Since databases are the primary repositories of information for today's organizations and governments, database security has become critically important. Introducing the concept of multilevel security in relational databases, this book provides a comparative study of the various models that support multilevel security policies in the relational database-illustrating the strengths and weaknesses of each model. Multilevel Security for Relational Databases covers multilevel database security concepts along with many other multilevel database security models and techniques. It presents a prototype that readers can implement as a tool for conducting performance evaluations to compare multilevel secure database models. The book supplies a complete view of an encryption-based multilevel security database model that integrates multilevel security for the relational database with a system that encrypts each record with an encryption key according to its security class level. This model will help you utilize an encryption system as a second security layer over the multilevel security layer for the database, reduce the multilevel database size, and improve the response time of data retrieval from the multilevel database. Considering instance-based multilevel database security, the book covers relational database access controls and examines concurrency control in multilevel database security systems. It includes database encryption algorithms, simulation programs, and Visual studio and Microsoft SQL Server code.

This book describes a cross-domain architecture and design tools for networked complex systems where application subsystems of different criticality coexist and interact on networked multi-core chips. The architecture leverages multi-core platforms for a hierarchical system perspective of mixed-criticality applications. This system perspective is realized by virtualization to establish security, safety and real-time performance. The impact further includes a reduction of time-to-market, decreased development, deployment and maintenance cost, and the exploitation of the economies of scale through cross-domain components and tools. Describes an end-to-end architecture for hypervisor-level, chip-level, and cluster level. Offers a solution for different types of resources including processors, on-chip communication, off-chip communication, and I/O. Provides a cross-domain approach with examples for wind-power, health-care, and avionics. Introduces hierarchical adaptation strategies for mixed-criticality systems Provides modular verification and certification methods for the seamless integration of mixed-criticality systems. Covers platform technologies, along with a methodology for the development process. Presents an experimental evaluation of technological results in cooperation with industrial partners. The information in this book will be extremely useful to industry leaders who design and manufacture products with distributed embedded systems in mixed-criticality use-cases. It will also benefit suppliers of embedded components or development tools used in this area. As an educational tool, this material can be used to teach students and working professionals in areas including embedded systems, computer networks, system architecture, dependability, real-time systems, and avionics, wind-power and health-care systems.

Building a data-driven organization (DDO) is an enterprise-wide initiative that may consume and lock up resources for the long term. Understandably, any organization considering such an initiative would insist on a roadmap and business case to be prepared and evaluated prior to approval. This book presents a step-by-step methodology in order to create a roadmap and business case, and provides a narration of the constraints and experiences of managers who have attempted the setting up of DDOs. The emphasis is on the big decisions - the key decisions that influence 90% of business outcomes - starting from decision first and reengineering the data to the decisions process-chain and data governance, so as to ensure the right data are available at the right time, every time. Investing in artificial intelligence and data-driven decision making are now being considered a survival necessity for organizations to stay competitive. While every enterprise aspires to become 100% data-driven and every Chief Information Officer (CIO) has a budget, Gartner estimates over 80% of all analytics projects fail to deliver intended value. Most CIOs think a data-driven organization is a distant dream, especially while they are still struggling to explain the value from analytics. They know a few isolated successes, or a one-time leveraging of big data for decision making does not make an organization data-driven. As of now, there is no precise definition for data-driven organization or what qualifies an organization to call itself data-driven. Given the hype in the market for big data, analytics and AI, every CIO has a budget for analytics, but very little clarity on where to begin or how to choose and prioritize the analytics projects. Most end up investing in a visualization platform like Tableau or QlikView, which in essence is an improved version of their BI dashboard that the organization had invested into not too long ago. The most important stakeholders, the decision-makers, are rarely kept in the loop while choosing analytics projects. This book provides a fail-safe methodology for assured success in deriving intended value from investments into analytics. It is a practitioners' handbook for creating a step-by-step transformational roadmap prioritizing the big data for the big decisions, the 10% of decisions that influence 90% of business outcomes, and delivering material improvements in the quality of decisions, as well as measurable value from analytics investments. The acid test for a data-driven organization is when all the big decisions, especially top-level strategic decisions, are taken based on data and not on the collective gut feeling of the decision makers in the organization.

Evaluates innovation policy and actions and considers real-world examples. Looks to the future of innovation and the role of future technologies. Provides an overview of recent policy trends in innovation and how they contribute to the creation of technology hotspots. Identifies how governments, industry, the research community and local communities can work together to craft individualised approaches to increasing innovation at a local level and building new industries.

The book investigates various MPPT algorithms, and the optimization of solar energy using machine learning and deep learning. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental. This book: Discusses data acquisition by the internet of things for real-time monitoring of solar cells. Covers artificial neural network techniques, solar collector optimization, and artificial neural network applications in solar heaters, and solar stills. Details solar analytics, smart centralized control centers, integration of microgrids, and data mining on solar data. Highlights the concept of asset performance improvement, effective forecasting for energy production, and Low-power wide-area network applications. Elaborates solar cell design principles, the equivalent circuits of single and two diode models, measuring idealist factors, and importance of series and shunt resistances. The text elaborates solar cell design principles, the equivalent circuit of single diode model, the equivalent circuit of two diode model, measuring idealist factor, and importance of series and shunt resistances. It further discusses perturb and observe technique, modified P&O method, incremental conductance method, sliding control method, genetic algorithms, and neuro-fuzzy methodologies. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in diverse engineering domains including electrical, electronics and communication, computer, and environmental.

This book deals with how to measure innovation in crisis management, drawing on data, case studies, and lessons learnt from different European countries. The aim of this book is to tackle innovation in crisis management through lessons learnt and experiences gained from the implementation of mixed methods through a practitioner-driven approach in a large-scale demonstration project (DRIVER+). It explores innovation from the perspective of the end-users by focusing on the needs and problems they are trying to address through a tool (be it an app, a drone, or a training program) and takes a deep dive into what is needed to understand if and to what extent the tool they have in mind can really bring innovation. This book is a toolkit for readers interested in understanding what needs to be in place to measure innovation: it provides the know-how through examples and best practices. The book will be a valuable source of knowledge for scientists, practitioners, researchers, and postgraduate students studying safety, crisis management, and innovation.

The significant objective of this edited book is to bridge the gap between smart manufacturing and big data by exploring the challenges and limitations. Companies employ big data technology in the manufacturing field to acquire data about the products. Manufacturing companies could gain a deep business insight by tracking customer details, monitoring fuel consumption, detecting product defects, and supply chain management. Moreover, the convergence of smart manufacturing and big data analytics currently suffers due to data privacy concern, short of qualified personnel, inadequate investment, long-term storage management of high-quality data. The technological advancement makes the data storage more accessible, cheaper and the convergence of these technologies seems to be more promising in the recent era. This book identified the innovative challenges in the industrial domains by integrating heterogeneous data sources such as structured data, semi-structures data, geo-spatial data, textual information, multimedia data, social networking data, etc. It promotes data-driven business modelling processes by adopting big data technologies in the manufacturing industry. Big data analytics is emerging as a promising discipline in the manufacturing industry to build the rigid industrial data platforms. Moreover, big data facilitates process automation in the complete lifecycle of product design and tracking. This book is an essential guide and reference since it synthesizes interdisciplinary theoretical concepts, definitions, and models, involved in smart manufacturing domain. It also provides real-world scenarios and applications, making it accessible to a wider interdisciplinary audience. Features The readers will get an overview about the smart manufacturing system which enables optimized manufacturing processes and benefits the users by increasing overall profit The researchers will get insight about how the big data technology leverages in finding new associations, factors and patterns through data stream observations in real time smart manufacturing systems The industrialist can get an overview about the detection of defects in design, rapid response to market, innovative products to meet the customer requirement which can benefit their per capita income in better way Discusses technical viewpoints, concepts, theories, and underlying assumptions that are used in smart manufacturing Information delivered in a user-friendly manner for students, researchers, industrial experts, and business innovators, as well as for professionals and practitioners

Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms - When to use them & Why - for Application developers and Researchers Machine Learning from an Application Perspective - General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.

The sequential analysis of data and information gathered from past to present is called time series analysis. Time series data are of high dimension, large size and updated continuously. A time series depends on various factors like trend, seasonality, cycle and irregular data set, and is basically a series of data points well-organized in time. Time series forecasting is a significant area of machine learning. There are various prediction problems that are time-dependent and these problems can be handled through time series analysis. Computational intelligence (CI) is a developing computing approach for the forthcoming several years. CI gives the litheness to model the problem according to given requirements. It helps to find swift solutions to the problems arising in numerous disciplines. These methods mimic human behavior. The main objective of CI is to develop intelligent machines to provide solutions to real world problems, which are not modelled or too difficult to model mathematically. This book aims to cover the recent advances in time series and applications of CI for time series analysis.

Technology Innovation discusses the fundamental aspects of processes and structures of technology innovation. It offers a new perspective concerning fundamentals aspects not directly involved in the complex relations existing between technology and the socio-economic system. By considering technology and its innovation from a scientific point of view, the book presents a novel definition of technology as a set of physical, chemical, and biological phenomena, producing an effect exploitable for human purposes. Expanding on the general model of technology innovation by linking the model of technology, based on a structure of technological operations, with the models of the structures for technology innovation, based on organization of fluxes of knowledge and capitals, the book considers various technological processes and the stages of the innovation process. Offers a perspective on the evolution of technology in the frame of an industrial platform network Explains a novel definition of technology as a set of physical, chemical, and biological phenomena producing an effect exploitable for human purposes Discusses technology innovation as result of structures organizing fluxes of knowledge and capitals Provides a technology model simulating the functioning of technology with its optimization Presents a technology innovation model explaining the territorial technology innovation process The book is intended for academics, graduate students, technology developers who are involved in operations management and research, innovation, and technology development.

ITIL is the leading best-practice framework for ITSM (IT service management) and is globally adopted in both the public and private sectors. The latest evolution of the framework - ITIL 4 - has been significantly updated and addresses new ITSM challenges, includes new technologies and incorporates new ways of working. ITIL 4 has evolved to a value system-focused approach that can be integrated with other management practices and ways of working, such as Agile and DevOps. Its end-to-end digital operation model has been designed to help IT teams create, deliver and operate technical products and services that fit their organisation's wider business strategy. ITIL(R) 4 Essentials contains everything you need to know to pass the ITIL 4 Foundation Certificate, plus more. It covers practices and concepts that are not addressed as part of the Foundation syllabus, making it ideal for newly qualified practitioners. The book offers practical tips - based on the author's extensive experience - for applying service management in the real world, with symbols used throughout to highlight which content is related to the ITIL 4 Foundation syllabus and which is not. Ideal for self-study candidates and training participants, ITIL 4 Essentials will prove a helpful companion to their studies and a practical aid for their professional development. Project managers, contractors or consultants with limited study time will also find it essential to their part-time education. This second edition has been updated to align with amendments to the ITIL(R) 4 Foundation syllabus, including: Replacing 'change control' with 'change enablement' throughout; The removal of 'IT' from the definition of a change; and Updating definitions for customer, sponsor and user. A perfect companion before, during and after your ITIL exam - buy your copy today. ITIL(R) is a registered trademark of AXELOS Limited. All rights reserved. This book is an official AXELOS licensed product.

Influence action through data! This is not a book. It is a one-of-a-kind immersive learning experience through which you can become--or teach others to be--a powerful data storyteller. Let's practice! helps you build confidence and credibility to create graphs and visualizations that make sense and weave them into action-inspiring stories. Expanding upon best seller storytelling with data's foundational lessons, Let's practice! delivers fresh content, a plethora of new examples, and over 100 hands-on exercises. Author and data storytelling maven Cole Nussbaumer Knaflic guides you along the path to hone core skills and become a well-practiced data communicator. Each chapter includes: Practice with Cole: exercises based on real-world examples first posed for you to consider and solve, followed by detailed step-by-step illustration and explanation Practice on your own: thought-provoking questions and even more exercises to be assigned or worked through individually, without prescribed solutions Practice at work: practical guidance and hands-on exercises for applying storytelling with data lessons on the job, including instruction on when and how to solicit useful feedback and refine for greater impact The lessons and exercises found within this comprehensive guide will empower you to master--or develop in others--data storytelling skills and transition your work from acceptable to exceptional. By investing in these skills for ourselves and our teams, we can all tell inspiring and influential data stories!

More frequent and complex cyber threats require robust, automated and rapid responses from cyber security specialists. This book offers a complete study in the area of graph learning in cyber, emphasising graph neural networks (GNNs) and their cyber security applications. Three parts examine the basics; methods and practices; and advanced topics. The first part presents a grounding in graph data structures and graph embedding and gives a taxonomic view of GNNs and cyber security applications. Part two explains three different categories of graph learning including deterministic, generative and reinforcement learning and how they can be used for developing cyber defence models. The discussion of each category covers the applicability of simple and complex graphs, scalability, representative algorithms and technical details. Undergraduate students, graduate students, researchers, cyber analysts, and AI engineers looking to understand practical deep learning methods will find this book an invaluable resource.

Focusing on the critical role IT plays in organizational development, the book shows how to employ action learning to improve the competitiveness of an organization. Defining the current IT problem from an operational and strategic perspective, it presents a collection of case studies that illustrate key learning issues. It details a dynamic model for effective IT management through adaptive learning techniques-supplying proven educational theories and practices to foster the required changes in your staff. It examines existing organizational learning theories and the historical problems that occurred with companies that have used them, as well as those that have failed to use them.

Preparing for your SAP S/4HANA business process integration exam? Make the grade with this certification study guide to C_TS410! From financial accounting to warehouse management, this guide will review the key technical and functional knowledge you need to exceed the cut score. Explore test methodology, key concepts for each topic area, and practice questions and answers. Your path to C_TS410 certification begins here! In this book, you'll learn about:a. The TestGet ready for test day! This guide follows the exact structure of the exam, so align your study of SAP S/4HANA business process integration with the test objectives and walk through the topics covered in C_TS410_2020. b. Core ContentReview major subject areas like financial accounting, source-to-pay processing, and human experience management. Then master important terminology and key takeaways for each subject. c. Q&AAfter reviewing each chapter, solidify your knowledge with questions and answers for each section and improve your test-taking skills.Highlights Include: 1) Exams C_TS410_2020 2) Financial and management accounting 3) Source-to-pay processing 4) Lead-to-cash processing 5) Design-to-operate processing 6) Procurement7) Supply chain 8) Production planning 9) Enterprise asset management 10) Warehouse management 11) Project systems 12) Human experience management

Hidden and Devalued Feminized Labour in the Digital Humanities examines the data-driven labour that underpinned the Index Thomisticus-a preeminent project of the incunabular digital humanities-and advanced the data-foundations of computing in the Humanities. Through oral history and archival research, Nyhan reveals a hidden history of the entanglements of gender in the intellectual and technical work of the early digital humanities. Setting feminized keypunching in its historical contexts-from the history of concordance making, to the feminization of the office and humanities computing-this book delivers new insight into the categories of work deemed meritorious of acknowledgement and attribution and, thus, how knowledge and expertise was defined in and by this field. Focalizing the overlooked yet significant data-driven labour of lesser-known individuals, this book challenges exclusionary readings of the history of computing in the Humanities. Contributing to ongoing conversations about the need for alternative genealogies of computing, this book is also relevant to current debates about diversity and representation in the Academy and the wider computing sector. Hidden and Devalued Feminized Labour in the Digital Humanities will be of interest to researchers and students studying digital humanities, library and information science, the history of computing, oral history, the history of the humanities, and the sociology of knowledge and science.

With recent advances in IT in areas such as AI and IoT, collaboration systems such as business chat, cloud services, conferencing systems, and unified communications are rapidly becoming widely used as new IT applications in global corporations' strategic activities. Through in-depth longitudinal studies of global corporations, the book presents a new theoretical framework and implications for IT-enabled dynamic capabilities using collaboration systems from the perspective of micro strategy theory and organization theory. The content of the book is based on longitudinal analyses that employ various qualitative research methods including ethnography, participant observation, action research and in-depth case studies of global corporations in Europe, the United States and Asia that actively use collaboration systems. It presents a new concept of micro dynamism whereby dynamic "IT-enabled knowledge communities" such as "IT-enabled communities of practice" and "IT-enabled strategic communities" create "IT-enabled dynamic capabilities" through the integration of four research streams - an information systems view, micro strategy view, micro organization view and knowledge-based view. The book demonstrates that collaboration systems create, maintain and develop "IT-enabled knowledge communities" within companies and are strategic IT applications for enhancing the competitiveness of companies in the ongoing creation of new innovation and the realization of sustainable growth in a 21st century knowledge-based society. This book is primarily written for academics, researchers and graduate students, but will also offer practical implications for business leaders and managers. Its use is anticipated not only in business and management schools, graduate schools and university education environments around the world but also in the broad business environment including management and leadership development training.

More frequent and complex cyber threats require robust, automated and rapid responses from cyber security specialists. This book offers a complete study in the area of graph learning in cyber, emphasising graph neural networks (GNNs) and their cyber security applications. Three parts examine the basics; methods and practices; and advanced topics. The first part presents a grounding in graph data structures and graph embedding and gives a taxonomic view of GNNs and cyber security applications. Part two explains three different categories of graph learning including deterministic, generative and reinforcement learning and how they can be used for developing cyber defence models. The discussion of each category covers the applicability of simple and complex graphs, scalability, representative algorithms and technical details. Undergraduate students, graduate students, researchers, cyber analysts, and AI engineers looking to understand practical deep learning methods will find this book an invaluable resource.

Presents concepts of data for business decision making as well as algorithms and models used to analyze data used to solve business problems. Use data analytics to inform decisions related to product price and possession utilities Market products on the basis of consumer analytics

Broadens the horizons of Chinese culture enthusiasts without expertise in animation, and helps to dismantle stereotypical perceptions of Chinese animated film culture as established in the discourses of Western animation studios. Answers the rising need for conducting thorough studies of Chinese mass culture and mechanisms of soft power and indoctrination, and thus helps to understand the cultural identity and heritage of China, which is becoming a global superpower and an aspiring world economic leader. Complements a niche existing in the general knowledge on Asian popular cultures.

1. Understand the audit culture, challenges, and benefits of the CAE role in digitally transforming business environment in smart cities 2. Identify ways to advance the value of Internal Audit in digital era 3. Use and control the resources of the city efficiently, and to ensure that the system units work properly in an integrated way.

Blockchain for IoT provides the basic concepts of Blockchain technology and its applications to varied domains catering to socio-technical fields. It also introduces intelligent Blockchain platforms by way of infusing elements of computational intelligence into Blockchain technology. With the help of an interdisciplinary approach, it includes insights into real-life IoT applications to enable the readers to assimilate the concepts with ease. This book provides a balanced approach between theoretical understanding and practical applications. Features: A self-contained approach to integrating the principles of Blockchain with elements of computational intelligence A rich and novel foundation of Blockchain technology with reference to the internet of things conjoined with the tenets of artificial intelligence in yielding intelligent Blockchain platforms Elucidates essential background, concepts, definitions, and theories thereby putting forward a complete treatment on the subject Information presented in an accessible way for research students of computer science and information technology, as well as software professionals who can inherit the much-needed developmental ideas to boost up their computing knowledge on distributed platforms This book is aimed primarily at undergraduates, postgraduates, and researchers studying Blockchain.

Explore the fascinating and rich world of Secret Key cryptography! This book provides practical methods for encrypting messages, an interesting and entertaining historical perspective, and an incredible collection of ciphers and codes-including 30 unbreakable methods. In Secret Key Cryptography: Ciphers, from simple to unbreakable you will: Measure the strength of your ciphers and learn how to guarantee their security Construct and incorporate data-compression codes Generate true random numbers in bulk Construct huge primes and safe primes Add an undetectable backdoor to a cipher Defeat hypothetical ultracomputers that could be developed decades from now Construct 30 unbreakable ciphers Secret Key Cryptography gives you a toolbox of cryptographic techniques and Secret Key methods. The book's simple, non-technical language is easy to understand and accessible for any reader, even without the advanced mathematics normally required for cryptography. You'll learn how to create and solve ciphers, as well as how to measure their strength. As you go, you'll explore both historic ciphers and groundbreaking new approaches-including a never-before-seen way to implement the uncrackable One-Time Pad algorithm. about the technology Secret Key cryptography is the backbone of all modern computing infrastructure. Secret Key ciphers use the same key to encrypt and decrypt messages. Properly designed, these algorithms are efficient and practical. Some Secret Key approaches are uncrackable, even under attacks backed by supercomputers or quantum technology! about the book Secret Key Cryptography teaches anyone how to create a wide range of ciphers-even if you have no background in math or creating codes. You'll combine Secret Key techniques to achieve ciphers that are effectively uncrackable and avoid common pitfalls that result in strong-looking but weak ciphers. The book reveals scores of different cipher methods, including both historic examples and current innovations in the field. RETAIL SELLING POINTS * Measure the strength of your ciphers and learn how to guarantee their security * Construct and incorporate data-compression codes * Generate true random numbers in bulk * Construct huge primes and safe primes * Add an undetectable backdoor to a cipher * Defeat hypothetical ultra computers that could be developed decades from now * Construct 30 unbreakable ciphers AUDIENCE For professional engineers, computer scientists, and cryptography hobbyists. No advanced math knowledge is required

This monograph, for the first time in book form, considers the large structure of metric spaces as captured by bornologies: families of subsets that contain the singletons, that are stable under finite unions, and that are stable under taking subsets of its members. The largest bornology is the power set of the space and the smallest is the bornology of its finite subsets. Between these lie (among others) the metrically bounded subsets, the relatively compact subsets, the totally bounded subsets, and the Bourbaki bounded subsets. Classes of functions are intimately connected to various bornologies; e.g., (1) a function is locally Lipschitz if and only if its restriction to each relatively compact subset is Lipschitz; (2) a subset is Bourbaki bounded if and only if each uniformly continuous function on the space is bounded when restricted to the subset. A great deal of attention is given to the variational notions of strong uniform continuity and strong uniform convergence with respect to the members of a bornology, leading to the bornology of UC-subsets and UC-spaces. Spaces on which its uniformly continuous real-valued functions are stable under pointwise product are characterized in terms of the coincidence of the Bourbaki bounded subsets with a usually larger bornology. Special attention is given to Lipschitz and locally Lipschitz functions. For example, uniformly dense subclasses of locally Lipschitz functions within the real-valued continuous functions, Cauchy continuous functions, and uniformly continuous functions are presented. It is shown very generally that a function between metric spaces has a particular metric property if and only if whenever it is followed in a composition by a real-valued Lipschitz function, the composition has the property. Bornological convergence of nets of closed subsets, having Attouch-Wets convergence as a prototype, is considered in detail. Topologies of uniform convergence for continuous linear operators between normed spaces is explained in terms of the bornological convergence of their graphs. Finally, the idea of a bornological extension of a topological space is presented, and all regular extensions can be so realized.