructure AI-enhanced analytics in an edge environment Encryption for securing information An Edge AI system programmed with Tiny Machine learning algorithms for decision making An improved edge paradigm for addressing the big data movement in IoT implementations by integrating AI and caching to the edge Ambient intelligence in healthcare services and in development of consumer electronic systems Smart manufacturing of unmanned aerial vehicles (UAVs) AI edge computing and blockchain in systems for environmental protection Case studies presenting the potential of leveraging AI in 5G wireless communication | Applied Edge AI Concepts Platforms and Industry Use Cases

GBP 99.99
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Making Data Work Enabling Digital Transformation Empowering People and Advancing Organisational Success

Making Data Work Enabling Digital Transformation Empowering People and Advancing Organisational Success

In this book Edosa explores common challenges which limit the value that organisations can get from data. What makes his book unique is that he also tackles one of the unspoken barriers to data adoption—fear. Fear of the unknown fear of the intangible fear of the investment needed and yes fear of losing your job to a machine. With his talent for distilling clarity from complexity Edosa tackles this and many other challenges. —Tim Carmichael Chief Data Officer Chalhoub Group This book offers fresh insight about how to solve the interactional frictions that hamper the flow of data information and knowledge across organisations. Yet rather than being stuck with endless polarising debates such as breaking down silos it shifts focus back towards the ultimate to what end. —Jacky Wright Chief Digital Officer (CDO) Microsoft US If you care about AI transformation empowering people or advancing organisational success in an increasingly digital world then you should read this book. —Yomi Ibosiola Chief Data and Analytics Officer Union Bank A retail giant already struggling due to the Covid-19 pandemic was faced with a disastrous situation when—at the end of a critical investment in an artificial intelligence project that had been meant to save money—it suddenly discovered that its implementation was likely to leave it worse off. An entire critical service stream within an insurer’s production system crashed. This critical failure resulted in the detentions of fully insured motorists for allegedly not carrying required insurance. Making Data Work details these two scenarios as well as others illustrating the consequences that arise when organizations do not know how to make data work properly. It is a journey to determine what to do to make data work for ourselves and for our organisations. It is a journey to discover how to bring it all together so organisations can enable digital transformation empower people and advance organisational success. It is the journey to a world where data and technology finally live up to the hype and deliver better human outcomes where artificial intelligence can move us from reacting to situations to predicting future occurrences and enabling desirable possibilities. | Making Data Work Enabling Digital Transformation Empowering People and Advancing Organisational Success

GBP 44.99
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Ethics of Data and Analytics Concepts and Cases

Ethics of Data and Analytics Concepts and Cases

The ethics of data and analytics in many ways is no different than any endeavor to find the right answer. When a business chooses a supplier funds a new product or hires an employee managers are making decisions with moral implications. The decisions in business like all decisions have a moral component in that people can benefit or be harmed rules are followed or broken people are treated fairly or not and rights are enabled or diminished. However data analytics introduces wrinkles or moral hurdles in how to think about ethics. Questions of accountability privacy surveillance bias and power stretch standard tools to examine whether a decision is good ethical or just. Dealing with these questions requires different frameworks to understand what is wrong and what could be better. Ethics of Data and Analytics: Concepts and Cases does not search for a new different answer or to ban all technology in favor of human decision-making. The text takes a more skeptical ironic approach to current answers and concepts while identifying and having solidarity with others. Applying this to the endeavor to understand the ethics of data and analytics the text emphasizes finding multiple ethical approaches as ways to engage with current problems to find better solutions rather than prioritizing one set of concepts or theories. The book works through cases to understand those marginalized by data analytics programs as well as those empowered by them. Three themes run throughout the book. First data analytics programs are value-laden in that technologies create moral consequences reinforce or undercut ethical principles and enable or diminish rights and dignity. This places an additional focus on the role of developers in their incorporation of values in the design of data analytics programs. Second design is critical. In the majority of the cases examined the purpose is to improve the design and development of data analytics programs. Third data analytics artificial intelligence and machine learning are about power. The discussion of power—who has it who gets to keep it and who is marginalized—weaves throughout the chapters theories and cases. In discussing ethical frameworks the text focuses on critical theories that question power structures and default assumptions and seek to emancipate the marginalized. | Ethics of Data and Analytics Concepts and Cases

GBP 56.99
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