This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance. The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data. Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

Work with Db2 to write SQL and access databases using optimized code for the fastest response. This book will give you complete documentation on DB2 via Python for the IBM_db module and provide a number of examples for the usage of each module API. Begin by getting your free version of Db2 for Linux and Windows. While the book concentrates more on the Linux version of Db2, it also covers enough of the Windows version so that you're comfortable with obtaining and installing Db2 on your version of Windows. Next, you'll see how to install the sample database that comes with Db2, and take some data from the web to design a database around it, including tables and indexes. For Db2 to be really useful you need to use strong SQL expressions. This book provides specific examples of how to avoid using poor ones that can cause extra processing time for the query. Lastly, you'll look at each API in the ibm_db and ibm_db_dbi module. This module is not sponsored by IBM and must be installed separately from the Db2 database. After reading Foundation Db2 and Python you'll be able to install Db2 on Windows or Linux, and perform backups and restore data. What You'll Learn Obtain and install Db2 properly on Linux and Windows Create databases and load them on Db2 Work with ibm_db and ibm_db_dbi API modules for Python Write SQL for Db2 Review the future of the ibm_db Python module Who This Book Is For Python programmers and DB2 administrators interested in building application with Python and DB2

This book focuses on Fintech regulation in Asian, situating local developments in broader economic, regulatory and technological contexts. Over the last decade, Fintech - broadly defined as the use of new information technologies to help financial institutions and intermediaries compete in the marketplace - has disrupted the financial services sector. Like other 21st century technological developments, Fintech is a global phenomenon that plays out in local economic, political and regulatory contexts, and this dynamic interplay between global trends and local circumstances has created a complex and fast-changing landscape. Diverse stakeholders (most obviously incumbent financial service providers, tech start-ups and regulators) all pursue a competitive edge against a background of profound uncertainty about the future direction and possible effects of multiple emerging technologies. Compounding these difficulties are uncertainties surrounding regulatory responses. Policymakers often struggle to identify appropriate regulatory responses and increasingly turn to policy experimentation. Such issues add to the challenges for the various actors operating in the Fintech space. This situation is particularly fluid in Asia, since many jurisdictions are seeking to establish themselves as a regional hub for new financial services.

In this new and exciting seventh edition, Technology Management continues to provide R&D managers with essential insight and information to address the most important challenges and opportunities of their profession. Divided into six sections, with contributions from experts in their field, this book is a current, complete reference guide into the ever-changing landscape of technology management.

This book highlights the importance of talent management practices in recruiting, developing and retaining talented professionals in the digital and IT&C industry. It unpacks the distinctive characteristics of 'digital talent' represented by a wide spectrum of professionals and managers with digital abilities, competencies and skills who add considerable value to organizations and industries worldwide. It shows that despite digital talent's increased variety and significant contribution to digital transformation processes, much of the existing human resource and talent management research and practice fail to account for their distinctiveness. This book calls for the need for a new kind of talent management, referred to as 'digital talent management' (DTM) that is applicable to digital talent and decidedly integrates digital talent's distinctive characteristics into talent management strategies and practices in a human-centered manner. Drawing upon existing, yet disconnected, streams of literature and empirical evidence derived from the information technology and communication (IT&C) industry, this book defines digital talent and delineates strategies to attract, develop and retain them for an uncertain and renewed future.

This book highlights the opportunities and risks of digitalization and digital transformation for our global economy at both the micro and macro level. Experts from various fields, presenting both scientific and practice-oriented perspectives, identify and critically analyse areas of tension and development potential in connection with new business models and sustainability efforts in our society. It is divided into four parts, the first of which highlights new technological advances in areas such as blockchain, cryptocurrencies and fintechs, and discusses the challenges they pose for public regulation. The second part illustrates digitalization's effects on and potential advantages for public welfare, focusing on key areas such as education, health and smart cities. The third part focuses on challenges for corporate and public management, particularly for leadership and Corporate Social Responsibility, while the fourth part discusses new dimensions for analysis based on big data. The contributions gathered here are partly an outcome of the International Conference on Digitalization, Digital Transformation and Sustainability held in Budapest in October 2020 and generously supported by the Hanns Seidel Foundation.

This book provides significant conceptual and empirical contributions to the understanding of service science and the practices of service sectors in the wake of the fourth industrial revolution bringing together a collection of articles written by keynote and invited speakers at the 2nd Service Science Symposium held on 24 November 2019. The symposium was organised by the Serviceology Society Malaysia (SESMA), which aims to bring service researchers and practitioners under one roof to redefine service concepts and ideas and explore their application in real industrial and community settings. In their contributions, authors present multiple real-world cases of service systems to demonstrate how organisations can incorporate service science to achieve sustainable development. By re-examining the existing service science models and the value creation process using valuable insights obtained from industries and communities in Malaysia, Japan and Taiwan, the authors present a new way forward for organisations.

Digital technologies are currently dramatically changing healthcare. This book introduces the reader to the latest digital innovations in healthcare in fields such as artificial intelligence, points out new ways in patient care and describes the limits of its application. It also offers essential guidance in the form of structured and authoritative contributions by domain experts spanning from artificial intelligence to hospital management to radiology to dentistry to preventive medicine. Furthermore, it shares ideas and experiences of industry veterans, in particular on how IT-driven solutions could solve long-standing issues in the fields of healthcare and hospitalization. It also gives advice on what new digital technologies to consider for becoming a healthcare market leader in the future. Taken together, these contributions provide a "road map" to guide decision makers, physicians, academics, industry representatives and other interested readers to understand the large impact of digital technology on healthcare today and its enormous potential for future development.

This book illustrates the importance effective cost management systems in providing a supportive environment in which reliable and relevant management information can be generated. Such a cost management system is only attainable if the importance of key business, operational and stakeholder requirements are recognised within the organisational context. In illustrating this importance, this book provides several case studies as examples thereof. The first two case studies focus on the engineering sector and illustrates the development of a cost management system in a water recycling context; and the design of a budgetary system in a mining engineering context. The remaining case studies focus on the services sector, including cost management systems for a digital technology services provider and a medical insurance services provider; an alternative activity-based costing approach for a public sector services provider; and finallya re-designed value stream for an automotive services provider. Academic researchers and industry managers in the fields of management accounting and financial management, as well as engineering and operations management, will find value in the experiences described herein.

CHANGE! A Student Guide to Social Action guides students, faculty, and staff with the goal of helping students bring about the change they believe will improve their community. What distinguishes an experiential social action class from other social change courses is that students are actively involved in enacting a policy change of their choice, providing first-hand experience of democracy and power. Students can choose to start a new campaign, keep a campaign going from a previous semester, or join a community campaign. This valuable new edition includes updates to the Student Victories section, reordering and updating of chapters for better student learning, and updates to all of the portfolio assignments.

A Standard for Auditing Computer Applications is a dynamic new resource for evaluating all aspects of automated business systems and systems environments. At the heart of A Standard for Auditing Computer Applications system is a set of customizable workpapers that provide blow-by-blow coverage of all phases of the IT audit process for traditional mainframe, distributed processing, and client/server environments.A Standard for Auditing Computer Applications was developed by Marty Krist, an acknowledged and respected expert in IT auditing. Drawing upon his more than twenty years of auditing experience with leading enterprise organizations, worldwide, Marty walks you step-by-step through the audit process for system environments and specific applications and utilities. He clearly spells out what you need to look for and where to look for it, and he provides expert advice and guidance on how to successfully address a problem when you find one.When you order A Standard for Auditing Computer Applications, you receive a powerful package containing all the forms, checklists, and templates you'll ever need to conduct successful audits on downloadable resources. Designed to function as a handy, on-the-job resource, the book follows a concise, quick-access format. It begins with an overview of the general issues inherent in any IT review. This is followed by a comprehensive review of the audit planning process. The remainder of the book provides you with detailed, point-by-point breakdowns along with proven tools for:evaluating systems environments-covers all the bases, including IT administration, security, backup and recovery planning, systems development, and moreEvaluating existing controls for determining hardware and software reliabilityAssessing the new system development processEvaluating all aspects of individual applications, from I/O, processing and logical and physical security to documentation, training, and programmed proceduresAssessing specific applications and utilities, including e-mail, groupware, finance and accounting applications, CAD, R&D, production applications, and more

This volume constitutes a first approximation for the use of systems approaches and dynamic performance management as tools for collaborative governance. The chapters examine models and simulations used in some specific systems approaches, which contribute to facilitating problem focus and collective understanding of collaborative governance, especially in the area of performance management. The explicit connection between resources and outcomes promoted by this view helps managers to understand better how to improve policy and to create positive outcomes that create public value.

This book provides readers with a thorough understanding of various research areas within the field of data science. The book introduces readers to various techniques for data acquisition, extraction, and cleaning, data summarizing and modeling, data analysis and communication techniques, data science tools, deep learning, and various data science applications. Researchers can extract and conclude various future ideas and topics that could result in potential publications or thesis. Furthermore, this book contributes to Data Scientists' preparation and to enhancing their knowledge of the field. The book provides a rich collection of manuscripts in highly regarded data science topics, edited by professors with long experience in the field of data science. Introduces various techniques, methods, and algorithms adopted by Data Science experts Provides a detailed explanation of data science perceptions, reinforced by practical examples Presents a road map of future trends suitable for innovative data science research and practice

This book provides relevant theoretical frameworks and the latest empirical research findings of Operations Research/Management Science applied to Internet of Things. This book identifies and describes ways in which OR and MS have been applied and influenced the development of IoT. Examples are from smart industry; city; transportation; home and smart devices. It discusses future applications, trends, and potential benefits of this new discipline. It is written for professionals who want to improve their understanding of the strategic role of IoT at various levels of the organization, that is, IoT at the global economy level, at networks and organizations level, at teams and work groups, at information systems and, finally, IoT at the level of individuals, as players in the networked environments.

This book focuses on the implementation of Artificial Intelligence in Business, Education and Healthcare, It includes research articles and expository papers on the applications of Artificial Intelligence on Decision Making, Entrepreneurship, Social Media, Healthcare, Education, Public Sector, FinTech, and RegTech. It also discusses the role of Artificial Intelligence in the current COVID-19 pandemic, in the health sector, education, and others. It also discusses the impact of Artificial Intelligence on decision-making in vital sectors of the economy.

This book discusses the impact of advanced information technologies, such as data processing, machine learning, and artificial intelligence, on organizational decision-making processes and practices. One of the book's central themes is the interplay between human reasoning and machine logic in the context of organizational functioning, specifically, the fairly common situations in which subjective beliefs are pitted against objective evidence giving rise to conflict rather than enhancing the quality of organizational sensemaking. Aiming to not only raise the awareness of the potential challenges but also to offer solutions, the book delineates and discusses the core impediments to effective human-information technology interactions, and outlines strategies for overcoming those obstacles on the way to enhancing the efficacy of organizational decision-making.

This book examines the nature, extent and implications of rapid strides digitalization has made in India since the turn of the millennium. These have been examined not merely in the sphere of information and communication technology (ICT) but its multifarious applications spreading across almost all aspects of production, services and institutions which have profound repercussions for the transformation of the society and economy at the micro, meso and macro levels. With contributions from both ICT scholars and social scientists, this book presents diverse scenarios and unravels challenges faced in the process of technical applications, access by the users of these disruptive technologies (automation, e-commerce, big data analytics & algorithms, artificial intelligence, cloud computing, etc.) which, unlike heavy machines (embodied technology), mostly defy physical space, pace of mobility and inoperability between technologies. Chapters in this volume address challenges and possibilities in establishing and operating intricate engineering infrastructure, technical and societal constraints encountered in broad-basing digitalization across layers of educational and social skills conducive to difficult geographies. Issues dealt within this book include farming, healthcare, education, food processing, e-commerce, labour, rural community development, open source data and information democracy. The chapters also reflect upon implications on local economy and society, of the very global nature of these seamless technologies where inter-operability remains the quintessential advantage of digitalization whether promoted or spearheaded through the state, private sector or global capital. The book critiques policy inadequacies and suggests plausible policy approaches to reduce the adverse impacts of fast digitalization and broad-base potential benefits across space and levels of socio-economic development of regions and society. This book would be of interest to scholars, practitioners, technocrats, industry analysts, policy makers and civil society agencies.

This book presents selected examples of digitalization in the age of digital change. It is divided into two sections: "Digital Innovation," which features new technologies that stimulate and enable new business opportunities; and "Digital Business Transformation," comprising business and management concepts that employ specific technological solutions for their practical implementation. Combining new insights from research, teaching and management, including digital transformation, e-business, knowledge representation, human-computer interaction, and business optimization, the book highlights the breadth of research as well as its meaningful and relevant transfer into practice. It is intended for academics seeking inspiration, as well as for leaders wanting to tap the potential of the latest trends to take society and their business to the next level.

Trust is a fundamental concept in modern society. This book provides current findings of trust research from various disciplines: communication studies, information systems, educational and organizational psychology, sports psychology and economics. The volume analyses how trust relationships have changed and are still changing under the influence of digitalization. In addition to presenting the current state of research, the implications for trust relationships in the digital world are examined. The book brings together empirical findings with the implications for media, business, sports and science. It is of value to interdisciplinary researchers and graduate students.

Use this book to learn the Distributed Application Runtime (Dapr), a new event-driven runtime from Microsoft designed to help developers build microservices applications, using a palette of languages and frameworks that run everywhere: on-premises, in any cloud, and even on the edge. One of the most popular architectural patterns for implementing large, complex, distributed solutions is the microservices architectural style. Because solutions are composed of services based on various languages, frameworks, and platforms, the more complex and compartmentalized an application becomes, the more considerations a developer has to keep in mind. Much of the time this proves to be difficult. Introducing Distributed Application Runtime (Dapr) is your guide to achieving more with less through patterns. Part I of the book is about understanding microservices and getting up and running with Dapr, either on your machine or in any Kubernetes cluster. From there you are guided through the concepts of Dapr, how it works, and what it can do for you. You will wrap up with various ways to debug Dapr applications using Visual Studio Code locally, inside a container or Kubernetes. In Part II you will jump into the reusable patterns and practices, the building blocks of Dapr. You will go from service invocation, publish and subscribe, state management, resource bindings, and the Actor model to secrets; each building block is covered in detail in its own dedicated chapter. You will learn what Dapr offers from a functional perspective and also how you can leverage the three pillars of observability (logs, metrics, and traces) in order to gain insight into your applications. In Part III you will explore advanced concepts, including using middleware pipelines, integrating Dapr into web frameworks such as ASP.NET Core, or the runtimes of Azure Logic Apps and Azure Functions. The book features a multi-versed set of examples that cover not only the plain API of Dapr, but also the .NET SDK. Hence, most of the examples are in .NET 5, with a small number in JavaScript to exemplify the use of multiple languages. Examples show you how to securely use Dapr to leverage a variety of services in Microsoft Azure, including Azure Kubernetes Service, Azure Storage, Azure Service Bus, Azure Event Grid, Azure Key Vault, Azure Monitor, and Azure Active Directory among others. What You Will Learn Recognize the challenges and boundaries of microservices architecture Host Dapr inside a Kubernetes cluster or as a standalone process Leverage and use Dapr's ready-to-use patterns and practices Utilize its HTTP/gRPC APIs Use Dapr with ASP.NET Core and in .NET applications (with or without the SDK) Implement observability for Dapr applications Secure Dapr applications Integrate Dapr with the runtime of Azure Logic Apps and Azure Functions Realize the full potential of Visual Studio Code by using the right extensions that will contribute to a better development experience Who This Book Is For Developers and architects who want to utilize a proven set of patterns to help easily implement microservices applications

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. The book first discusses some fundamental big data problems and solutions in large scale distributed CPSs. The book then addresses the design and control challenges in multiple CPS domains such as vehicular system, smart city, smart building, and digital microfluidic biochips. This book also presents the recent advances and trends in the maritime simulation system and the flood defence system.

This volume presents selected papers from the International Conference on Urban Intelligence and Applications (ICUIA), which took place on May 10-12, 2019 in Wuhan, China. The goal of the conference was to bring together researchers, industry leaders, policy makers, and administrators to discuss emerging technologies and their applications to advance the design and implementation of intelligent utilization and management of urban assets, and thus contributing to the autonomous, reliable, and efficient operation of modern, smart cities. The papers are collated to address major themes of urban sustainability, urban infrastructure and management, smart city applications, image and signal processing, natural language processing, and machine learning for monitoring and communications applications. The book will be of interest to researchers and industrial practitioners working on geospatial theories and tools, smart city applications, urban mobility and transportation, and community well-being and management.

This book provides a comprehensive and effective exchange of information on current developments in the management of manufacturing systems and Industry 4.0. The book aims to establish channels of communication and disseminate knowledge among professionals working in manufacturing and related institutions. In the book, researchers, academicians and practitioners in relevant fields share their knowledge from the sectors of management of manufacturing systems. The chapters were selected from several conferences in the field, with the topics including management of manufacturing systems with support for Industry 4.0, logistics and intelligent manufacturing systems and applications, cooperation management, and its effective applications. The book also includes case studies in logistics, RFID applications, and economic impacts in logistics, ICT support for industry 4.0, industrial and smart logistics, intelligent manufacturing systems and applications

This textbook offers a comprehensive introduction to Machine Learning techniques and algorithms. This Third Edition covers newer approaches that have become highly topical, including deep learning, and auto-encoding, introductory information about temporal learning and hidden Markov models, and a much more detailed treatment of reinforcement learning. The book is written in an easy-to-understand manner with many examples and pictures, and with a lot of practical advice and discussions of simple applications. The main topics include Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, decision trees, rule-induction programs, artificial neural networks, support vector machines, boosting algorithms, unsupervised learning (including Kohonen networks and auto-encoding), deep learning, reinforcement learning, temporal learning (including long short-term memory), hidden Markov models, and the genetic algorithm. Special attention is devoted to performance evaluation, statistical assessment, and to many practical issues ranging from feature selection and feature construction to bias, context, multi-label domains, and the problem of imbalanced classes.

This book presents research in artificial techniques using intelligence for energy transition, outlining several applications including production systems, energy production, energy distribution, energy management, renewable energy production, cyber security, industry 4.0 and internet of things etc. The book goes beyond standard application by placing a specific focus on the use of AI techniques to address the challenges related to the different applications and topics of energy transition. The contributions are classified according to the market and actor interactions (service providers, manufacturers, customers, integrators, utilities etc.), to the SG architecture model (physical layer, infrastructure layer, and business layer), to the digital twin of SG (business model, operational model, fault/transient model, and asset model), and to the application domain (demand side management, load monitoring, micro grids, energy consulting (residents, utilities), energy saving, dynamic pricing revenue management and smart meters, etc.).