Systemanalyse og systemdesign

This book constitutes the refereed post-conference proceedings of the 7th Russian Supercomputing Days, RuSCDays 2021, held in Moscow, Russia, in September 2021.The 37 revised full papers and 3 short papers presented were carefully reviewed and selected from 99 submissions. The papers are organized in the following topical sections: supercomputer simulation; HPC, BigData, AI: architectures, technologies, tools; and distributed and cloud computing.

This book not only presents the state-of-the-art research on knowledge modelling, knowledge retrieval and knowledge reuse, but also elaborates the Collaborative Knowledge Management (CKM) paradigm and the architecture for the next generation of knowledge management systems. Although knowledge management has been extensively studied, particularly in the fields of business management and engineering design, there is a lack of systematic methodologies for addressing the integrated and collaborative dimension of knowledge management during the collaborative process of designing and developing complex systems, products, processes and services. The rapid development of information technologies, together with their applications in engineering and management, has laid the foundation for a Collaborative Knowledge Management (CKM) paradigm. The book specifically discusses this paradigm from a computational perspective.By exploring specific research findings underpinning further CKM research and applications and describing methods related to hot research topics and new research areas, the book appeals to professionals, researchers and graduate students who are interested in knowledge management and related topics and who have a basic understanding of information technologies, computational methods, and knowledge management.

Global surveys from McKinsey, BCG, Gartner, and others show that less than 30% of digital transformation programs succeed in their missions to improve a company¿s performance and employee productivity. This is due to the fact that IT efforts within the company do not center around the employee. This book will provide concrete steps to allow both IT professionals and business leaders to transform the way they deliver IT to employees ¿ with the employee (the human) centered in their transformation.The concepts, models, checklists, and playbook you'll review are based on the author's many years of experience, lessons learned, and proven outcomes. IT organizations want to improve their employee experience but don¿t know how and this is the ¿must have¿ book for those who don¿t know where to start. More than two-thirds of today¿s jobs require good digital and IT skills from employees. The expectations of management, who invest in these big digital transformations, is that the employees will become more productive, effective and help the bottom line. However, this can only happen through active and proactive change of IT operations and transformations that center the employee, rather than technology or senior management. This book reveals the benefit of moving towards an approach where employees gain technology aptitude, are up for technology change, and are willing to learn more for their benefit and even provide feedback on ways to improve these tools, trainings and support. You'll see how employee engagement and experience research, concepts, and implementations are growing rapidly across many organizations and taking a key role in their global strategies. Employee-centric IT will transform employees to own their digital literacy and development, and this in turn reduces or even eliminates the shadow IT need and allows the organization to drive and implement successful digital transformation.What You'll LearnUnderstand the value of being employee-centric in IT departments versus current modelsTake steps to win IT team¿s acceptance of the changes needed to achieve employee-centricityBe proactive in providing training & information on digital & productivity toolsWho This Book Is ForBusiness leaders, IT and digital leaders as well as IT employees who would like to transform their current IT and Digital teams to be more employee centric and drive highest level of value, adoption and satisfaction for their IT/digital programs, transformations and investment.

This volume constitutes selected papers presented at the First International Conference on Engineering Software for Modern Challenges, ESMoC 2021, held in Johor, Malaysia, in October 20-21, 2021.The 17 papers presented were thoroughly reviewed and selected from the 167 submissions. They are organized in the topical sections on software engineering; intelligent systems; software quality. 

This book discusses the newest approach to online learning systems in higher education. As e-learning platforms change their mechanisms for data processing and storage towards being more efficient and smarter, this book covers online learning systems and their application to large scaled data along with the technological aspects.

This book provides applications of machine learning in healthcare systems and seeks to close the gap between engineering and medicine by combining design and problem-solving skills of engineering with health sciences to advance healthcare treatment.Machine Learning and Artificial Intelligence in Healthcare Systems: Tools and Techniques discusses AI-based smart paradigms for reliable prediction of infectious disease dynamics; such paradigms can help prevent disease transmission. It highlights the different aspects of using extended reality for diverse healthcare applications and aggregates the current state of research. The book offers intelligent models of the smart recommender system for personal well-being services and computer-aided drug discovery and design methods. Case studies illustrating the business processes that underlie the use of big data and health analytics to improve healthcare delivery are center stage. Innovative techniques used for extracting user social behavior (known as sentiment analysis for healthcare-related purposes) round out the diverse array of topics this reference book covers.Contributions from experts in the field, this book is useful to healthcare professionals, researchers, and students of industrial engineering, systems engineering, biomedical, computer science, electronics, and communications engineering.

This book highlights various evolutionary algorithm techniques for various medical conditions and introduces medical applications of evolutionary computation for real-time diagnosis.Evolutionary Intelligence for Healthcare Applications presents how evolutionary intelligence can be used in smart healthcare systems involving big data analytics, mobile health, personalized medicine, and clinical trial data management. It focuses on emerging concepts and approaches and highlights various evolutionary algorithm techniques used for early disease diagnosis, prediction, and prognosis for medical conditions. The book also presents ethical issues and challenges that can occur within the healthcare system.Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

This four-volume set LNCS 13701-13704 constitutes contributions of the associated events held at the 11th International Symposium on Leveraging Applications of Formal Methods, ISoLA 2022, which took place in Rhodes, Greece, in October/November 2022. The contributions in the four-volume set are organized according to the following topical sections: specify this - bridging gaps between program specification paradigms; x-by-construction meets runtime verification; verification and validation of concurrent and distributed heterogeneous systems; programming - what is next: the role of documentation; automated software re-engineering; DIME day; rigorous engineering of collective adaptive systems; formal methods meet machine learning; digital twin engineering; digital thread in smart manufacturing; formal methods for distributed computing in future railway systems; industrial day.

This book constitutes the refereed post-conference proceedings of the Fifth IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2022, held in Amsterdam in October 2022.The 20 full papers presented were carefully reviewed and selected from 36 submissions. The papers are organized in the following topical sections: IoT for Smart Villages, Security and Safety, Smart Home, Development, Engineering, Machine Learning, and Applications.

Resilience Engineering (RE) studies have successfully identified and described many instances of resilient performance in high hazard sectors as well as in the far more frequent cases where people and organisations cope with the uncertainties of daily operations. Since RE was first described in 2006, a steady accumulation of insights and efforts have provided the basis for practical tools and methods. This development has been documented by a series of texts in the Resilience Engineering Perspectives series as well as by a growing number of papers and reports. This book encapsulates the essential practical lessons learned from the use of Resilience Engineering (RE) for over ten years. The main contents are a series of chapters written by those who have been instrumental in these applications. To increase the value for the reader, each chapter will include: rationale for the overall approach; data sought and reason(s) for choosing; data sources used, data analyses performed, and how recommendations were made and turned into practice.Serving as a reference for practitioners who want to analyse, support, and manage resilient performance, this book also advances research into RE by inquiring why work goes well in unpredictable environments, to improve work performance, or compensate for deficiencies.

This book constitutes refereed proceedings of the 7th China National Conference on Big Data and Social Computing, BDSC 2022, held in Hangzhou, China, from August 11-13, 2022The 24 full papers and 2 short papers presented in this volume were carefully reviewed and selected from a total of 99 submissions. The papers in the volume are organised according to the following topical headings: urban computing and social governance; artificial intelligence and cognitive science; social network and group behavior; digital society and public security; digital government and public big data

Emerging machine learning techniques bring new opportunities to flexible network control and management. This book focuses on using state-of-the-art machine learning-based approaches to improve the performance of Software-Defined Networking (SDN). It will apply several innovative machine learning methods (e.g., Deep Reinforcement Learning, Multi-Agent Reinforcement Learning, and Graph Neural Network) to traffic engineering and controller load balancing in software-defined wide area networks, as well as flow scheduling, coflow scheduling, and flow migration for network function virtualization in software-defined data center networks. It helps readers reflect on several practical problems of deploying SDN and learn how to solve the problems by taking advantage of existing machine learning techniques. The book elaborates on the formulation of each problem, explains design details for each scheme, and provides solutions by running mathematical optimization processes, conducting simulated experiments, and analyzing the experimental results.