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How do we interact with people in our everyday life? Who are the people we are connected to? What are the consequences of overlapping social circles and how people deal with the potential emerging conflicts? What are the structural and cultural mechanisms that regulate social worlds? Network science is a scientific approach to the study of network dependencies and associations which tries to answer these and many other questions. This book explores the underlying mechanisms that regulate social life as they are produced, reproduced, modified, and abandoned in the spatial and temporal patterns of interactions. The mixed methods approach, that combines formal network analysis with qualitative materials and statistical tools, shows the importance of contextualising structural mechanisms in their social and cultural environment, and allows overcoming the traditional methodological boundaries that shape the field of social sciences.
"Analyzes the behavior, design, and implementation of artificial recurrent neural networks. Offers methods of synthesis for associative memories. Evaluates the qualitative properties and limitations of neural networks. Contains practical applications for optimal system performance."
This book is devoted to some mathematical methods that arise in two domains of artificial intelligence: neural networks and qualitative physics. Professor Aubin makes use of control and viability theory in neural networks and cognitive systems, regarded as dynamical systems controlled by synaptic matrices, and set-valued analysis that plays a natural and crucial role in qualitative analysis and simulation. This allows many examples of neural networks to be presented in a unified way. In addition, several results on the control of linear and nonlinear systems are used to obtain a "learning algorithm" of pattern classification problems, such as the back-propagation formula, as well as learning algorithms of feedback regulation laws of solutions to control systems subject to state constraints.
This book focuses on the stability of the dynamical neural system, synchronization of the coupling neural system and their applications in automation control and electrical engineering. The redefined concept of stability, synchronization and consensus are adopted to provide a better explanation of the complex neural network. Researchers in the fields of dynamical systems, computer science, electrical engineering and mathematics will benefit from the discussions on complex systems. The book will also help readers to better understand the theory behind the control technique and its design.
Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measures provides a clear and consolidated view of current social network models. This work explores new methods for modeling, characterizing, and constructing social networks. Chapters contained in this book study critical security issues confronting social networking, the emergence of new mobile social networking devices and applications, network robustness, and how social networks impact the business aspects of organizations.
Using qualitative methods to deal with imperfect information.
Starting with an updated description of Allen's calculus, the book proceeds with a description of the main qualitative calculi which have been developed over the last two decades. It describes the connection of complexity issues to geometric properties. Models of the formalisms are described using the algebraic notion of weak representations of the associated algebras. The book also includes a presentation of fuzzy extensions of qualitative calculi, and a description of the study of complexity in terms of clones of operations.
This handbook provides a comprehensive overview of state-of-the-art, innovative approaches to qualitative research for organizational scholars. Individual chapters in each area are written by experts in a variety of fields, who have contributed some of the most innovative studies themselves in recent years. An indispensable reference guide to anyone conducting high-impact organizational research, this handbook includes innovative approaches to research problems, data collection, data analysis and interpretation, and application of research findings. The book will be of interest to scholars and graduate students in a wide variety of disciplines, including anthropology, organizational behavior, organizational theory, social psychology, and sociology
An essential companion for students across the social and health sciences, this text provides a wide-ranging coverage of qualitative methods complemented by extended illustration from the array of academic disciplines in which qualitative research is found and employed. Written in a lively and reader-friendly style, the guide covers a comprehensive range of topics, including: - a concise definition of the method - a description of distinctive features - examples to convey the flavour of a technique or principle - a critical and reflective evaluation of the method or approach under consideration - cross references to associated concepts within the dictionary - a list of key readings
In Doing Good Qualitative Research, Jennifer Cyr and Sara Wallace Goodman bring together over forty experts to provide one of the first comprehensive introductions to using qualitative methods across the social sciences, from start to finish. Each chapter introduces the theoretical considerations and best practices involved in the application of qualitative data collection and analysis. Additionally, contributors provide first-person accounts of methodology in action, address the expected and unexpected challenges associated with conducting qualitative research, and demonstrate the real-world applications of academic debates.