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Dehmer Matthias Analysis of Complex Networks. From Biology to Linguistics


Mathematical problems such as graph theory problems are of increasing importance for the analysis of modelling data in biomedical research such as in systems biology, neuronal network modelling etc. This book follows a new approach of including graph theory from a mathematical perspective with specific applications of graph theory in biomedical and computational sciences. The book is written by renowned experts in the field and offers valuable background information for a wide audience.

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Matthias Dehmer Analysis of Microarray Data


This book is the first to focus on the application of mathematical networks for analyzing microarray data. This method goes well beyond the standard clustering methods traditionally used. From the contents: * Understanding and Preprocessing Microarray Data * Clustering of Microarray Data * Reconstruction of the Yeast Cell Cycle by Partial Correlations of Higher Order * Bilayer Verification Algorithm * Probabilistic Boolean Networks as Models for Gene Regulation * Estimating Transcriptional Regulatory Networks by a Bayesian Network * Analysis of Therapeutic Compound Effects * Statistical Methods for Inference of Genetic Networks and Regulatory Modules * Identification of Genetic Networks by Structural Equations * Predicting Functional Modules Using Microarray and Protein Interaction Data * Integrating Results from Literature Mining and Microarray Experiments to Infer Gene Networks The book is for both, scientists using the technique as well as those developing new analysis techniques.

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Dehmer Matthias Statistical and Machine Learning Approaches for Network Analysis


Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationally renowned researchers in the field of interdisciplinary network theory, the book presents current and classical methods to analyze networks statistically. Methods from machine learning, data mining, and information theory are strongly emphasized throughout. Real data sets are used to showcase the discussed methods and topics, which include: A survey of computational approaches to reconstruct and partition biological networks An introduction to complex networks—measures, statistical properties, and models Modeling for evolving biological networks The structure of an evolving random bipartite graph Density-based enumeration in structured data Hyponym extraction employing a weighted graph kernel Statistical and Machine Learning Approaches for Network Analysis is an excellent supplemental text for graduate-level, cross-disciplinary courses in applied discrete mathematics, bioinformatics, pattern recognition, and computer science. The book is also a valuable reference for researchers and practitioners in the fields of applied discrete mathematics, machine learning, data mining, and biostatistics.

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Matthias Dehmer Medical Biostatistics for Complex Diseases


A collection of highly valuable statistical and computational approaches designed for developing powerful methods to analyze large-scale high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the major health challenges in industrialized countries. They are characterized by the systems properties of gene networks and their interrelations, instead of individual genes, whose malfunctioning manifests in pathological phenotypes, thus making the analysis of the resulting large data sets particularly challenging. This is why novel approaches are needed to tackle this problem efficiently on a systems level. Written by computational biologists and biostatisticians, this book is an invaluable resource for a large number of researchers working on basic but also applied aspects of biomedical data analysis emphasizing the pathway level.

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Guanrong Chen Fundamentals of Complex Networks


Complex networks such as the Internet, WWW, transportation networks, power grids, biological neural networks, and scientific cooperation networks of all kinds provide challenges for future technological development. • The first systematic presentation of dynamical evolving networks, with many up-to-date applications and homework projects to enhance study • The authors are all very active and well-known in the rapidly evolving field of complex networks • Complex networks are becoming an increasingly important area of research • Presented in a logical, constructive style, from basic through to complex, examining algorithms, through to construct networks and research challenges of the future

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Xinchu Fu Propagation Dynamics on Complex Networks


Explores the emerging subject of epidemic dynamics on complex networks, including theories, methods, and real-world applications Throughout history epidemic diseases have presented a serious threat to human life, and in recent years the spread of infectious diseases such as dengue, malaria, HIV, and SARS has captured global attention; and in the modern technological age, the proliferation of virus attacks on the Internet highlights the emergent need for knowledge about modeling, analysis, and control in epidemic dynamics on complex networks. For advancement of techniques, it has become clear that more fundamental knowledge will be needed in mathematical and numerical context about how epidemic dynamical networks can be modelled, analyzed, and controlled. This book explores recent progress in these topics and looks at issues relating to various epidemic systems. Propagation Dynamics on Complex Networks covers most key topics in the field, and will provide a valuable resource for graduate students and researchers interested in network science and dynamical systems, and related interdisciplinary fields. Key Features: Includes a brief history of mathematical epidemiology and epidemic modeling on complex networks. Explores how information, opinion, and rumor spread via the Internet and social networks. Presents plausible models for propagation of SARS and avian influenza outbreaks, providing a reality check for otherwise abstract mathematical modeling. Considers various infectivity functions, including constant, piecewise-linear, saturated, and nonlinear cases. Examines information transmission on complex networks, and investigates the difference between information and epidemic spreading.

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Feuillet Mathieu Network Performance Analysis


The book presents some key mathematical tools for the performance analysis of communication networks and computer systems. Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service. This book introduces the main results of queuing theory that are useful for analyzing the performance of these systems. These mathematical tools are key to the development of robust dimensioning rules and engineering methods. A number of examples illustrate their practical interest.

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Falk Schreiber Analysis of Biological Networks


An introduction to biological networks and methods for their analysis Analysis of Biological Networks is the first book of its kind to provide readers with a comprehensive introduction to the structural analysis of biological networks at the interface of biology and computer science. The book begins with a brief overview of biological networks and graph theory/graph algorithms and goes on to explore: global network properties, network centralities, network motifs, network clustering, Petri nets, signal transduction and gene regulation networks, protein interaction networks, metabolic networks, phylogenetic networks, ecological networks, and correlation networks. Analysis of Biological Networks is a self-contained introduction to this important research topic, assumes no expert knowledge in computer science or biology, and is accessible to professionals and students alike. Each chapter concludes with a summary of main points and with exercises for readers to test their understanding of the material presented. Additionally, an FTP site with links to author-provided data for the book is available for deeper study. This book is suitable as a resource for researchers in computer science, biology, bioinformatics, advanced biochemistry, and the life sciences, and also serves as an ideal reference text for graduate-level courses in bioinformatics and biological research.

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Akira Hirose Complex-Valued Neural Networks. Advances and Applications


Presents the latest advances in complex-valued neural networks by demonstrating the theory in a wide range of applications Complex-valued neural networks is a rapidly developing neural network framework that utilizes complex arithmetic, exhibiting specific characteristics in its learning, self-organizing, and processing dynamics. They are highly suitable for processing complex amplitude, composed of amplitude and phase, which is one of the core concepts in physical systems to deal with electromagnetic, light, sonic/ultrasonic waves as well as quantum waves, namely, electron and superconducting waves. This fact is a critical advantage in practical applications in diverse fields of engineering, where signals are routinely analyzed and processed in time/space, frequency, and phase domains. Complex-Valued Neural Networks: Advances and Applications covers cutting-edge topics and applications surrounding this timely subject. Demonstrating advanced theories with a wide range of applications, including communication systems, image processing systems, and brain-computer interfaces, this text offers comprehensive coverage of: Conventional complex-valued neural networks Quaternionic neural networks Clifford-algebraic neural networks Presented by international experts in the field, Complex-Valued Neural Networks: Advances and Applications is ideal for advanced-level computational intelligence theorists, electromagnetic theorists, and mathematicians interested in computational intelligence, artificial intelligence, machine learning theories, and algorithms.

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Jeremiah Hayes F. Modeling and Analysis of Telecommunications Networks


This book covers at an advanced level mathematical methods for analysis of telecommunication networks. The book concentrates on various call models used in telecommunications such as quality of service (QoS) in packet-switched Internet Protocol (IP) networks, Asynchronous Transfer Mode (ATM), and Time Division Multiplexing (TDM). Professionals, researchers, and graduate and advanced undergraduate students of telecommunications will benefit from this invaluable guidebook.

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Analysis of Complex Networks: From Biology to Linguistics ...

Analysis of Complex Networks: From Biology to Linguistics (Quantitative and Network Biology) | Dehmer, Matthias, Emmert-Streib, Frank | ISBN: 9783527323456 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

Structural Analysis of Complex Networks | Matthias Dehmer ...

Editors: Dehmer, Matthias (Ed.) Free Preview. Real-world applications; Demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems ; For a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems ...

Strukturelle Analyse Web-basierter Dokumente | Matthias ...

Matthias Dehmer rückt das Web Structure Mining, insbesondere die strukturelle Analyse Web-basierter Hypertexte auf Grundlage gerichteter Graphen, in den Mittelpunkt seiner Untersuchung. Der Autor stellt ein graphentheoretisches Modell zur Bestimmung der strukturellen Ähnlichkeit einer Klasse von gerichteten Graphen vor. Auf Basis des angesprochenen Modells führt er Experimente mit ...

Research » Matthias Dehmer

Network Analysis Some Collaborators. Prof. Dr. Danail Bonchev Virginia Commonwealth University, Center for the Study of Biological Complexity, USA

Publications » Matthias Dehmer

Dehmer M., Emmert-Streib F., Graber A., Salvador A. Wiley-VCH, 2011: 15 Link Bib: Structural Analysis of Complex Networks Dehmer M. Birkhäuser Publishing, 2010: 16 Link Bib: Medical Biostatistics for Complex Diseases Emmert-Streib F., Dehmer M. Wiley-VCH Publishing, 2010: 17 Link Bib: Analysis of Complex Networks: From Biology to Linguistics

Structural Analysis of Complex Networks: Dehmer, Matthias ...

by Matthias Dehmer (Editor) ISBN-13: 978-0817647889. ISBN-10: 0817647880. Why is ISBN important? ISBN ... Structural Analysis of Complex Networks is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive ...

Teaching » Matthias Dehmer

Lecturer of the course ’Structural Analysis of Networks: Theory and Applications’ Postgraduate level, Vienna University of Technology, Austria. 2007/2008. winter. Tutor in Mathematics, ’Mathematik für Bauingenieure’ Undergraduate level, Vienna University of Technology, Austria. 2006/2007. winter

Students » Matthias Dehmer

June 2013 - Larissa Schulz, UMIT. Topic: Programming paradigms and Biomedical Data Analysis, First supervisor. Apr. 2009 - May 2011. Karl Kugler, UMIT. Topic: Integrative Analysis of Biological and Medical Data by Means of Data Warehousing, Meta-Analysis, and Network-Based Approaches, First supervisor Apr. 2009 -

‪Matthias Dehmer‬ - ‪Google Scholar‬

Matthias Dehmer. Swiss Distance University of Applied Sciences, UMIT, Hall, Tyrol, Austria, Nankai University. Bestätigte E-Mail-Adresse bei ffhs.ch . Data Science Big Data Analytics Bioinformatics Complex Networks. Artikel Zitiert von Koautoren. Titel. Sortieren. Nach Zitationen sortieren Nach Jahr sortieren Nach Titel sortieren. Zitiert von. Zitiert von. Jahr; A history of graph entropy ...

Frontiers in Data Science - 1st Edition - Matthias Dehmer ...

Matthias Dehmer studied mathematics at the University of Siegen (Germany) and received his Ph.D. in computer science from the Technical University of Darmstadt (Germany). Afterwards, he was a research fellow at Vienna Bio Center (Austria), Vienna University of Technology, and University of Coimbra (Portugal). He obtained his habilitation in applied discrete mathematics from the Vienna ...

Matthias Dehmer - download.e-bookshelf.de

Matthias Dehmer Editor Structural Analysis of Complex Networks. Editor Ao. Prof. Dr. habil. Matthias Dehmer Institute for Bioinformatics and Translational Research The Health and Life Sciences University UMIT-Private Universit¨at f¨ur Gesundheitswissenschaften Eduard Walln¨ofer-Zentrum 1 A-6060 Hall in Tirol, Austria and Institute of Discrete Mathematics and Geometry Vienna University of ...

Structural Analysis of Complex Networks: Amazon.de: Dehmer ...

Structural Analysis of Complex Networks | Dehmer, Matthias | ISBN: 9780817647889 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

Matthias Dehmer: Mathematical Foundations of Data Science ...

Matthias Dehmer studied mathematics at the University of Siegen (Germany) and received his PhD in computer science from the Technical University of Darmstadt (Germany). Afterwards, he was a research fellow at Vienna Bio Center (Austria), Vienna University of Technology and University of Coimbra (Portugal). Currently, he is Professor at UMIT - The Health and Life Sciences University (Austria ...

Strukturelle Analyse Web-basierter Dokumente von Matthias ...

Matthias Dehmer rückt das Web Structure Mining, insbesondere die strukturelle Analyse Web-basierter Hypertexte auf Grundlage gerichteter Graphen, in den Mittelpunkt seiner Untersuchung. Der Autor stellt ein graphentheoretisches Modell zur Bestimmung der strukturellen Ähnlichkeit einer Klasse von gerichteten Graphen vor. Auf Basis des angesprochenen Modells führt er Experimente mit ...

Strukturelle Analyse Web-basierter Dokumente (Multimedia ...

Strukturelle Analyse Web-basierter Dokumente (Multimedia und Telekooperation) (German Edition) | Dehmer, Matthias | ISBN: 9783835003088 | Kostenloser Versand für alle Bücher mit Versand und Verkauf duch Amazon.

Analysis of Complex Networks : Matthias Dehmer : 9783527323456

Analysis of Complex Networks by Matthias Dehmer, 9783527323456, available at Book Depository with free delivery worldwide.

Structural Analysis of Complex Networks: Dehmer, Matthias ...

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Matthias Dehmer - Deutsche Digitale Bibliothek

Analysis of complex networks : from biology to linguistics Dehmer, Matthias Computational network analysis with R : applications in biology, medicine, and chemistry Dehmer, Matthias Strukturelle Analyse Web-basierter Dokumente Dehmer, Matthias Strukturelle Analyse web-basierter Dokumente Dehmer, Matthias Alle Objekte (11)

Strukturelle analyse Web-basierter dokumente, Paperback by ...

Strukturelle analyse Web-basierter dokumente, Paperback by Dehmer, Matthias, ISBN 3835003089, ISBN-13 9783835003088, Brand New, Free shipping in the US<br><br>Matthias Dehmer rückt das Web Structure Mining, insbesondere die strukturelle Analyse Web-basierter Hypertexte auf Grundlage gerichteter Graphen, in den Mittelpunkt seiner Untersuchung. Der Autor stellt ein graphentheoretisches Modell ...

Matthias Dehmer – Technical Project Manager – MSC Software ...

Sehen Sie sich das Profil von Matthias Dehmer im größten Business-Netzwerk der Welt an. Im Profil von Matthias Dehmer sind 5 Jobs angegeben. Auf LinkedIn können Sie sich das vollständige Profil ansehen und mehr über die Kontakte von Matthias Dehmer und Jobs bei ähnlichen Unternehmen erfahren.

EPDA - Dissertationen: Dehmer, Matthias

Dehmer, Matthias ; Titel: Strukturelle Analyse Web-basierter Dokumente Dissertation: TU Darmstadt, Fachbereich Informatik, 2005 Die Dokumente in PDF 1.3 (mit Adobe Acrobat Reader 4.0 zu lesen): diss_dehmer.pdf (1562166: Byte) Abstract auf Deutsch: Im Zuge der web-basierten Kommunikation und in Anbetracht der gigantischen Datenmengen, die im World Wide Web verfügbar sind, erlangt das so ...

Quantitative Graph Theory: Mathematical Foundations and ...

Matthias Dehmer studied mathematics and computer science at the University of Siegen, Germany, and earned his Ph.D in computer science from the Darmstadt University of Technology. He held research positions at the University of Rostock (Germany), Vienna Bio Center (Austria), Vienna Technical University (Austria), and University of Coimbra (Portugal), and obtained his habilitation in applied ...

Matthias DEHMER | TU Wien, Vienna | TU Wien | Institute of ...

Matthias DEHMER of TU Wien, Vienna (TU Wien) | Read 276 publications | Contact Matthias DEHMER

Big Data of Complex Networks - 1st Edition - Matthias ...

Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory.

JuLib | Books & more - Dehmer, Matthias

Computational network analysis with R : applications in biology, medicine, and chemistry [E-Book] / Dehmer, Matthias 2017 Other Authors: '; “... Dehmer, Matthias... ” Full Text. QR Code. Add to Favourites. Saved in: 3 . E-Book. Computational network theory : theoretical foundations and applications [E-Book] / ...

Wiley: Applied Statistics for Network Biology: Methods in ...

Network Analysis to Interpret Complex Phenotypes (Hong Yu, Jialiang Huang, Wei Zhang, and Jing-Dong J. Han) ... Matthias Dehmer studied mathematics at the University of Siegen, Germany and received his PhD in computer science from the Technical University of Darmstadt. He began his academic career as a research fellow at Vienna Bio Center, Austria, and at Vienna University of Technology, and ...

Matthias Dehmer - GBV

Matthias Dehmer Editor Structural Analysis of Complex Networks Birkhäuser . Contents Preface v Contributors xi 1 A Brief Introduction to Complex Networks and Their Analysis 1 Frank Emmert-Streib 2 Partitions of Graphs 27 Mieczyslaw Borowiecki 3 Distance in Graphs 49 Wayne Goddard and Ortrud R. Oellermann 4 Domination in Graphs 73 Nawarat Ananchuen, Watcharaphong Ananchuen, and Michael D ...

Blättern nach Person - TUbiblio

Borgert, Stephan; Dehmer, Matthias; Aitenbichler, Erwin (2009): A comparative study of Complexity Measures to analyze Business Process Models. In: Proceedings of the International Symposium on Understanding Intelligent and Complex Systems, UICS 2009, S. 1 - 8,

Books by Matthias Dehmer on Google Play

Matthias Dehmer, Abbe Mowshowitz, and Frank Emmert-Streib, well-known pioneers in the fi eld, have edited this volume with a view to balancing classical and modern approaches to ensure broad coverage of contemporary research problems. The book is a valuable addition to the literature and a must-have for anyone dealing with network compleaity and complexity issues. $100.00. Statistical ...

Scope Analysis GmbH

Scope Analysis ist das führende europäische Unternehmen zur Bewertung von Fonds und Asset Managern. Neben klassischen Rating-Aktivitäten unterstützen die Scope Analysten institutionelle Investoren auch direkt bei der Auswahl und Selektion von Fonds und Asset Managern.

Structural Analysis of Complex Networks: Dehmer, Matthias ...

Structural Analysis of Complex Networks: Dehmer, Matthias: 9780817647889: Books - Amazon.ca. Skip to main content.ca. Hello Select your address Books Hello, Sign in. Account & Lists Account Returns & Orders. Cart All. Best Sellers Gift Ideas Prime New Releases ...

Matthias Dehmer - download.e-bookshelf.de

Matthias Dehmer V . Zusammenfassung Im Zuge der web-basierten Kommunikation und in Anbetracht der gigantischen Datenmengen, die im World Wide Web (kurz: Web) verfiigbar sind, erlangt das so genannte Web Mining eine immer stiirkere Bedeutung. Ziel des Web Mining ist die Informationsgewinnung und Analyse web-basierter Daten auf der Grundlage von Data Mining-Methoden. Die eigentliche ...

Big Data of Complex Networks Chapman & Hall/CRC Big Data ...

Matthias Dehmer . received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and ...

Strukturelle Analyse Web-Basierter Dokumente (M, Dehmer ...

Strukturelle Analyse Web-Basierter Dokumente (M, Dehmer-, $61.91 Free Shipping. Get it by Wed, Jul 8 - Fri, Jul 17 from NY, United States • Brand New condition • 30 day returns - Buyer pays return shipping ...

Matthias Dehmer - publications.waset.org

Authors: Matthias Dehmer, Frank Emmert-Streib. Abstract: Inferring the network structure from time series data is a hard problem, especially if the time series is short and noisy. DNA microarray is a technology allowing to monitor the mRNA concentration of thousands of genes simultaneously that produces data of these characteristics. In this study we try to investigate the influence of the ...

Matthias Dehmer - Info zur Person mit Bilder, News & Links ...

190 Ergebnisse zu Matthias Dehmer: Frank Emmert-Streib, Complex Networks, Graph, Biology, Analysis of Complex, Books, Statistical

Statistical and Machine Learning Approaches for Network ...

Explore the multidisciplinary nature of complex networksthrough machine learning techniques Statistical and Machine Learning Approaches for NetworkAnalysis provides an accessible framework for structurallyanalyzing graphs by bringing together known and novel approaches ongraph classes and graph measures for classification.

Statistical and Machine Learning Approaches for Network ...

Matthias Dehmer (Author) › Visit Amazon's Matthias Dehmer Page. Find all the books, read about the author, and more. See search results for this author. Are you an author? Learn about Author Central. Matthias Dehmer (Author), Subhash C. Basak (Author) 1.0 out of 5 stars 1 rating. ISBN-13: 978-0470195154. ISBN-10: 0470195150. Why is ISBN important? ISBN. This bar-code number lets you verify ...

Analysis of Microarray Data - Matthias Dehmer, Frank ...

Pris: 1549 kr. Inbunden, 2008. Skickas inom 7-10 vardagar. Köp Analysis of Microarray Data av Matthias Dehmer, Frank Emmert-Streib på Bokus.com.

Matthias Dehmer im Das Telefonbuch >> Jetzt finden!

Matthias Dehmer Kontaktdaten ⏲ Öffnungszeiten Bewertungen ☎ Das Telefonbuch Ihre Nr. 1 für Adressen und Telefonnummern

Matthias Dehmer's research works | Universität der ...

Matthias Dehmer's 11 research works with 85 citations and 1,382 reads, including: From the connectivity index to various randić-Type descriptors

Matthias Dehmer in der Personensuche von Das Telefonbuch

Finden Sie private und berufliche Informationen zu Matthias Dehmer: Interessen, Berufe, Biografien und Lebensläufe in der Personensuche von Das Telefonbuch

Dangzhi Zhao Analysis and Visualization of Citation Networks

Prof. Gisela Bichler Understanding Criminal Networks


Understanding Criminal Networks is a short methodological primer for those interested in studying illicit, deviant, covert, or criminal networks using social network analysis (SNA). Accessibly written by Gisela Bichler, a leading expert in SNA for dark networks, the book is chock-full of graphics, checklists, software tips, step-by-step guidance, and straightforward advice. Covering all the essentials, each chapter highlights three themes: the theoretical basis of networked criminology,&#160;methodological issues and useful analytic tools,&#160;and producing professional analysis. Unlike any other book on the market, the book combines conceptual and empirical work with advice on designing networking studies, collecting data, and analysis. Relevant, practical, theoretical, and methodologically innovative, Understanding Criminal Networks promises to jumpstart readers&rsquo; understanding of how to cross over from conventional investigations of crime to the study of criminal networks.

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Antonios K. Alexandridis Wavelet Neural Networks


A step-by-step introduction to modeling, training, and forecasting using wavelet networks Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification presents the statistical model identification framework that is needed to successfully apply wavelet networks as well as extensive comparisons of alternate methods. Providing a concise and rigorous treatment for constructing optimal wavelet networks, the book links mathematical aspects of wavelet network construction to statistical modeling and forecasting applications in areas such as finance, chaos, and classification. The authors ensure that readers obtain a complete understanding of model identification by providing in-depth coverage of both model selection and variable significance testing. Featuring an accessible approach with introductory coverage of the basic principles of wavelet analysis, Wavelet Neural Networks: With Applications in Financial Engineering, Chaos, and Classification also includes: • Methods that can be easily implemented or adapted by researchers, academics, and professionals in identification and modeling for complex nonlinear systems and artificial intelligence • Multiple examples and thoroughly explained procedures with numerous applications ranging from financial modeling and financial engineering, time series prediction and construction of confidence and prediction intervals, and classification and chaotic time series prediction • An extensive introduction to neural networks that begins with regression models and builds to more complex frameworks • Coverage of both the variable selection algorithm and the model selection algorithm for wavelet networks in addition to methods for constructing confidence and prediction intervals Ideal as a textbook for MBA and graduate-level courses in applied neural network modeling, artificial intelligence, advanced data analysis, time series, and forecasting in financial engineering, the book is also useful as a supplement for courses in informatics, identification and modeling for complex nonlinear systems, and computational finance. In addition, the book serves as a valuable reference for researchers and practitioners in the fields of mathematical modeling, engineering, artificial intelligence, decision science, neural networks, and finance and economics.

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Ghafouri-Shiraz Hooshang Optical CDMA Networks. Principles, Analysis and Applications


This book focuses heavily on the principles, analysis and applications of code-division multiple-access (CDMA) techniques in optical communication systems and networks. In this book, the authors intimately discuss modern optical networks and their applications in current and emerging communication technologies, evaluating the quality, speed and number of supported services. In particular, principles and fundamentals of optical CDMA techniques from beginner to advanced levels are heavily covered. Furthermore, the authors concentrate on methods and techniques of various encoding and decoding schemes and their structures, as well as analysis of optical CDMA systems with various transceiver models including advanced multi-level incoherent and coherent modulations with the architecture of access/aggregation networks in mind. Moreover, authors examine intriguing topics of optical CDMA networking, compatibility with IP networks, and implementation of optical multi-rate multi-service CDMA networks. Key features: Expanded coverage of optical CDMA networks, starts from principles and fundamentals Comprehensive mathematical modelling and analysis from signal to system levels Addresses the applications of modern optical networking in the current and emerging communication technologies Greater focus on advanced optical multi-level incoherent and coherent modulations, spreading codes, and transceiver designs Detailed hardware specifications, system-level block diagrams, and network nodes’ functionalities This book appeals to researchers, practicing engineers, and advanced students. It is a practical resource for readers with an interest in optical communications and networks.

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Stefan Bornholdt Handbook of Graphs and Networks


Complex interacting networks are observed in systems from such diverse areas as physics, biology, economics, ecology, and computer science. For example, economic or social interactions often organize themselves in complex network structures. Similar phenomena are observed in traffic flow and in communication networks as the internet. In current problems of the Biosciences, prominent examples are protein networks in the living cell, as well as molecular networks in the genome. On larger scales one finds networks of cells as in neural networks, up to the scale of organisms in ecological food webs. This book defines the field of complex interacting networks in its infancy and presents the dynamics of networks and their structure as a key concept across disciplines. The contributions present common underlying principles of network dynamics and their theoretical description and are of interest to specialists as well as to the non-specialized reader looking for an introduction to this new exciting field. Theoretical concepts include modeling networks as dynamical systems with numerical methods and new graph theoretical methods, but also focus on networks that change their topology as in morphogenesis and self-organization. The authors offer concepts to model network structures and dynamics, focussing on approaches applicable across disciplines.

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J. Antonio R. Ostoic Algebraic Analysis of Social Networks

Jerry R. Muir, Jr. Complex Analysis


A thorough introduction to the theory of complex functions emphasizing the beauty, power, and counterintuitive nature of the subject Written with a reader-friendly approach, Complex Analysis: A Modern First Course in Function Theory features a self-contained, concise development of the fundamental principles of complex analysis. After laying groundwork on complex numbers and the calculus and geometric mapping properties of functions of a complex variable, the author uses power series as a unifying theme to define and study the many rich and occasionally surprising properties of analytic functions, including the Cauchy theory and residue theorem. The book concludes with a treatment of harmonic functions and an epilogue on the Riemann mapping theorem. Thoroughly classroom tested at multiple universities, Complex Analysis: A Modern First Course in Function Theory features: Plentiful exercises, both computational and theoretical, of varying levels of difficulty, including several that could be used for student projects Numerous figures to illustrate geometric concepts and constructions used in proofs Remarks at the conclusion of each section that place the main concepts in context, compare and contrast results with the calculus of real functions, and provide historical notes Appendices on the basics of sets and functions and a handful of useful results from advanced calculus Appropriate for students majoring in pure or applied mathematics as well as physics or engineering, Complex Analysis: A Modern First Course in Function Theory is an ideal textbook for a one-semester course in complex analysis for those with a strong foundation in multivariable calculus. The logically complete book also serves as a key reference for mathematicians, physicists, and engineers and is an excellent source for anyone interested in independently learning or reviewing the beautiful subject of complex analysis.

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Stephen Pryke Managing Networks in Project-Based Organisations


The first book demonstrating how to apply the principles of social network analysis to managing complex projects This groundbreaking book gets project managers and students up to speed on state-of-the-art applications of social network analysis (SNA) for observing, analysing, and managing complex projects. Written by an expert at the leading edge of the SNA project management movement, it clearly demonstrates how the principles of social network analysis can be used to provide a smarter, more efficient, holistic approach to managing complex projects. Project managers, especially those tasked with managing large, complex construction and engineering projects, traditionally have relied upon analysis and decision-making based upon hierarchical structures and vaguely defined project systems, much of which is borrowed from historic scientific management approaches. However, it has become apparent that a more sophisticated methodology is required for observing project systems and managing relationships with today’s more knowledgeable and demanding clients. Social network analysis (SNA) provides just such an approach. Unfortunately, existing books on social network analysis are written primarily for sociologists and mathematicians, with little or no regard for the needs of project managers – until now. The first and only book of its kind, Managing Networks in Project-Based Organisations: Offers a framework and a fully-developed approach to applying SNA theory and methodologies to large, complex projects Describes highly effective strategies and techniques for managing the iterative and transient relationships between network-defining actor roles involved in the delivery of complex projects Uses numerous real-world examples and case studies of successful applications of SNA to large-scale construction and engineering projects around the world Draws on its author’s decades of experience managing complex projects for demanding clients, as well as his extensive academic research in Project Management Managing Networks in Project-Based Organisations is an important working resource for project management professionals and consultants, especially those serving the construction and engineering industries. It is also an excellent text/reference for postgraduate students of project management and supply chain management, as well as academic researchers of project management.

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Matthias Wagner Thermal Analysis in Practice

Bruce Marcot Bayesian Networks


Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis. This book provides a general introduction to Bayesian networks, defining and illustrating the basic concepts with pedagogical examples and twenty real-life case studies drawn from a range of fields including medicine, computing, natural sciences and engineering. Designed to help analysts, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips readers with proven methods to generate, calibrate, evaluate and validate Bayesian networks. The book: Provides the tools to overcome common practical challenges such as the treatment of missing input data, interaction with experts and decision makers, determination of the optimal granularity and size of the model. Highlights the strengths of Bayesian networks whilst also presenting a discussion of their limitations. Compares Bayesian networks with other modelling techniques such as neural networks, fuzzy logic and fault trees. Describes, for ease of comparison, the main features of the major Bayesian network software packages: Netica, Hugin, Elvira and Discoverer, from the point of view of the user. Offers a historical perspective on the subject and analyses future directions for research. Written by leading experts with practical experience of applying Bayesian networks in finance, banking, medicine, robotics, civil engineering, geology, geography, genetics, forensic science, ecology, and industry, the book has much to offer both practitioners and researchers involved in statistical analysis or modelling in any of these fields.

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