Large Scale Complex It Systems Development Operation And Management

This book presents the thoroughly refereed and revised post-workshop proceedings of the 17th Monterey Workshop, held in Oxford, UK, in March 2012. The workshop explored the challenges associated with the Development, Operation and Management of Large-Scale complex IT Systems. The 21 revised full papers presented were significantly extended and improved by the insights gained from the productive and lively discussions at the workshop, and the feedback from the post-workshop peer reviews.

This book presents recent research on the hybridization of intelligent methods, which refers to combining methods to solve complex problems. It discusses hybrid approaches covering different areas of intelligent methods and technologies, such as neural networks, swarm intelligence, machine learning, reinforcement learning, deep learning, agent-based approaches, knowledge-based system and image processing. The book includes extended and revised versions of invited papers presented at the 6th International Workshop on Combinations of Intelligent Methods and Applications (CIMA 2016), held in The Hague, Holland, in August 2016. The book is intended for researchers and practitioners from academia and industry interested in using hybrid methods for solving complex problems.

This book is a pioneering yet primary general reference resource on cyber physical systems and their security concerns. Providing a fundamental theoretical background, and a clear and comprehensive overview of security issues in the domain of cyber physical systems, it is useful for students in the fields of information technology, computer science, or computer engineering where this topic is a substantial emerging area of study.

Internet and World Wide Web platforms, big data analytics, software, social media and civic technologies allow for the creation of smart ecosystems in which connected intelligence emerges and disruptive social and eco-innovation flourishes. This book focuses on three grand challenges that matter for any territory, no matter where it is located: (i) smart growth, a path that more and more cities, regions and countries are adopting having realised the unlimited potential of growth that is based on knowledge, innovation and digital technologies; (ii) safety and security, which is a pre-requisite for quality of life in a world of intense social, natural and technological threats; and (iii) sustainability, use of renewable energy, protection of living ecosystems, addressing climate change and global warming in a period of rapid urbanisation that makes established sustainability models and planning patterns quickly obsolete. The core argument of the book is that problem-solving and novel solutions to these grand challenges emerge in smart ecosystems through connected intelligence. It is the broadest form of intelligence that combines capabilities from heterogeneous actors (humans, organisations, machines) and propel problem-solving through externalities and resource agglomeration, user engagement and collaboration, awareness and behaviour change. This book will be of interest to students and researchers of urban and regional studies, innovation studies, economic geography and urban planning, as well as urban policy makers.

The concept of concurrent engineering (CE) was first developed in the 1980s. Now often referred to as transdiciplinary engineering, it is based on the idea that different phases of a product life cycle should be conducted concurrently and initiated as early as possible within the Product Creation Process (PCP). The main goal of CE is to increase the efficiency and effectiveness of the PCP and reduce errors in later phases, as well as incorporating considerations – including environmental implications – for the full lifecycle of the product. It has become a substantive methodology in many industries, and has also been adopted in the development of new services and service support. This book presents the proceedings of the 25th ISPE Inc. International Conference on Transdisciplinary Engineering, held in Modena, Italy, in July 2018. This international conference attracts researchers, industry experts, students, and government representatives interested in recent transdisciplinary engineering research, advancements and applications. The book contains 120 peer-reviewed papers, selected from 259 submissions from all continents of the world, ranging from the theoretical and conceptual to papers addressing industrial best practice, and is divided into 11 sections reflecting the themes addressed in the conference program and addressing topics as diverse as industry 4.0 and smart manufacturing; human-centered design; modeling, simulation and virtual design; and knowledge and data management among others. With an overview of the latest research results, product creation processes and related methodologies, this book will be of interest to researchers, design practitioners and educators alike.

This innovative textbook presents material for a course on industrial statistics that incorporates Python as a pedagogical and practical resource. Drawing on many years of teaching and conducting research in various applied and industrial settings, the authors have carefully tailored the text to provide an ideal balance of theory and practical applications. Numerous examples and case studies are incorporated throughout, and comprehensive Python applications are illustrated in detail. A custom Python package is available for download, allowing students to reproduce these examples and explore others. The first chapters of the text focus on the basic tools and principles of process control, methods of statistical process control (SPC), and multivariate SPC. Next, the authors explore the design and analysis of experiments, quality control and the Quality by Design approach, computer experiments, and cyber manufacturing and digital twins. The text then goes on to cover reliability analysis, accelerated life testing, and Bayesian reliability estimation and prediction. A final chapter considers sampling techniques and measures of inspection effectiveness. Each chapter includes exercises, data sets, and applications to supplement learning. Industrial Statistics: A Computer-Based Approach with Python is intended for a one- or two-semester advanced undergraduate or graduate course. In addition, it can be used in focused workshops combining theory, applications, and Python implementations. Researchers, practitioners, and data scientists will also find it to be a useful resource with the numerous applications and case studies that are included. A second, closely related textbook is titled Modern Statistics: A Computer-Based Approach with Python. It covers topics such as probability models and distribution functions, statistical inference and bootstrapping, time series analysis and predictions, and supervised and unsupervised learning. These texts can be used independently or for consecutive courses. The mistat Python package can be accessed at https://gedeck.github.io/mistat-code-solutions/IndustrialStatistics/. "This book is part of an impressive and extensive write up enterprise (roughly 1,000 pages!) which led to two books published by Birkhäuser. This book is on Industrial Statistics, an area in which the authors are recognized as major experts. The book combines classical methods (never to be forgotten!) and "hot topics" like cyber manufacturing, digital twins, A/B testing and Bayesian reliability. It is written in a very accessible style, focusing not only on HOW the methods are used, but also on WHY. In particular, the use of Python, throughout the book is highly appreciated. Python is probably the most important programming language used in modern analytics. The authors are warmly thanked for providing such a state-of-the-art book. It provides a comprehensive illustration of methods and examples based on the authors longstanding experience, and accessible code for learning and reusing in classrooms and on-site applications." Professor Fabrizio RuggeriResearch Director at the National Research Council, ItalyPresident of the International Society for Business and Industrial Statistics (ISBIS)Editor-in-Chief of Applied Stochastic Models in Business and Industry (ASMBI)

This book explores a wide range of topics in digital ethics. It features 11 chapters that analyze the opportunities and the ethical challenges posed by digital innovation, delineate new approaches to solve them, and offer concrete guidance to harness the potential for good of digital technologies. The contributors are all members of the Digital Ethics Lab (the DELab), a research environment that draws on a wide range of academic traditions. The chapters highlight the inherently multidisciplinary nature of the subject, which cannot be separated from the epistemological foundations of the technologies themselves or the political implications of the requisite reforms. Coverage illustrates the importance of expert knowledge in the project of designing new reforms and political systems for the digital age. The contributions also show how this task requires a deep self-understanding of who we are as individuals and as a species. The questions raised here have ancient -- perhaps even timeless -- roots. The phenomena they address may be new. But, the contributors examine the fundamental concepts that undergird them: good and evil, justice and truth. Indeed, every epoch has its great challenges. The role of philosophy must be to redefine the meaning of these concepts in light of the particular challenges it faces. This is true also for the digital age. This book takes an important step towards redefining and re-implementing fundamental ethical concepts to this new era.