Graph theory

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In mathematics and computer science, graph theory is the study of graphs, mathematical structures used to model pairwise relations between objects from a certain collection. (Wikipedia.org)






Conferences related to Graph theory

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2013 IEEE International Conference on Data Engineering (ICDE 2013)

The annual IEEE International Conference on Data Engineering (ICDE) addresses research issues in designing, building, managing, and evaluating advanced data-intensive systems and applications. It is a leading forum for researchers, practitioners, developers, and users to explore cutting-edge ideas and to exchange techniques, tools, and experiences.


2013 International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of Social Network Analysis and Mining (SNAM) in academia, politics, homeland security and business. The 2013 international conference on Advances in Social Network Analysis and Mining (ASONAM-13 will primarily provide an interdisciplinary venue brings together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. The conference will address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoretical works on social network analysis and mining with their application to real life situations.

  • 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)

    In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social Web sites, email logs, phone logs and instant messaging systems, which are widely analyzed using graph theory and machine learning techniques. People perceive the Web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community formation and evolution. This has led to a rising prominence of SNAM in academia, politics, homeland security and business.

  • 2011 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2011)

    The international conference on Advances in Social Network Analysis and Mining (ASONAM 2011) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. ASONAM 2011 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoreti

  • 2010 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2010)

    The international conference on Advances in Social Network Analysis and Mining (ASONAM 2010) will primarily provide an interdisciplinary venue that will bring together practitioners and researchers from a variety of SNAM fields to promote collaborations and exchange of ideas and practices. ASONAM 2010 is intended to address important aspects with a specific focus on the emerging trends and industry needs associated with social networking analysis and mining. The conference solicits experimental and theoreti

  • 2009 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2009)

    In recent years, social network research has advanced significantly; the development of sophisticated techniques for Social Network Analysis and Mining (SNAM) has been highly influenced by the online social websites, email logs, phone logs and instant messageing systems, which are widely analyzed using graph theory and machine learning techniques. People perceive teh web increasingly as a social medium that fosters interaction among people, sharing of experiences and knowledge, group activities, community


2012 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

BIBM 2012 solicits high-quality original research papers (including significant work-in-progress) in any aspect of bioinformatics, biomedicine and healthcare informatics. New computational techniques and methods in machine learning; data mining; text analysis; pattern recognition; knowledge representation; databases; data modeling; combinatorics; stochastic modeling; string and graph algorithms; linguistic methods; robotics; constraint satisfaction; data visualization; parallel computation; data integration; modeling and simulation and their application in life science domain are especially encouraged.


2011 2nd International Conference on Biomedical Engineering and Computer Science (ICBECS)

The 2nd International Conference on Biomedical Engineering and Computer Science (ICBECS 2011) will be held from April 23th to 24th, 2010 in Wuhan, China, which will bring together top researchers from Asian Pacific areas, North America, Europe and around the world to exchange research results and address open issues in all aspects of biomedical engineering, bioinformatics and computer science.


2011 3rd International Workshop on Education Technology and Computer Science (ETCS)

ETCS2011 will be held on 12-13 March, 2011 in Wuhan, China. ETCS2009 and ETCS2010 have been indexed by EI Compendex and ISTP. The ETCS2011 will bring together the top researchers from Asian Pacific nations, North America, Europe and around the world to exchange their research results and address open issues in Education Technology and Computer Science.

  • 2010 2nd International Workshop on Education Technology and Computer Science (ETCS)

    The 2nd International Workshop on Education Technology and Computer Science (ETCS2010) will be held on 6-7 March, 2010 in Wuhan, China. The workshop will bring together the top researchers from Asian Pacific nations, North America, Europe and around the world to exchange their research results and address open issues in Education Technology and Computer Science.


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Periodicals related to Graph theory

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Information Theory, IEEE Transactions on

The fundamental nature of the communication process; storage, transmission and utilization of information; coding and decoding of digital and analog communication transmissions; study of random interference and information-bearing signals; and the development of information-theoretic techniques in diverse areas, including data communication and recording systems, communication networks, cryptography, detection systems, pattern recognition, learning, and automata.


Pattern Analysis and Machine Intelligence, IEEE Transactions on

Statistical and structural pattern recognition; image analysis; computational models of vision; computer vision systems; enhancement, restoration, segmentation, feature extraction, shape and texture analysis; applications of pattern analysis in medicine, industry, government, and the arts and sciences; artificial intelligence, knowledge representation, logical and probabilistic inference, learning, speech recognition, character and text recognition, syntactic and semantic processing, understanding natural language, expert systems, ...


Signal Processing, IEEE Transactions on

The technology of transmission, recording, reproduction, processing, and measurement of speech; other audio-frequency waves and other signals by digital, electronic, electrical, acoustic, mechanical, and optical means; the components and systems to accomplish these and related aims; and the environmental, psychological, and physiological factors of thesetechnologies.


Visualization and Computer Graphics, IEEE Transactions on

Specific topics include, but are not limited to: a) visualization techniques and methodologies; b) visualization systems and software; c) volume visulaization; d) flow visualization; e) information visualization; f) multivariate visualization; g) modeling and surfaces; h) rendering techniques and methodologies; i) graphics systems and software; j) animation and simulation; k) user interfaces; l) virtual reality; m) visual programming and program visualization; ...



Most published Xplore authors for Graph theory

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Xplore Articles related to Graph theory

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Qualitative tracking of 3-D objects using active contour networks

S. J. Dickinson; P. Jasiobedzki; G. Olofsson; H. I. Christensen Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on, 1994

In this paper, we track changes in the appearance of the object as it moves from one frame to the next. At a symbolic level, an aspect graph clusters all the views of an object into a set of topologically distinct classes in terms of which surfaces of an object are visible from a given viewpoint (Koenderink and van Doom ...


Expander Graph based Key Distribution Mechanisms in Wireless Sensor Networks

Seyit Ahmet Camtepe; Bulent Yener; Moti Yung 2006 IEEE International Conference on Communications, 2006

Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key- chain), to each sensor node. ...


On the Consensus of Dynamic Multi-agent Systems with Changing Topology

Qin Li; Zhong-Ping Jiang 2007 American Control Conference, 2007

This paper proposes relaxed sufficient conditions for the consensus of multi- agent systems by the averaging protocol with time-varying system topology. Bidirectional information exchange between neighboring agents is considered and both the discrete-time and continuous-time consensus protocols are studied. It is shown that the consensus is reached if there exists an unbounded time sequence such that two agents who own ...


Node robust algorithm study based on graph theory

Yanbo Zhu; Xiangning Huang Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on, 2011

An enhancing algorithm for node robustness based on graph theory is proposed, which focus on the situation of poor network robust caused by the weak ability of anti-vulnerable attacks of nodes. The strategy for node and network robust based on graph coloring theory and diversity is introduced first, the graph derived from the algorithm with 35 nodes and 4 coloring ...


Graph-constrained group testing

Mahdi Cheraghchi; Amin Karbasi; Soheil Mohajer; Venkatesh Saligrama 2010 IEEE International Symposium on Information Theory, 2010

Non-adaptive group testing involves grouping arbitrary subsets of n items into different pools and identifying defective items based on tests obtained for each pool. Motivated by applications in network tomography, sensor networks and infection propagation we formulate non-adaptive group testing problems on graphs. Unlike conventional group testing problems each group here must conform to the constraints imposed by a graph. ...


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Educational Resources on Graph theory

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eLearning

Qualitative tracking of 3-D objects using active contour networks

S. J. Dickinson; P. Jasiobedzki; G. Olofsson; H. I. Christensen Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on, 1994

In this paper, we track changes in the appearance of the object as it moves from one frame to the next. At a symbolic level, an aspect graph clusters all the views of an object into a set of topologically distinct classes in terms of which surfaces of an object are visible from a given viewpoint (Koenderink and van Doom ...


Expander Graph based Key Distribution Mechanisms in Wireless Sensor Networks

Seyit Ahmet Camtepe; Bulent Yener; Moti Yung 2006 IEEE International Conference on Communications, 2006

Secure communications between large number of sensor nodes that are randomly scattered over a hostile territory, necessitate efficient key distribution schemes. However, due to limited resources at sensor nodes such schemes cannot be based on post deployment computations. Instead, pairwise (symmetric) keys are required to be pre-distributed by assigning a list of keys, (a.k.a. key- chain), to each sensor node. ...


On the Consensus of Dynamic Multi-agent Systems with Changing Topology

Qin Li; Zhong-Ping Jiang 2007 American Control Conference, 2007

This paper proposes relaxed sufficient conditions for the consensus of multi- agent systems by the averaging protocol with time-varying system topology. Bidirectional information exchange between neighboring agents is considered and both the discrete-time and continuous-time consensus protocols are studied. It is shown that the consensus is reached if there exists an unbounded time sequence such that two agents who own ...


Node robust algorithm study based on graph theory

Yanbo Zhu; Xiangning Huang Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on, 2011

An enhancing algorithm for node robustness based on graph theory is proposed, which focus on the situation of poor network robust caused by the weak ability of anti-vulnerable attacks of nodes. The strategy for node and network robust based on graph coloring theory and diversity is introduced first, the graph derived from the algorithm with 35 nodes and 4 coloring ...


Graph-constrained group testing

Mahdi Cheraghchi; Amin Karbasi; Soheil Mohajer; Venkatesh Saligrama 2010 IEEE International Symposium on Information Theory, 2010

Non-adaptive group testing involves grouping arbitrary subsets of n items into different pools and identifying defective items based on tests obtained for each pool. Motivated by applications in network tomography, sensor networks and infection propagation we formulate non-adaptive group testing problems on graphs. Unlike conventional group testing problems each group here must conform to the constraints imposed by a graph. ...


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IEEE.tv Videos

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IEEE-USA E-Books

  • Context

    Interactive systems and devices, from mobile phones to office copiers, do not fulfill their potential for a wide variety of reasons--not all of them technical. Press On shows that we can design better interactive systems and devices if we draw on sound computer science principles. It uses state machines and graph theory as a powerful and insightful way to analyze and design better interfaces and examines specific designs and creative solutions to design problems. Programmers--who have the technical knowledge that designers and users often lack--can be more creative and more central to interaction design than we might think. Sound programming concepts improve device design. Press On provides the insights, concepts and programming tools to improve usability. Knowing the computer science is fundamental, but Press On also shows how essential it is to have the right approaches to manage the design of systems that people use. Particularly for complex systems, the social, psychological and ethical concerns--the wider design issues--are crucial, and these are covered in depth. Press On highlights key principles throughout the text and provides cross-topic linkages between chapters and suggestions for further reading. Additional material, including all the program code used in the book, is available on an interactive web site. Press On is an essential textbook and reference for computer science students, programmers, and anyone interested in the design of interactive technologies.Harold Thimbleby is Professor of Computer Science at Swansea University, Wales. He is the author or editor of a number of books, including User Interface Design, and nearly 400 other publications.

  • A Linear Approximation for Graph-Based Simultaneous Localization and Mapping

    This article investigates the problem of Simultaneous Localization and Mapping (SLAM) from the perspective of linear estimation theory. The problem is first formulated in terms of graph embedding: a graph describing robot poses at subsequent instants of time needs be embedded in a three-dimensional space, assuring that the estimated configuration maximizes measurement likelihood. Combining tools belonging to linear estimation and graph theory, a closed-form approximation to the full SLAM problem is proposed, under the assumption that the relative position and the relative orientation measurements are independent. The approach needs no initial guess for optimization and is formally proven to admit solution under the SLAM setup. The resulting estimate can be used as an approximation of the actual nonlinear solution or can be further refined by using it as an initial guess for nonlinear optimization techniques. Finally, the experimental analysis demonstrates that such refinement is often unnecessary, since the linear estimate is already accurate.

  • Graph Theoretic Models in Chemistry and Molecular Biology

    The field of chemical graph theory utilizes simple graphs as models of molecules. These models are called molecular graphs, and quantifiers of molecular graphs are known as molecular descriptors or topological indices. Today's chemists use molecular descriptors to develop algorithms for computer aided drug designs, and computer based searching algorithms of chemical databases and the field is now more commonly known as combinatorial or computational chemistry. With the completion of the human genome project, related fields are emerging such as chemical genomics and pharmacogenomics. Recent advances in molecular biology are driving new methodologies and reshaping existing techniques, which in turn produce novel approaches to nucleic acid modeling and protein structure prediction. The origins of chemical graph theory are revisited and new directions in combinatorial chemistry with a special emphasis on biochemistry are explored. Of particular importance is the extension of the set of molecular descriptors to include graphical invariants. We also describe the use of artificial neural networks (ANNs) in predicting biological functional relationships based on molecular descriptor values. Specifically, a brief discussion of the fundamentals of ANNs together with an example of a graph theoretic model of RNA to illustrate the potential for ANN coupled with graphical invariants to predict function and structure of biomolecules is included.

  • No title

    The sequel to the popular lecture book entitled Biomedical Image Analysis: Tracking, this book on Biomedical Image Analysis: Segmentation tackles the challenging task of segmenting biological and medical images. The problem of partitioning multidimensional biomedical data into meaningful regions is perhaps the main roadblock in the automation of biomedical image analysis. Whether the modality of choice is MRI, PET, ultrasound, SPECT, CT, or one of a myriad of microscopy platforms, image segmentation is a vital step in analyzing the constituent biological or medical targets. This book provides a state-of-the-art, comprehensive look at biomedical image segmentation that is accessible to well-equipped undergraduates, graduate students, and research professionals in the biology, biomedical, medical, and engineering fields. Active model methods that have emerged in the last few years are a focus of the book, including parametric active contour and active surface models, active shape models and geometric active contours that adapt to the image topology. Additionally, Biomedical Image Analysis: Segmentation details attractive new methods that use graph theory in segmentation of biomedical imagery. Finally, the use of exciting new scale space tools in biomedical image analysis is reported. Table of Contents: Introduction / Parametric Active Contours / Active Contours in a Bayesian Framework / Geometric Active Contours / Segmentation with Graph Algorithms / Scale-Space Image Filtering for Segmentation

  • Evolvability Analysis: Distribution of Hyperbiobs in a Variable-Length Protein Genotype Space

    A variable-length protein genotype space (the whole amino-acid sequence space) is mathematically analyzed and a lower threshold density for adequate connectivity of functional (viable) genotypes is estimated. Functional genotypes are assumed to distribute as a 'hyperblob' which means a cluster or an island, and connectivity between hyperblobs is estimated using the theory of regular languages and the random graph theory. It is shown that the logarithmic value of the threshold density approximately decreases with an increase in the genotype length

  • Appendix A: Basics of Graph Theory

    The essential guide to the state of the art in WDM and its vast networking potential As a result of its huge transmission capacity and countless other advantages, fiber optics has fostered a bandwidth revolution, addressing the constantly growing demand for increased bandwidth. Within this burgeoning area, Wavelength Division Multiplexing (WDM) has emerged as a breakthrough technology for exploiting the capacity of optical fibers. Today, WDM is deployed by many network providers for point-to-point transmission-but there is strong momentum to develop it as a full-fledged networking technology in its own right. The telecommunications industry, network service providers, and research communities worldwide are paying close attention. Optical WDM Networks presents an easy-to-follow introduction to basic concepts, key issues, effective solutions, and state-of-the-art technologies for wavelength- routed WDM networks. Responding to the need for resources focused on the networking potential of WDM, the book is organized in terms of the most important networking aspects, such as: * Network control architecture * Routing and wavelength assignment * Virtual topology design and reconfiguration * Distributed lightpath control and management * Optical-layer protection and restoration * IP over WDM * Trends for the future in optical networks Each chapter includes examples and problems that illustrate and offer practical application of concepts, as well as extensive references for further reading. This is an essential resource for professionals and students in electrical engineering, computer engineering, and computer science as well as network engineers, designers, planners, operators, and managers who seek a backbone of knowledge in optical networks.

  • Natural Structures for ManMade MachinesCurvature in Information and Computation

    This chapter contains sections titled: Engineering Problems Arrows Everywhere - Graph Theory and Feynman-Like Diagrams Relays and Switches by Any Other Name Differentiation Through Divergence Relationships and Twisting Sequences Growth Spirals, Fibonacci Progressions, and Other Sequential Patterns L-Systems Information Compression and Maximization in Biological Systems Degrees of Freedom and Information Representation in Biological Systems A More Detailed Account of DNA's Structure More Evidence of Efficiency at Play in DNA and Higher Levels of Physiology Books, Bytes, Computers, and Biological Systems - An Analogy

  • Graph Theory and Applications

    This chapter contains sections titled: Introduction Graph Data Structures Graph-Based Problems and Algorithms Summary

  • No title

    The present book illustrates the theoretical aspects of several methodologies related to the possibility of i) enhancing the poor spatial information of the electroencephalographic (EEG) activity on the scalp and giving a measure of the electrical activity on the cortical surface. ii) estimating the directional influences between any given pair of channels in a multivariate dataset. iii) modeling the brain networks as graphs. The possible applications are discussed in three different experimental designs regarding i) the study of pathological conditions during a motor task, ii) the study of memory processes during a cognitive task iii) the study of the instantaneous dynamics throughout the evolution of a motor task in physiological conditions. The main outcome from all those studies indicates clearly that the performance of cognitive and motor tasks as well as the presence of neural diseases can affect the brain network topology. This evidence gives the power of reflecting cerebral "s ates" or "traits" to the mathematical indexes derived from the graph theory. In particular, the observed structural changes could critically depend on patterns of synchronization and desynchronization - i.e. the dynamic binding of neural assemblies - as also suggested by a wide range of previous electrophysiological studies. Moreover, the fact that these patterns occur at multiple frequencies support the evidence that brain functional networks contain multiple frequency channels along which information is transmitted. The graph theoretical approach represents an effective means to evaluate the functional connectivity patterns obtained from scalp EEG signals. The possibility to describe the complex brain networks sub-serving different functions in humans by means of "numbers" is a promising tool toward the generation of a better understanding of the brain functions. Table of Contents: Introduction / Brain Functional Connectivity / Graph Theory / High- Resolution EEG / Cortical Networks n Spinal Cord Injured Patients / Cortical Networks During a Lifelike Memory Task / Application to Time-varying Cortical Networks / Conclusions

  • MultiLog2 N Networks and Their Applications in HighSpeed Electronic and Photonic Switching Systems

    A new class of switching networks has been proposed to remove the time and space bottlenecks of conventional RAM-controlled switching architectures. The proposed networks possess many desirable characteristics for high-speed electronic and photonic switching systems - such as tolerance of faults, _O_(log2 _N_) stages between each inlet-outlet pair, self-routing capability, easy path hunt, and easy fault diagnosis. Graph theory provides the theoretical basis for the proposed networks. It is shown tbat the key problem in the construction of this new class of networks is related to the coloring problem in graph theory.



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