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L'analyse des systèmes techniques fait surgir des difficultés redoutables pour toutes les sciences sociales. Une mise en perspective s'impose à l'analyste, en fonction des diverses sociétés, en raison de la connotation du terme dans les sociétés modernes. L'analyse de tout système technique ne peut se dispenser d'une description minutieuse où le langage joue un rôle prépondérant, pour le saisir en tant que totalité sociale. The analysis of technical systems is giving rise to considerable dangers in the field of all social sciences. Analysts are faced with the obligation to study them in perspective, taking account of the variety of societies in view of the connotations of the term in modern societies. The analysis of any technical system cannot leave aside a scrupulous and detailed description, in which language is playing a leading part, so that it can be fully understood as representing a whole social entity.
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Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
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The papers contained in this volume were originally presented at the 2015 International Conference on Complex Systems in Business, Administration, Science and Engineering. Included are the latest works of practitioners from a variety of disciplines who have developed new approaches for resolving complex issues.
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This book is an introduction to the language of systems biology, which is spoken among many disciplines, from biology to engineering. Authors Thomas Sauter and Marco Albrecht draw on a multidisciplinary background and evidence-based learning to facilitate the understanding of biochemical networks, metabolic modeling and system dynamics. Their pedagogic approach briefly highlights core ideas of concepts in a broader interdisciplinary framework to guide a more effective deep dive thereafter. The learning journey starts with the purity of mathematical concepts, reveals its power to connect biological entities in structure and time, and finally introduces physics concepts to tightly align abstraction with reality. This workbook is all about self-paced learning, supports the flipped-classroom concept, and kick-starts with scientific evidence on studying. Each chapter comes with links to external YouTube videos, learning checklists, and Integrated real-world examples to gain confidence in thinking across scientific perspectives. The result is an integrated approach that opens a line of communication between theory and application, enabling readers to actively learn as they read. This overview of capturing and analyzing the behavior of biological systems will interest adherers of systems biology and network analysis, as well as related fields such as bioinformatics, biology, cybernetics, and data science.
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There has been recently some interdisciplinary convergence on a number of precise topics which can be considered as prototypes of complex systems. This convergence is best appreciated at the level of the techniques needed to deal with these systems, which include: 1) A domain of research around a multiple point where statistical physics, information theory, algorithmic computer science, and more theoretical (probabilistic) computer science meet: this covers some aspects of error correcting codes, stochastic optimization algorithms, typical case complexity and phase transitions, constr
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System science and engineering is a field that covers a wide spectrum of modern technology. A system can be seen as a collection of entities and their interrelationships, which forms a whole greater than the sum of the entities and interacts with people, organisations, cultures and activities and the interrelationships among them. Systems composed of autonomous subsystems are not new, but the increased complexity of modern technology demands ever more reliable, intelligent, robust and adaptable systems to meet evolving needs. This book presents papers delivered at the International Conference
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Qualitative analysis of large scale dynamical systems
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This volume in the AMIS series presents the very latest, state-of-the-art research in the area of systems analysis and design, focusing on the personal and socio technical aspects. Chapters are grouped into three categories: people and social systems, socio technical aspects, and project teams.
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