Pulling aside the curtain of 'Big Data' buzz, this book introduces C-suite and other non-technical senior leaders to the essentials of obtaining and maintaining accurate, reliable data, especially for decision-making purposes. Bad data begets bad decisions, and an understanding of data fundamentals - how data is generated, organized, stored, evaluated, and maintained - has never been more important when solving problems such as the pandemic-related supply chain crisis. This book addresses the data-related challenges that businesses face, answering questions such as: What are the characteristics of high-quality data? How do you get from bad data to good data? What procedures and practices ensure high-quality data? How do you know whether your data supports the decisions you need to make? This clear and valuable resource will appeal to C-suite executives and top-line managers across industries, as well as business analysts at all career stages and data analytics students.

Healthcare Informatics: Improving Efficiency and Productivity examines the complexities involved in managing resources in our healthcare system and explains how management theory and informatics applications can increase efficiencies in various functional areas of healthcare services. Delving into data and project management and advanced analytics, this book details and provides supporting evidence for the strategic concepts that are critical to achieving successful healthcare information technology (HIT), information management, and electronic health record (EHR) applications. This includes the vital importance of involving nursing staff in rollouts, engaging physicians early in any process, and developing a more receptive organizational culture to digital information and systems adoption. We owe it to ourselves and future generations to do all we can to make our healthcare systems work smarter, be more effective, and reach more people. The power to know is at our fingertips; we need only embrace it. -From the foreword by James H. Goodnight, PhD, CEO, SAS Bridging the gap from theory to practice, it discusses actual informatics applications that have been incorporated by various healthcare organizations and the corresponding management strategies that led to their successful employment. Offering a wealth of detail, it details several working projects, including: A computer physician order entry (CPOE) system project at a North Carolina hospital E-commerce self-service patient check-in at a New Jersey hospital The informatics project that turned a healthcare system's paper-based resources into digital assets Projects at one hospital that helped reduce excesses in length of stay, improved patient safety; and improved efficiency with an ADE alert system A healthcare system's use of algorithms to identify patients at risk for hepatitis Offering the guidance that healthcare specialists need to make use of various informatics platforms, this book provides the motivation and the proven methods that can be adapted and applied to any number of staff, patient, or regulatory concerns.

1. It is a practical guide to understanding and implementation 2. It assumes no prior in depth knowledge 3. It is written in plain language and may be understood by anyone, whether or not they are qualified or involved with IT. It is therefore equally suitable for senior management, IT practitioners, students and interested individuals.

This set contains the two volumes, Biomolecular Information Processing together with Molecular and Supramolecular Information Processing with contributions from all the major scientists in the field. Edited by a renowned and much cited chemist, the two books cover all the different systems, providing an excellent overview of the latest developments in this rapidly expanding area.
A must-have for all researchers working on this very hot topic.

The deployment of software patches can be just as challenging as building entirely new workstations. Training and support issues can haunt even the most successful software launch for months. Preparing for the rigors of software deployment includes not just implementing change, but training employees, predicting and mitigating pitfalls, and managing expectations. Software Deployment, Updating, and Patching provides the skills you need to develop a comprehensive strategy for tracking and managing system configurations, as well as for updating and securing systems with the latest packs and patches. Written by two of Microsoft's top experts, this clear and concise manual demonstrates how to perform inventories of IT assets, test compatibility, target deployment, and evaluate management technologies. It also shows you how to create and implement your own deployment plans with recovery and remediation options, and how to recognize potential vulnerabilities.

New Work and Industry 4.0 have matured and this book takes a practical, experience-based approach to project management in these areas. It introduces methods and covers the practical aspects. It critically examines existing approaches and practices and shows their limitations. The book covers appropriate methods as well as human and social aspects. It contributes to the ongoing discussion of business practices and methods. It also aims to stimulate dialogue in the professional community. Digital Project Practice for New Work and Industry 4.0 begins by introducing basic concepts in the context of Industry 4.0 and discussing how they might influence organizational communication and impact the work environment. After examining the possibilities and challenges of remote work and collaboration in distributed teams all over the world, the book looks at a company's fundamental changes related to New Work from a practical business perspective as well as legal and ethical perspectives. It reviews the case of the VW emission scandal and recommends ways to improve corporate culture. Legal issues include New Work and hybrid forms of collaboration as well as liability for automated decisions (i.e., the potential need for an 'electronic person'). Other implications for the workplace include how: Industry 4.0 might influence the potential demand for "Digital Unions" Industry 4.0, and lean production, and their applications can change industrial practices Open Banking presents new approaches and new business models Work structures and systems can empower employees' work self-management This book also looks at how New Work effects individual workers. It addresses digital stress, introduces strategies for coping with it, and discusses related topics. It also explores the benefits of meditation and the economics of mind, body, and spirit. In essence, this book cover appropriate methods along with human and social factors. It also covers practice, different perspectives, and various experiences from all around the globe. Contributing to the ongoing discussion on business practices and methods, this book will nourish and stimulate dialogue in the professional community.

This book explores how to use generative adversarial networks in a variety of applications and emphasises their substantial advancements over traditional generative models. This book's major goal is to concentrate on cutting-edge research in deep learning and generative adversarial networks, which includes creating new tools and methods for processing text, images, and audio. A Generative Adversarial Network (GAN) is a class of machine learning framework and is the next emerging network in deep learning applications. Generative Adversarial Networks(GANs) have the feasibility to build improved models, as they can generate the sample data as per application requirements. There are various applications of GAN in science and technology, including computer vision, security, multimedia and advertisements, image generation, image translation,text-to-images synthesis, video synthesis, generating high-resolution images, drug discovery, etc. Features: Presents a comprehensive guide on how to use GAN for images and videos. Includes case studies of Underwater Image Enhancement Using Generative Adversarial Network, Intrusion detection using GAN Highlights the inclusion of gaming effects using deep learning methods Examines the significant technological advancements in GAN and its real-world application. Discusses as GAN challenges and optimal solutions The book addresses scientific aspects for a wider audience such as junior and senior engineering, undergraduate and postgraduate students, researchers, and anyone interested in the trends development and opportunities in GAN and Deep Learning. The material in the book can serve as a reference in libraries, accreditation agencies, government agencies, and especially the academic institution of higher education intending to launch or reform their engineering curriculum

There is considerable connection between growth of the personnel in the organization and the ability for the company to compete over time. Looking outside for help training may be required but looking within for opportunities for enhanced training and growth, will foster a continually improving and growing organization. This book examines the opportunities for learning, within the organization and its' activities, along with the connection to motivation. Additionally, it provides information on the characteristics of organizations that are able to quickly disseminate, along with approaches for improving this distribution of that learning throughout the organization.

'Natural Language Processing in the Real World' is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real-world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects. .

As long as humans write software, the key to successful software security is making the software development program process more efficient and effective. Although the approach of this textbook includes people, process, and technology approaches to software security, Practical Core Software Security: A Reference Framework stresses the people element of software security, which is still the most important part to manage as software is developed, controlled, and exploited by humans. The text outlines a step-by-step process for software security that is relevant to today's technical, operational, business, and development environments. It focuses on what humans can do to control and manage a secure software development process using best practices and metrics. Although security issues will always exist, students learn how to maximize an organization's ability to minimize vulnerabilities in software products before they are released or deployed by building security into the development process. The authors have worked with Fortune 500 companies and have often seen examples of the breakdown of security development lifecycle (SDL) practices. The text takes an experience-based approach to apply components of the best available SDL models in dealing with the problems described above. Software security best practices, an SDL model, and framework are presented in this book. Starting with an overview of the SDL, the text outlines a model for mapping SDL best practices to the software development life cycle (SDLC). It explains how to use this model to build and manage a mature SDL program. Exercises and an in-depth case study aid students in mastering the SDL model. Professionals skilled in secure software development and related tasks are in tremendous demand today. The industry continues to experience exponential demand that should continue to grow for the foreseeable future. This book can benefit professionals as much as students. As they integrate the book's ideas into their software security practices, their value increases to their organizations, management teams, community, and industry.

Software Security: Concepts & Practices is designed as a textbook and explores fundamental security theories that govern common software security technical issues. It focuses on the practical programming materials that will teach readers how to implement security solutions using the most popular software packages. It's not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Features The book presents the implementation of a unique socio-technical solution for real-time cybersecurity awareness. It provides comprehensible knowledge about security, risk, protection, estimation, knowledge and governance. Various emerging standards, models, metrics, continuous updates and tools are described to understand security principals and mitigation mechanism for higher security. The book also explores common vulnerabilities plaguing today's web applications. The book is aimed primarily at advanced undergraduates and graduates studying computer science, artificial intelligence and information technology. Researchers and professionals will also find this book useful.

Digital Image Processing with C++ presents the theory of digital image processing, and implementations of algorithms using a dedicated library. Processing a digital image means transforming its content (denoising, stylizing, etc.), or extracting information to solve a given problem (object recognition, measurement, motion estimation, etc.). This book presents the mathematical theories underlying digital image processing, as well as their practical implementation through examples of algorithms implemented in the C++ language, using the free and easy-to-use CImg library. Chapters cover in a broad way the field of digital image processing and proposes practical and functional implementations of each method theoretically described. The main topics covered include filtering in spatial and frequency domains, mathematical morphology, feature extraction and applications to segmentation, motion estimation, multispectral image processing and 3D visualization. Students or developers wishing to discover or specialize in this discipline, teachers and researchers wishing to quickly prototype new algorithms, or develop courses, will all find in this book material to discover image processing or deepen their knowledge in this field.

Cloud based Multi-Modal Information Analytics: A Hands-on Approach discusses the various modalities of data and provide an aggregated solutions using cloud. It includes the fundamentals of neural networks, different types and how it can be used for the multi-modal information analytics. The various application areas that are image-centric and video are also presented with deployment solutions in the cloud. Features Life cycle of the multi- modal data analytics is discussed with applications of modalities of text, image, and video. Deep Learning fundamentals and architectures covering CNN, RNN and its types for learning for different multi-modal networks. Applications of Multi-Modal Analytics covering Text , Speech, and Image. This book is aimed at researchers in Multi-modal analytics and related areas

Introduction to Programming with Java: A Problem Solving Approach teaches the reader how to write programs using Java. It does so with a unique approach that combines fundamentals first with objects early. The book transitions smoothly through a carefully selected set of procedural programming fundamentals to object-oriented fundamentals. During this early transition and beyond, the book emphasizes problem solving. For example, Chapter 2 is devoted to algorithm development, Chapter 8 is devoted to program design, and problem-solving sections appear throughout the book. The third edition introduces several new Java language features, most of the end-of-chapter GUI sections and the final GUI chapters use JavaFX, and almost all end-of-chapter exercises are new.

Computer vision-based crack-like object detection has many useful applications, such as pavement surface inspection, underground pipeline inspection, bridge cracking monitoring, railway track assessment, etc. However, in most contexts, cracks appear as thin, irregular long-narrow objects, and often are buried into complex, textured background with high diversity which make the crack detection very challenging. During the past a few years, the deep learning technique has achieved great success and has been utilized for solving a variety of object detection problems. However, using deep learning for accurate crack localization is non-trivial. This book discusses crack-like object detection problem in a comprehensive way. It starts by discussing traditional image processing approaches for solving this problem, and then introduces deep learning-based methods. The book provides a comprehensive review of object detection problems and focuses on the most challenging problem, crack-like object detection, to dig deep into the deep learning method. It includes examples of real-world problems, which are easy to understand and could be a good tutorial for introducing computer vision and machine learning.

Cybersecurity risk is a top-of-the-house issue for all organizations. Cybertax-Managing the Risks and Results is a must read for every current or aspiring executive seeking the best way to manage and mitigate cybersecurity risk. It examines cybersecurity as a tax on the organization and charts the best ways leadership can be cybertax efficient. Viewing cybersecurity through the cybertax lens provides an effective way for non-cybersecurity experts in leadership to manage and govern cybersecurity in their organizations The book outlines questions and leadership techniques to gain the relevant information to manage cybersecurity threats and risk. The book enables executives to: Understand cybersecurity risk from a business perspective Understand cybersecurity risk as a tax (cybertax) Understand the cybersecurity threat landscape Drive business-driven questions and metrics for managing cybersecurity risk Understand the Seven C's for managing cybersecurity risk Governing the cybersecurity function is as important as governing finance, sales, human resources, and other key leadership responsibilities Executive leadership needs to manage cybersecurity risk like they manage other critical risks, such as sales, finances, resources, and competition. This book puts managing cybersecurity risk on an even plane with these other significant risks that demand leader ships' attention. The authors strive to demystify cybersecurity to bridge the chasm from the top-of-the-house to the cybersecurity function. This book delivers actionable advice and metrics to measure and evaluate cybersecurity effectiveness across your organization.

In May 2021, Jim Gosler, known as the Godfather and commander of US agencies' cyber offensive capability, said, ''Either the Intelligence Community (IC) would grow and adapt, or the Internet would eat us alive.'' Mr Gosler was speaking at his retirement only several months before the terrorist attacks of 9/11. He possibly did not realise the catalyst or the tsunami that he and his tens of thousands of US IC offensive website operatives had created and commenced. Over the last two decades, what Mr Gosler and his army of Internet keyboard warriors created would become the modus operandi for every faceless, nameless, state-sponsored or individual cybercriminal to replicate against an unwary, ill-protected, and ignorant group of executives and security professionals who knew little to nothing about the clandestine methods of infiltration and weaponisation of the Internet that the US and UK agencies led, all in the name of security. This book covers many cyber and ransomware attacks and events, including how we have gotten to the point of massive digital utilisation, particularly during the global lockdown and COVID-19 pandemic, to online spending that will see twice the monetary amount lost to cybercrime than what is spent online. There is little to no attribution, and with the IC themselves suffering cyberattacks, they are all blamed on being sophisticated ones, of course. We are witnessing the undermining of our entire way of life, our economies, and even our liberties. The IC has lots to answer for and unequivocally created the disastrous situation we are currently in. They currently have little to no answer. We need-no, we must demand-change. That change must start by ensuring the Internet and all connections to it are secure and no longer allow easy access and exfiltration for both the ICs and cybercriminals.

A best-seller in its French edition, the construction of this book is original and its success in the French market demonstrates its appeal. It is based on three principles: 1. An organization of the chapters by families of algorithms : exhaustive search, divide and conquer, etc. At the contrary, there is no chapter only devoted to a systematic exposure of, say, algorithms on strings. Some of these will be found in different chapters. 2. For each family of algorithms, an introduction is given to the mathematical principles and the issues of a rigorous design, with one or two pedagogical examples. 3. For its most part, the book details 150 problems, spanning on seven families of algorithms. For each problem, a precise and progressive statement is given. More important, a complete solution is detailed, with respect to the design principles that have been presented ; often, some classical errors are pointed at. Roughly speaking, two thirds of the book are devoted to the detailed rational construction of the solutions.

Digital Intermediation offers a new framework for understanding content creation and distribution across automated media platforms - a new mediatisation process. The book draws on empirical and theoretical research to carefully identify and describe a number of unseen digital infrastructures that contribute to a predictive media production process through technologies, institutions and automation. Field data is drawn from several international sites, including Los Angeles, San Francisco, Portland, London, Amsterdam, Munich, Berlin, Hamburg, Sydney and Cartagena. By highlighting an increasingly automated content production and distribution process, the book responds to a number of regulatory debates on the societal impact of social media platforms. It highlights emerging areas of key importance that shape the production and distribution of social media content, including micro-platformization and digital first personalities. The book explains how technologies, institutions and automation are used within agencies to increase exposure for the talent they manage, while providing inside access to the processes and requirements of producers who create content for platform algorithms. Finally, it outlines user agency as a strategy for those who seek diversity in the information they access on automated social media content distribution platforms. The findings in this book provide key recommendations for policymakers working within digital media platforms, and will be invaluable reading for students and academics interested in automated media environments.

The internet has launched the world into an era into which enormous amounts of data are generated every day through technologies with both positive and negative consequences. This often refers to big data . This book explores big data in organisations operating in the criminology and criminal justice fields. Big data entails a major disruption in the ways we think about and do things, which certainly applies to most organisations including those operating in the criminology and criminal justice fields. Big data is currently disrupting processes in most organisations - how different organisations collaborate with one another, how organisations develop products or services, how organisations can identify, recruit, and evaluate talent, how organisations can make better decisions based on empirical evidence rather than intuition, and how organisations can quickly implement any transformation plan, to name a few. All these processes are important to tap into, but two underlying processes are critical to establish a foundation that will permit organisations to flourish and thrive in the era of big data - creating a culture more receptive to big data and implementing a systematic data analytics-driven process within the organisation. Written in a clear and direct style, this book will appeal to students and scholars in criminology, criminal justice, sociology, and cultural studies but also to government agencies, corporate and non-corporate organisations, or virtually any other institution impacted by big data.

High-speed, power-efficient analog integrated circuits can be used as standalone devices or to interface modern digital signal processors and micro-controllers in various applications, including multimedia, communication, instrumentation, and control systems. New architectures and low device geometry of complementary metaloxidesemiconductor (CMOS) technologies have accelerated the movement toward system on a chip design, which merges analog circuits with digital, and radio-frequency components.

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 provides a first-of-its-kind approach for using blockchain to enhance resilience in disaster supply chain and logistics management, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources - these are elements of volatility, uncertainty, complexity, and ambiguity (VUCA) describing a dynamic environment that now form the "new norm" for many leaders. Blockchain-Enabled Resilience: An Integrated Approach for Disaster Supply Chain and Logistics Management analyzes the application of blockchain technology used to enable resilience in a disaster supply chain network. It discusses IoT and DVFS algorithms for developing a network-based simulation and presents advancements in disaster supply chain strategies using smart contacts for collaborations. The book covers how success is based on collaboration, coordination, sovereignty, and equality in distributing resources and offers a theoretical analysis that reveals that enhancing resilience can improve collaboration and communication and can result in more time-efficient processing for disaster supply management. This book provides a first-of-its-kind approach for managers and policy-makers as well as researchers interested in using blockchain to enhance resilience in disaster supply chains, especially when dealing with dynamic communication, relief operations, prioritization, coordination, and distribution of scarce resources. Practical guidance is provided for managers interested in implementation. A robust research agenda is also provided for those interested in expanding present research.

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.

A more accessible approach than most competitor texts, which move into advanced, research-level topics too quickly for today's students. Part I is comprehensive in providing all necessary mathematical underpinning, particularly for those who need more opportunity to develop their mathematical competence. More confident students may move directly to Part II and dip back into Part I as a reference. Ideal for use as an introductory text for courses in quantum computing. Fully worked examples illustrate the application of mathematical techniques. Exercises throughout develop concepts and enhance understanding. End-of-chapter exercises offer more practice in developing a secure foundation.