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Systems Analysis and Synthesis: Bridging Computer Science and Information Technology presents several new graph-theoretical methods that relate system design to core computer science concepts, and enable correct systems to be synthesized from specifications. Based on material refined in the author’s university courses, the book has immediate applicability for working system engineers or recent graduates who understand computer technology, but have the unfamiliar task of applying their knowledge to a real business problem. Starting with a comparison of synthesis and analysis, the book explains the fundamental building blocks of systems-atoms and events-and takes a graph-theoretical approach to database design to encourage a well-designed schema. The author explains how database systems work-useful both when working with a commercial database management system and when hand-crafting data structures-and how events control the way data flows through a system. Later chapters deal with system dynamics and modelling, rule-based systems, user psychology, and project management, to round out readers’ ability to understand and solve business problems. Bridges computer science theory with practical business problems to lead readers from requirements to a working system without error or backtracking Explains use-definition analysis to derive process graphs and avoid large-scale designs that don’t quite work Demonstrates functional dependency graphs to allow databases to be designed without painful iteration Includes chapters on system dynamics and modeling, rule-based systems, user psychology, and project management

System analysis. --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization

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Network science has accelerated a deep and successful trend in research that influences a range of disciplines like mathematics, graph theory, physics, statistics, data science and computer science (just to name a few) and adapts the relevant techniques and insights to address relevant but disparate social, biological, technological questions. We are now in an era of ‘big biological data' supported by cost-effective high-throughput genomic, transcriptomic, proteomic, metabolomic data collection techniques that allow one to take snapshots of the cells' molecular profiles in a systematic fashion. Moreover recently, also phenotypic data, data on diseases, symptoms, patients, etc. are being collected at nation-wide level thus giving us another source of highly related (causal) 'big data'. This wealth of data is usually modeled as networks (aka binary relations, graphs or webs) of interactions, (including protein–protein, metabolic, signaling and transcription-regulatory interactions). The network model is a key view point leading to the uncovering of mesoscale phenomena, thus providing an essential bridge between the observable phenotypes and 'omics' underlying mechanisms. Moreover, network analysis is a powerful 'hypothesis generation' tool guiding the scientific cycle of 'data gathering', 'data interpretation, 'hypothesis generation' and 'hypothesis testing’. A major challenge in contemporary research is the synthesis of deep insights coming from network science with the wealth of data (often noisy, contradictory, incomplete and difficult to replicate) so to answer meaningful biological questions, in a quantifiable way using static and dynamic properties of biological networks.

systems biology --- network science --- network biology --- cancer networks --- hypothesis generation and verification --- computational biology

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In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation;methods for low-rank

System analysis. --- Analyse de systèmes --- System Analysis --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization

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Control and Dynamic Systems V52: Integrated Technology Methods and Applications in Aerospace Systems Design

System analysis. --- Airplanes --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization --- Design and construction.

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This book is divided into four parts. The first part, Preliminaries, begins by introducing the basic theme of the book. It provides an overview of the current status of water resources utilization, the likely scenario of future demands, and advantages and disadvantages of systems techniques. An understanding of how the hydrological data are measured and processed is important before undertaking any analysis. The discussion is extended to emerging techniques, such as Remote Sensing, GIS, Artificial Neural Networks, and Expert Systems.

Water resources development --- System analysis. --- Network analysis --- Network science --- Network theory --- Systems analysis --- System theory --- Mathematical optimization --- Planning.