WorldWideScience

Sample records for undirected possibilistic networks

  1. Detecting Statistically Significant Communities of Triangle Motifs in Undirected Networks

    Science.gov (United States)

    2016-04-26

    extend the work of Perry et al. [6] by developing a statistical framework that supports the detection of triangle motif- based clusters in complex...priori, the need for triangle motif- based clustering. 2. Developed an algorithm for clustering undirected networks, where the triangle con guration was...13 5 Application to Real Networks 18 5.1 2012 FBS Football Schedule Network

  2. Possibilistic networks for uncertainty knowledge processing in student diagnosis

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2006-12-01

    Full Text Available In this paper, a possibilistic network implementation for uncertain knowledge modeling of the diagnostic process is proposed as a means to achieve student diagnosis in intelligent tutoring system. This approach is proposed in the object oriented programming domain for diagnosis of students learning errors and misconception. In this expertise domain dependencies between data exist that are encoded in the structure of network. Also, it is available qualitative information about these data which are represented and interpreted with qualitative approach of possibility theory. The aim of student diagnosis system is to ensure an adapted support for the student and to sustain the student in personalized learning process and errors explanation.

  3. On the Existence of t-Identifying Codes in Undirected De Bruijn Networks

    Science.gov (United States)

    2015-08-04

    UNDIRECTED DE BRUIJN NETWORKS 5a. CONTRACT NUMBER NA 5b. GRANT NUMBER NA 5c. PROGRAM ELEMENT NUMBER 62788F 6. AUTHOR(S) Victoria Horan 5d. PROJECT...remaining cases remain open. Additionally, we show that the eccentricity of the undirected non-binary de Bruijn graph is n. 15. SUBJECT TERMS...Additionally, we show that the eccentricity of the undirected non-binary de Bruijn graph is n. 1 Introduction and Background Let x ∈ V (G), and

  4. Convergence speed of consensus problems over undirected scale-free networks

    International Nuclear Information System (INIS)

    Sun Wei; Dou Li-Hua

    2010-01-01

    Scale-free networks and consensus behaviour among multiple agents have both attracted much attention. To investigate the consensus speed over scale-free networks is the major topic of the present work. A novel method is developed to construct scale-free networks due to their remarkable power-law degree distributions, while preserving the diversity of network topologies. The time cost or iterations for networks to reach a certain level of consensus is discussed, considering the influence from power-law parameters. They are both demonstrated to be reversed power-law functions of the algebraic connectivity, which is viewed as a measurement on convergence speed of the consensus behaviour. The attempts of tuning power-law parameters may speed up the consensus procedure, but it could also make the network less robust over time delay at the same time. Large scale of simulations are supportive to the conclusions. (general)

  5. Towards an Intelligent Possibilistic Web Information Retrieval Using Multiagent System

    Science.gov (United States)

    Elayeb, Bilel; Evrard, Fabrice; Zaghdoud, Montaceur; Ahmed, Mohamed Ben

    2009-01-01

    Purpose: The purpose of this paper is to make a scientific contribution to web information retrieval (IR). Design/methodology/approach: A multiagent system for web IR is proposed based on new technologies: Hierarchical Small-Worlds (HSW) and Possibilistic Networks (PN). This system is based on a possibilistic qualitative approach which extends the…

  6. Comparison between Possibilistic c-Means (PCM and Artificial Neural Network (ANN Classification Algorithms in Land use/ Land cover Classification

    Directory of Open Access Journals (Sweden)

    Ganchimeg Ganbold

    2017-03-01

    Full Text Available There are several statistical classification algorithms available for landuse/land cover classification. However, each has a certain bias orcompromise. Some methods like the parallel piped approach in supervisedclassification, cannot classify continuous regions within a feature. Onthe other hand, while unsupervised classification method takes maximumadvantage of spectral variability in an image, the maximally separableclusters in spectral space may not do much for our perception of importantclasses in a given study area. In this research, the output of an ANNalgorithm was compared with the Possibilistic c-Means an improvementof the fuzzy c-Means on both moderate resolutions Landsat8 and a highresolution Formosat 2 images. The Formosat 2 image comes with an8m spectral resolution on the multispectral data. This multispectral imagedata was resampled to 10m in order to maintain a uniform ratio of1:3 against Landsat 8 image. Six classes were chosen for analysis including:Dense forest, eucalyptus, water, grassland, wheat and riverine sand. Using a standard false color composite (FCC, the six features reflecteddifferently in the infrared region with wheat producing the brightestpixel values. Signature collection per class was therefore easily obtainedfor all classifications. The output of both ANN and FCM, were analyzedseparately for accuracy and an error matrix generated to assess the qualityand accuracy of the classification algorithms. When you compare theresults of the two methods on a per-class-basis, ANN had a crisperoutput compared to PCM which yielded clusters with pixels especiallyon the moderate resolution Landsat 8 imagery.

  7. Connecting possibilistic prudence and optimal saving

    Directory of Open Access Journals (Sweden)

    Ana María Lucia Casademunt

    2013-12-01

    Full Text Available In this paper we study the optimal saving problem in the framework of possibility theory. The notion of possibilistic precautionary saving is introduced as a measure of the way the presence of possibilistic risk (represented by a fuzzy number influences a consumer in establishing the level of optimal saving. The notion of prudence of an agent in the face of possibilistic risk is defined and the equivalence between the prudence condition and a positive possibilistic precautionary saving is proved. Some relations between possibilistic risk aversion, prudence and possibilistic precautionary saving were established.

  8. Possibilistic approach to target classification

    NARCIS (Netherlands)

    Huizing, A.G.; Groen, F.C.A.

    2000-01-01

    Abstract: This chapter describes an alternative to the Bayesian approach to target classification that is based on possibility theory. A possibilistic classifier minimizes the maximum cost of the classification decision taking into account the a posteriori possibilities of the target classes given

  9. A Note on the PageRank of Undirected Graphs

    OpenAIRE

    Grolmusz, Vince

    2012-01-01

    The PageRank is a widely used scoring function of networks in general and of the World Wide Web graph in particular. The PageRank is defined for directed graphs, but in some special cases applications for undirected graphs occur. In the literature it is widely noted that the PageRank for undirected graphs are proportional to the degrees of the vertices of the graph. We prove that statement for a particular personalization vector in the definition of the PageRank, and we also show that in gene...

  10. Lattice-Valued Possibilistic Entropy Measure

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2008-01-01

    Roč. 16, č. 6 (2008), s. 829-846 ISSN 0218-4885 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : complete lattice * lattice-valued possibilistic distribution * entropy measure * product of possibilistic distribution Subject RIV: BA - General Mathematics Impact factor: 1.000, year: 2008

  11. Completely Described Undirected Graph Structure

    Directory of Open Access Journals (Sweden)

    G. S. Ivanova

    2016-01-01

    Full Text Available The objects of research are undirected graphs. The paper considers a problem of their isomorphism. A literature analysis of its solution, has shown that there is no way to define a complete graph invariant in the form of unique structural characteristics of each its vertex, which has a computational complexity of definition better than О (n 4 .The work objective is to provide the characteristics of the graph structure, which could be used to solve the problem of their isomorphism for a time better than О (n 4 . As such characteristics, the paper proposes to use the set of codes of tree roots of all the shortest - in terms of the number of edges - paths from each vertex to the others, uniquely defining the structure of each tree. It proves the theorem that it is possible to reduce the problem of isomorphism of the undirected graphs to the isomorphism problem of their splitting into the trees of all the shortest - in terms of the number of edges - paths of each vertex to the others. An algorithm to construct the shortest paths from each vertex to all others and to compute codes of their vertices has been developed. As the latter, are used Aho-codes, which find application in recognising the isomorphism of trees. The computational complexity to obtain structural characteristics of vertices has been estimated to be about О (n 3 .The pilot studies involved the full-scale experiment using the developed complex programmes to generate raw data, i.e. analytic representation of the graph with the number of vertices equal to 1200, and a programme to provide codes of the tree roots. To have an estimate of - "the worst" in terms of time - complexity of expansion algorithm of graphs into trees of the shortest paths and define the codes of their roots has been an experimentally studied how the number of tree vertices depends on the graph density. For the worst case was obtained a dependence of the number of tree vertices on the number of graph vertices

  12. Possibilistic Belief Functions Generated by Direct Products of Single Possibilistic Measures

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    1999-01-01

    Roč. 9, č. 6 (1999), s. 517-525 ISSN 1210-0552 R&D Projects: GA AV ČR IAA1030803 Institutional research plan: AV0Z1030915 Keywords : belief functions * belief revision * Dempster combination rule * possibilistic measures * possibilistic belief functions Subject RIV: BA - General Mathematics

  13. A possibilistic approach to clustering

    Science.gov (United States)

    Krishnapuram, Raghu; Keller, James M.

    1993-01-01

    Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

  14. Applying Fuzzy Possibilistic Methods on Critical Objects

    DEFF Research Database (Denmark)

    Yazdani, Hossein; Ortiz-Arroyo, Daniel; Choros, Kazimierz

    2016-01-01

    Providing a flexible environment to process data objects is a desirable goal of machine learning algorithms. In fuzzy and possibilistic methods, the relevance of data objects is evaluated and a membership degree is assigned. However, some critical objects objects have the potential ability to affect...... the performance of the clustering algorithms if they remain in a specific cluster or they are moved into another. In this paper we analyze and compare how critical objects affect the behaviour of fuzzy possibilistic methods in several data sets. The comparison is based on the accuracy and ability of learning...

  15. A Fuzzy Neural Tree for Possibilistic Reliability

    NARCIS (Netherlands)

    Ciftcioglu, O.

    2008-01-01

    An innovative neural fuzzy system is considered for possibilistic reliability using a neural tree structure with nodes of neuronal type. The total tree structure works effectively as a fuzzy logic system where the possibility theory plays important role with Gaussian possibility distribution at the

  16. Decision making with probabilitic and possibilistic assessments

    Energy Technology Data Exchange (ETDEWEB)

    Sudkamp, T. [Wright State Univ., Dayton, OH (United States)

    1996-12-31

    System models are constructed to provide tools for both situation assessment and decision analysis. Two distinct types of information are used in system modeling: external information provided by mechanical sensors or human observation and internal information that describes relationships between components of the system. The former type of information is frequently represented by probability estimates, fuzzy sets, or other techniques for representing uncertain or ambiguous information while the latter type is represented by logical relations, rules, or other variations of predicate calculus. Modeling complex system requires the ability to combine the internal system relationships with the information that describes the current assessment of the status of the system. Updating an assessment incorporates sensor information and propagates it through the relational constraints of the system. Two strategies have been introduced to attempt to integrate probabilistic and possibilistic information: probability-possibility transformations and consistency measures. Consistency measures have been designed to analyze the degree of agreement of possibilistic and probabilistic interpretations of the same data. In this paper we consider the problem of assessing the consistency of probabilistic and possibilistic information obtained from different sources. Criteria for possibilistic-probabilistic consistency measures are developed using inclusion measures for fuzzy sets.

  17. Ambient Surveillance by Probabilistic-Possibilistic Perception

    NARCIS (Netherlands)

    Bittermann, M.S.; Ciftcioglu, O.

    2013-01-01

    A method for quantifying ambient surveillance is presented, which is based on probabilistic-possibilistic perception. The human surveillance of a scene through observing camera sensed images on a monitor is modeled in three steps. First immersion of the observer is simulated by modeling perception

  18. On a Particular Class of Lattice-Valued Possibilistic Distributions

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2011-01-01

    Roč. 21, č. 5 (2011), s. 407-427 ISSN 1210-0552 R&D Projects: GA ČR GEICC/08/E018 Institutional research plan: CEZ:AV0Z10300504 Keywords : possibilistic distribution * possibilistic measure * lattice-valued uncertainty degrees * complete lattice * boolean ordering * lexicographic ordering * possibilistic entropy function Subject RIV: BA - General Mathematics Impact factor: 0.646, year: 2011

  19. Hierarchical Fuzzy Sets To Query Possibilistic Databases

    OpenAIRE

    Thomopoulos, Rallou; Buche, Patrice; Haemmerlé, Ollivier

    2008-01-01

    Within the framework of flexible querying of possibilistic databases, based on the fuzzy set theory, this chapter focuses on the case where the vocabulary used both in the querying language and in the data is hierarchically organized, which occurs in systems that use ontologies. We give an overview of previous works concerning two issues: firstly, flexible querying of imprecise data in the relational model; secondly, the introduction of fuzziness in hierarchies. Concerning the latter point, w...

  20. Locally Sensitive Lattice-Valued Possibilistic Entropy Functions

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2008-01-01

    Roč. 18, č. 6 (2008), s. 469-488 ISSN 1210-0552 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : complete lattice * chained lattice * lattice-valued possibilistic distribution * possibilistic expected value Subject RIV: BA - General Mathematics Impact factor: 0.395, year: 2008

  1. Possibilistic systems within a general information theory

    Energy Technology Data Exchange (ETDEWEB)

    Joslyn, C.

    1999-06-01

    The author surveys possibilistic systems theory and place it in the context of Imprecise Probabilities and General Information Theory (GIT). In particular, he argues that possibilistic systems hold a distinct position within a broadly conceived, synthetic GIT. The focus is on systems and applications which are semantically grounded by empirical measurement methods (statistical counting), rather than epistemic or subjective knowledge elicitation or assessment methods. Regarding fuzzy measures as special provisions, and evidence measures (belief and plausibility measures) as special fuzzy measures, thereby he can measure imprecise probabilities directly and empirically from set-valued frequencies (random set measurement). More specifically, measurements of random intervals yield empirical fuzzy intervals. In the random set (Dempster-Shafer) context, probability and possibility measures stand as special plausibility measures in that their distributionality (decomposability) maps directly to an aggregable structure of the focal classes of their random sets. Further, possibility measures share with imprecise probabilities the ability to better handle open world problems where the universe of discourse is not specified in advance. In addition to empirically grounded measurement methods, possibility theory also provides another crucial component of a full systems theory, namely prediction methods in the form of finite (Markov) processes which are also strictly analogous to the probabilistic forms.

  2. Bounds for percolation thresholds on directed and undirected graphs

    Science.gov (United States)

    Hamilton, Kathleen; Pryadko, Leonid

    2015-03-01

    Percolation theory is an efficient approach to problems with strong disorder, e.g., in quantum or classical transport, composite materials, and diluted magnets. Recently, the growing role of big data in scientific and industrial applications has led to a renewed interest in graph theory as a tool for describing complex connections in various kinds of networks: social, biological, technological, etc. In particular, percolation on graphs has been used to describe internet stability, spread of contagious diseases and computer viruses; related models describe market crashes and viral spread in social networks. We consider site-dependent percolation on directed and undirected graphs, and present several exact bounds for location of the percolation transition in terms of the eigenvalues of matrices associated with graphs, including the adjacency matrix and the Hashimoto matrix used to enumerate non-backtracking walks. These bounds correspond t0 a mean field approximation and become asymptotically exact for graphs with no short cycles. We illustrate this convergence numerically by simulating percolation on several families of graphs with different cycle lengths. This research was supported in part by the NSF Grant PHY-1416578 and by the ARO Grant W911NF-11-1-0027.

  3. Amplification on Undirected Population Structures: Comets Beat Stars.

    Science.gov (United States)

    Pavlogiannis, Andreas; Tkadlec, Josef; Chatterjee, Krishnendu; Nowak, Martin A

    2017-03-06

    The fixation probability is the probability that a new mutant introduced in a homogeneous population eventually takes over the entire population. The fixation probability is a fundamental quantity of natural selection, and known to depend on the population structure. Amplifiers of natural selection are population structures which increase the fixation probability of advantageous mutants, as compared to the baseline case of well-mixed populations. In this work we focus on symmetric population structures represented as undirected graphs. In the regime of undirected graphs, the strongest amplifier known has been the Star graph, and the existence of undirected graphs with stronger amplification properties has remained open for over a decade. In this work we present the Comet and Comet-swarm families of undirected graphs. We show that for a range of fitness values of the mutants, the Comet and Comet-swarm graphs have fixation probability strictly larger than the fixation probability of the Star graph, for fixed population size and at the limit of large populations, respectively.

  4. A possibilistic approach to diverse-stressor aquatic ecological risk ...

    African Journals Online (AJOL)

    A possibilistic approach to assess the risk of co-occurring stressors in an aquatic ecosystem based on the use of fuzzy sets is illustrated at the hand of a hypothetical case study. There are two aspects of importance: a fuzzy stressor response relationship where the response may have reference to a lower level end-point, ...

  5. Extensions of Partial Lattice-Valued Possibilistic Measures from Nested Domains

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2006-01-01

    Roč. 14, č. 2 (2006), s. 175-197 ISSN 0218-4885 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : complete lattice * possibilistic measure * lattice-valued possibilistic space * nested system of sets * conservative extension * Cartesian product of possibilistic spaces Subject RIV: BA - General Mathematics Impact factor: 0.406, year: 2006

  6. Hierarchization process by possibilistic fuzzy clustering of fuzzy rules

    OpenAIRE

    Salgado, Paulo; Cunha, Manuela; Pavão, João; Igrejas, Getúlio

    2010-01-01

    This paper presents a possibilistic fuzzy clustering algorithm that is applied to a multidimensional fuzzy set or fuzzy rules. This method can be used to decompose the fuzzy system into an hierarchical structure. The methodology presented leads to a fuzzy partition of the fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. This technique is tested to organize the fuzzy model into a new and more comprehensive structure.

  7. Initialization of Possibilistic Clustering via Mountain Clustering Method

    Czech Academy of Sciences Publication Activity Database

    Coufal, David

    2000-01-01

    Roč. 10, č. 5 (2000), s. 797-809 ISSN 1210-0552. [SOFSEM 2000 Workshop on Soft Computing. Milovy, 27.11.2000-28.11.2000] R&D Projects: GA ČR GA201/00/1489 Institutional research plan: AV0Z1030915 Keywords : Mountain clustering * fuzzy c-means * possibilistic c-means Subject RIV: BA - General Mathematics

  8. Several Results on Set-Valued Possibilistic Distributions

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan; Daniel, Milan

    2015-01-01

    Roč. 51, č. 3 (2015), s. 391-407 ISSN 0023-5954 R&D Projects: GA ČR GAP202/10/1826 Institutional support: RVO:67985807 Keywords : probability measures * possibility measures * non-numerical uncertainty degrees * set-valued uncertainty degrees * possibilistic uncertainty functions * set-valued entropy functions Subject RIV: BA - General Mathematics Impact factor: 0.628, year: 2015 http://dml.cz/handle/10338.dmlcz/144376

  9. A proposal toward a possibilistic multi-robot task allocation

    Energy Technology Data Exchange (ETDEWEB)

    Guerrero, J.

    2017-07-01

    One of the main problems to solve in multi-agent (or multi-robot) systems is to select the best robot or group of robots to carry out a specific task. This problem, referenced as Multi-Agent (robot) task allocation (MRTA), is still an open issue in real environments. Swarm intelligence methods provide very simple solutions for the MRTA problem. One of the most widely used swarm methods are the so-called Response Threshold algorithms, where the behavior of the systems is modeled as a Markov chain and the robots in each time step select the next task to execute according to a transition probability function. Among other factors, this probability depends on a stimulus (for example the distance between the robot and the task). This classical probabilistic approach presents a lot of disadvantages:the transition function must meet constraints of a probabilistic distribution, the system only convergences to a stationary asymptotically, and so on. In order to overcome these problems, a new theoretical framework based on fuzzy (possibilistic) Markov chains was proposed [2]. As was proved, the possibilistic Markov chains outperform the classical probabilistic when a Max-Min algebra is considered for matrix composition. For example, fuzzy Markov chains convergence to a stable state in a finite number of steps 10 times faster than its probability counter part. Moreover, they improve the predictions of the system under imprecise information. Firstly, this paper will review relevant work in MRTA, from theoretical and experimental point of view. Then it will be summarized the aforementioned recent advances given toward a new possibilistic swarm multi-robot task allocation framework. It will be seen how the possibilistic Markov chains behave when other algebras are considered for matrix composition [1] and how the possibility transition function impacts on the system's performance [3]. Finally, it will be proposed new future works in this field. (Author)

  10. Probabilistic Networks

    DEFF Research Database (Denmark)

    Jensen, Finn Verner; Lauritzen, Steffen Lilholt

    2001-01-01

    This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs.......This article describes the basic ideas and algorithms behind specification and inference in probabilistic networks based on directed acyclic graphs, undirected graphs, and chain graphs....

  11. Unsupervised approach data analysis based on fuzzy possibilistic clustering: application to medical image MRI.

    Science.gov (United States)

    El Harchaoui, Nour-Eddine; Ait Kerroum, Mounir; Hammouch, Ahmed; Ouadou, Mohamed; Aboutajdine, Driss

    2013-01-01

    The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems of uncertain data in complex systems. We used the membership function of fuzzy c-means (FCM) to initialize the parameters of possibilistic c-means (PCM), in order to solve the problem of coinciding clusters that are generated by PCM and also overcome the weakness of FCM to noise. To validate our approach, we used several validity indexes and we compared them with other conventional classification algorithms: fuzzy c-means, possibilistic c-means, and possibilistic fuzzy c-means. The experiments were realized on different synthetics data sets and real brain MR images.

  12. Unsupervised Approach Data Analysis Based on Fuzzy Possibilistic Clustering: Application to Medical Image MRI

    Directory of Open Access Journals (Sweden)

    Nour-Eddine El Harchaoui

    2013-01-01

    Full Text Available The analysis and processing of large data are a challenge for researchers. Several approaches have been used to model these complex data, and they are based on some mathematical theories: fuzzy, probabilistic, possibilistic, and evidence theories. In this work, we propose a new unsupervised classification approach that combines the fuzzy and possibilistic theories; our purpose is to overcome the problems of uncertain data in complex systems. We used the membership function of fuzzy c-means (FCM to initialize the parameters of possibilistic c-means (PCM, in order to solve the problem of coinciding clusters that are generated by PCM and also overcome the weakness of FCM to noise. To validate our approach, we used several validity indexes and we compared them with other conventional classification algorithms: fuzzy c-means, possibilistic c-means, and possibilistic fuzzy c-means. The experiments were realized on different synthetics data sets and real brain MR images.

  13. Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

    Science.gov (United States)

    Chen, Wei

    2015-07-01

    In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

  14. Partial Convergence and Continuity of Lattice-Valued Possibilistic Measures

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2008-01-01

    Roč. 27, č. 3 (2008), s. 297-313 ISSN 1335-9150 R&D Projects: GA AV ČR IAA100300503 Institutional research plan: CEZ:AV0Z10300504 Keywords : partially ordered set * (complete) lattice * set function * lattice-valued possibilistic (possibility) measure * convergence and continuity from below (lower convergence and continuity) * convergence and continuity from above (upper convergence and continuity) Subject RIV: BA - General Mathematics Impact factor: 0.492, year: 2008 http://www.cai.sk/ojs/index.php/cai/article/view/251

  15. A multi-objective possibilistic programming approach for locating distribution centers and allocating customers demands in supply chains

    Directory of Open Access Journals (Sweden)

    Seyed Ahmad Yazdian

    2011-01-01

    Full Text Available In this paper, we present a multi-objective possibilistic programming model to locate distribution centers (DCs and allocate customers' demands in a supply chain network design (SCND problem. The SCND problem deals with determining locations of facilities (DCs and/or plants, and also shipment quantities between each two consecutive tier of the supply chain. The primary objective of this study is to consider different risk factors which are involved in both locating DCs and shipping products as an objective function. The risk consists of various components: the risks related to each potential DC location, the risk associated with each arc connecting a plant to a DC and the risk of shipment from a DC to a customer. The proposed method of this paper considers the risk phenomenon in fuzzy forms to handle the uncertainties inherent in these factors. A possibilistic programming approach is proposed to solve the resulted multi-objective problem and a numerical example for three levels of possibility is conducted to analyze the model.

  16. Possibilistic Information Flow Control for Workflow Management Systems

    Directory of Open Access Journals (Sweden)

    Thomas Bauereiss

    2014-04-01

    Full Text Available In workflows and business processes, there are often security requirements on both the data, i.e. confidentiality and integrity, and the process, e.g. separation of duty. Graphical notations exist for specifying both workflows and associated security requirements. We present an approach for formally verifying that a workflow satisfies such security requirements. For this purpose, we define the semantics of a workflow as a state-event system and formalise security properties in a trace-based way, i.e. on an abstract level without depending on details of enforcement mechanisms such as Role-Based Access Control (RBAC. This formal model then allows us to build upon well-known verification techniques for information flow control. We describe how a compositional verification methodology for possibilistic information flow can be adapted to verify that a specification of a distributed workflow management system satisfies security requirements on both data and processes.

  17. [The Identification of Lettuce Varieties by Using Unsupervised Possibilistic Fuzzy Learning Vector Quantization and Near Infrared Spectroscopy].

    Science.gov (United States)

    Wu, Xiao-hong; Cai, Pei-qiang; Wu, Bin; Sun, Jun; Ji, Gang

    2016-03-01

    To solve the noisy sensitivity problem of fuzzy learning vector quantization (FLVQ), unsupervised possibilistic fuzzy learning vector quantization (UPFLVQ) was proposed based on unsupervised possibilistic fuzzy clustering (UPFC). UPFLVQ aimed to use fuzzy membership values and typicality values of UPFC to update the learning rate of learning vector quantization network and cluster centers. UPFLVQ is an unsupervised machine learning algorithm and it can be applied to classify without learning samples. UPFLVQ was used in the identification of lettuce varieties by near infrared spectroscopy (NIS). Short wave and long wave near infrared spectra of three types of lettuces were collected by FieldSpec@3 portable spectrometer in the wave-length range of 350-2 500 nm. When the near infrared spectra were compressed by principal component analysis (PCA), the first three principal components explained 97.50% of the total variance in near infrared spectra. After fuzzy c-means (FCM). clustering was performed for its cluster centers as the initial cluster centers of UPFLVQ, UPFLVQ could classify lettuce varieties with the terminal fuzzy membership values and typicality values. The experimental results showed that UPFLVQ together with NIS provided an effective method of identification of lettuce varieties with advantages such as fast testing, high accuracy rate and non-destructive characteristics. UPFLVQ is a clustering algorithm by combining UPFC and FLVQ, and it need not prepare any learning samples for the identification of lettuce varieties by NIS. UPFLVQ is suitable for linear separable data clustering and it provides a novel method for fast and nondestructive identification of lettuce varieties.

  18. Products and Marginals of Poset-Valued Fuzzy and Possibilistic Measures

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2003-01-01

    Roč. 11, č. 6 (2003), s. 729-748 ISSN 0218-4885 R&D Projects: GA AV ČR IAA1030803 Institutional research plan: CEZ:AV0Z1030915 Keywords : fuzzy measure * possibilistic measure * partially ordered set * (semi) lattice * Cartesian product of measure s Subject RIV: BA - General Mathematics Impact factor: 0.487, year: 2003

  19. Use of Total Possibilistic Uncertainty as a Measure of Students' Modelling Capacities

    Science.gov (United States)

    Voskoglou, Michael Gr.

    2010-01-01

    We represent the main stages of the process of mathematical modelling as fuzzy sets in the set of the linguistic labels of negligible, low intermediate, high and complete success by students in each of these stages and we use the total possibilistic uncertainty as a measure of students' modelling capacities. A classroom experiment is also…

  20. Cache-Oblivious Data Structures and Algorithms for Undirected Breadth-First Search and Shortest Paths

    DEFF Research Database (Denmark)

    Brodal, G.S.; Fagerberg, Rolf; Meyer, U.

    2004-01-01

    We present improved cache-oblivious data structures and algorithms for breadth-first search and the single-source shortest path problem on undirected graphs with non-negative edge weights. Our results removes the performance gap between the currently best cache-aware algorithms for these problems...

  1. Undirected learning styles and academic risk: Analysis of the impact of stress, strain and coping.

    Science.gov (United States)

    Kimatian, Stephen; Lloyd, Sara; Berger, Jeffrey; Steiner, Lorraine; McKay, Robert; Schwengal, Deborah

    2017-01-01

    Learning style inventories used in conjunction with a measure of academic achievement consistently show an association of meaning directed learning patterns with academic success, but have failed to show a clear association of undirected learning styles with academic failure. Using survey methods with anesthesia residents, this study questioned whether additional assessment of factors related to stress, strain, and coping help to better define the association between undirected learning styles and academic risk. Pearson chi squared tests. 296 subjects were enrolled from eight institutions with 142 (48%) completing the study. American Board of Anesthesiologists In Training Examinations (ITE) percentiles (ITE%) were used as a measure of academic achievement. The Vermunt Inventory of Learning Styles (ILS) was used to identify four learning patterns and 20 strategies, and the Osipow Stress Inventory-Revised (OSI-R) was used as a measure of six scales of occupational stress, four of personal strain, and four coping resources. Two learning patterns had significant relationship with ITE scores. As seen in previous studies, Meaning Directed Learning was beneficial for academic achievement while Undirected Learning was the least beneficial. Higher scores on Meaning Directed Learning correlated positively with higher ITE scores while higher Undirected and lower Meaning Directed patterns related negatively to ITE%. OSI-R measures of stress, strain and coping indicated that residents with Undirected learning patterns had higher scores on three scales related to stress, and 4 related to strain, while displaying lower scores on two scales related to coping. Residents with higher Meaning Directed patterns scored lower on two scales of stress and two scales of strain, with higher scores on two scales for coping resources. Low Meaning Directed and high Undirected learning patterns correlated with lower ITE percentiles, higher scores for stress and strain, and lower coping resources

  2. A possibilistic model to determine the cost of environmental quality in mid/short term planning of an electricity distribution system

    International Nuclear Information System (INIS)

    Schweickardt, Gustavo Alejandro; Gimenez Alvarez, Juan Manuel

    2012-01-01

    This work presents a Possibilistic Optimization Model to determine the Dynamic Environmental Quality Cost, applied on an Electricity Distribution System and measured as Network System Visual Impact. The Mid/Short Term Planning is the Regulatory Control Period. A multicriteria optimization approach is proposed, and for each criterion, non-stochastic uncertainties are recognized and represented by mean the introduction of Fuzzy Sets. In this way, a possibility in the occurrence of criteria variables values is established. In addition, as consequence of uncertainties of criteria preference ranking, a Model to obtain criteria Priority Vector is introduced. The Environmental Quality Cost determination is based in the relationship between the Investment Cost and an Impact Index of Network System Environmental Quality, proposed in this work. Finally, a simulation on a real system and the most important conclusions are presented.

  3. Duopoly Market Analysis within One-Shot Decision Framework with Asymmetric Possibilistic Information

    Directory of Open Access Journals (Sweden)

    Peijun Guo

    2010-12-01

    Full Text Available In this paper, a newly emerging duopoly market with a short life cycle is analyzed. The partially known information of market is characterized by the possibility distribution of the parameter in the demand function. Since the life cycle of the new product is short, how many products should be produced by two rival firms is a typical one-shot decision problem. Within the one-shot decision framework, the possibilistic Cournot equilibrium is obtained for the optimal production level of each firm in a duopoly market with asymmetrical possibilistic information. The analysis results show that the proposed approaches are reasonable for one-shot decision problems, which are extensively encountered in business and economics.

  4. Fuzzy possibilistic model for medium-term power generation planning with environmental criteria

    International Nuclear Information System (INIS)

    Muela, E.; Schweickardt, G.; Garces, F.

    2007-01-01

    The aim of this paper is to apply a fuzzy possibilistic model to the power generation planning that includes environmental criteria. Since it is not always meaningful to relate uncertainty to frequency, the proposed approach analyzes the imprecision and ambiguity into the decision making, especially when the system involves human subjectivity. This paper highlights the subjacent differences between fuzzy and possibilistic entities. Additionally, it illustrates the use of fuzzy sets theory and possibility theory for modeling flexibility, and nonprobablistic uncertainty, respectively. The necessity of a new direction for the environmental problem in a power system is outlined, an approach that attempts a greater integral quality of planning instead of searching for a simple optimal solution. This process must be consistent with a wider and more suitable interpretation about both the problem as such and the concept of solution in uncertain situations

  5. Compatibility of Safety Properties and Possibilistic Information Flow Security in MAKS

    OpenAIRE

    Bauereiss , Thomas; Hutter , Dieter

    2014-01-01

    Part 6: Information Flow Control; International audience; Motivated by typical security requirements of workflow management systems, we consider the integrated verification of both safety properties (e.g. separation of duty) and information flow security predicates of the MAKS framework (e.g. modeling confidentiality requirements). Due to the refinement paradox, enforcement of safety properties might violate possibilistic information flow properties of a system. We present an approach where s...

  6. Almost-Measurability Relation Induced by Lattice-Valued Partial Possibilistic Measures

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2004-01-01

    Roč. 33, č. 6 (2004), s. 679-704 ISSN 0308-1079 R&D Projects: GA MŠk OC 274.001 Grant - others:COST(XE) Action 274 TARSKI Institutional research plan: CEZ:AV0Z1030915 Keywords : partially ordered set * complete lattice * partial lattice-valuied possibilistic measure * inner measure * outer measure * measurability in the Lebesgue sense * almost-measurability Subject RIV: BA - General Mathematics Impact factor: 0.509, year: 2004

  7. On Inner and Outer Extensions of Non-Numerical Fuzzy and Possibilistic Measures

    Czech Academy of Sciences Publication Activity Database

    Kramosil, Ivan

    2002-01-01

    Roč. 12, č. 5 (2002), s. 473-482 ISSN 1210-0552. [SOFSEM 2002 Workshop on Soft Computing. Milovy, 28.11.2002-29.11.2002] R&D Projects: GA AV ČR IAA1030803 Institutional research plan: AV0Z1030915 Keywords : fuzzy measure * possibilistic measure * inner measure * outer measure * measurability in the Lebesgue sense * non-numerical uncertainty degrees Subject RIV: BA - General Mathematics

  8. Fuzzy segmentation of cerebral tissues in a 3-D MR image: a possibilistic approach versus other methods

    International Nuclear Information System (INIS)

    Barra, V.; Boire, J.Y.

    1999-01-01

    An algorithm for the segmentation of a single sequence of 3-D magnetic resonance images into cerebrospinal Fluid (CSF), Grey (GM) and White Matter (WM) classes is proposed. The method is a possibilistic clustering algorithm on the wavelet coefficients of the voxels. Possibilistic logic allows for modeling the uncertainty and the impreciseness inherent in MR images of the brain, while the wavelet representation allows to take into account both spatial and textural information. The procedure is fast, unsupervised and totally independent of statistical assumptions. In method is validated on a phantom, and then compared with other very used brain tissues segmentation algorithms. (authors)

  9. Pattern recognition in RICH counters using the Possibilistic C- Spherical Shell algorithm

    CERN Document Server

    Massone, A M; Masulli, F

    2000-01-01

    The pattern recognition problem in RICH counters concerns the identification of an unknown number of imperfect roughly-circular rings made of a low number of discrete points in presence of background. We present some preliminary results obtained using the Possibilistic C-Spherical Shell algorithm. In particular, we show that the algorithm is very tolerant and robust to noise (outliers rate) level. Moreover, for complex images full of rings, we introduce an iterative scheme that greatly improves performance. Also, the rings are not required to be complete, arcs are sufficient to recognize the underlying rings. (4 refs).

  10. Conversational agents for academically productive talk: a comparison of directed and undirected agent interventions

    DEFF Research Database (Denmark)

    Tegos, Stergios; Demetriadis, Stavros N.; Papadopoulos, Pantelis M.

    2016-01-01

    Conversational agents that draw on the framework of academically productive talk (APT) have been lately shown to be effective in helping learners sustain productive forms of peer dialogue in diverse learning settings. Yet, literature suggests that more research is required on how learners respond...... instead of the dyad (D treatment). The results suggest that although both agent intervention methods can improve students’ learning outcomes and dyad in-task performance, the directed one is more effective than the undirected one in enhancing individual domain knowledge acquisition and explicit reasoning....... Furthermore, findings show that the positive effect of the agent on dyad performance is mediated by the frequency of students’ contributions displaying explicit reasoning, while most students perceive agent involvement favorably....

  11. Optimization of environmental management strategies through a dynamic stochastic possibilistic multiobjective program.

    Science.gov (United States)

    Zhang, Xiaodong; Huang, Gordon

    2013-02-15

    Greenhouse gas (GHG) emissions from municipal solid waste (MSW) management facilities have become a serious environmental issue. In MSW management, not only economic objectives but also environmental objectives should be considered simultaneously. In this study, a dynamic stochastic possibilistic multiobjective programming (DSPMP) model is developed for supporting MSW management and associated GHG emission control. The DSPMP model improves upon the existing waste management optimization methods through incorporation of fuzzy possibilistic programming and chance-constrained programming into a general mixed-integer multiobjective linear programming (MOP) framework where various uncertainties expressed as fuzzy possibility distributions and probability distributions can be effectively reflected. Two conflicting objectives are integrally considered, including minimization of total system cost and minimization of total GHG emissions from waste management facilities. Three planning scenarios are analyzed and compared, representing different preferences of the decision makers for economic development and environmental-impact (i.e. GHG-emission) issues in integrated MSW management. Optimal decision schemes under three scenarios and different p(i) levels (representing the probability that the constraints would be violated) are generated for planning waste flow allocation and facility capacity expansions as well as GHG emission control. The results indicate that economic and environmental tradeoffs can be effectively reflected through the proposed DSPMP model. The generated decision variables can help the decision makers justify and/or adjust their waste management strategies based on their implicit knowledge and preferences. Copyright © 2012 Elsevier B.V. All rights reserved.

  12. A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

    Directory of Open Access Journals (Sweden)

    Vahid Reza Salamat

    2018-09-01

    Full Text Available The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills the gap between theories of inter-organizational relationships and quantitative models. Thus, a novel Robust Fuzzy Possibilistic AHP approach is proposed for combining the benefits of two complementary theories of inter-organizational relationships named, (1 Resource-based view, and (2 Transaction-cost theory and considering Fit theory as the perquisite of alliance success. The Robust Fuzzy Possibilistic AHP approach is a novel development of Interval-AHP technique employing robust formulation; aimed at handling the ambiguity of the problem and let the use of intervals as pairwise judgments. The proposed approach was compared with existing approaches, and the results show that it provides the best quality solutions in terms of minimum error degree. Moreover, the framework implemented in a case study and its applicability were discussed.

  13. A possibilistic analysis approach for environmental risk assessment of petroleum-contaminated sites

    International Nuclear Information System (INIS)

    Liu, L.; Huang, G.H.; Fuller, G.A.

    1999-01-01

    A possibilistic approach for assessing risks associated with petroleum-contaminated sites is provided. The approach is applied to an illustrative case study in order to show its applicability and implementation for decision making in effective site remediation and management. The approach consists of three main parts: (1) the determination of fuzzy steady state contaminant concentrations in a aquifer based on an analytical solute transport model; (2) possibilistic analysis of fuzzy criteria for different risk levels; and (3) environmental risk assessment based on the Euclidian method. Based on results from an illustrative case study, environmental risks at a petroleum-contaminated site can be effectively evaluated using the developed methodology. The risk assessment framework can effectively handle uncertainities presented as fuzzy numbers. The fuzzy nature of water quality and risk level criteria were seen in the related simulation and evaluation models, and the framework is especially useful for situations in which probabilistic information is not available. This use of this approach is new in the area of petroleum waste management under uncertainty, and its results are useful for the related site remediation and management decisions. 36 refs., 1 tab., 4 figs

  14. Positive effect of dietary lutein and cholesterol on the undirected song activity of an opportunistic breeder

    Directory of Open Access Journals (Sweden)

    Stefania Casagrande

    2016-10-01

    Full Text Available Song is a sexually selected trait that is thought to be an honest signal of the health condition of an individual in many bird species. For species that breed opportunistically, the quantity of food may be a determinant of singing activity. However, it is not yet known whether the quality of food plays an important role in this respect. The aim of the present study was to experimentally investigate the role of two calorie-free nutrients (lutein and cholesterol in determining the expression of a sexually selected behavior (song rate and other behaviors (locomotor activity, self-maintenance activity, eating and resting in male zebra finches (Taeniopygia guttata. We predicted that males supplemented with lutein and cholesterol would sing at higher rates than controls because both lutein and cholesterol have important health-related physiological functions in birds and birdsong mirrors individual condition. To control for testosterone secretion that may upregulate birdsong, birds were exposed to a decreasing photoperiod. Our results showed that control males down-regulated testosterone in response to a decreasing photoperiod, while birds treated with lutein or cholesterol maintained a constant singing activity. Both lutein- and cholesterol-supplemented groups sang more than control groups by the end of the experiment, indicating that the quality of food can affect undirected song irrespective of circulating testosterone concentrations. None of the other measured behaviors were affected by the treatment, suggesting that, when individuals have full availability of food, sexually selected song traits are more sensitive to the effect of food quality than other behavioral traits. Overall the results support our prediction that undirected song produced by male zebra finches signals access to high-quality food.

  15. A weighted possibilistic programming approach for sustainable vendor selection and order allocation in fuzzy environment

    DEFF Research Database (Denmark)

    Gupta, Pankaj; Govindan, Kannan; Mehlawat, Mukesh Kumar

    2016-01-01

    This paper focused on the analysis of imprecise information in terms of many critical parameters for a multi-objective multi-item vendor selection-order allocation problem with price-breaks. We used both quantitative and qualitative criteria taking into account the economic, technological, social......, environmental factors, and the price-breaks that were offered on order quantity following ‘all-unit discount schedule.’ We developed an optimization model that integrated fuzzy multi-objective integer linear programming and analytic hierarchy process techniques. A weighted possibilistic programming approach...... approach were tested on the data set of an industrial case study. A detailed performance analysis and comparisons were done to show superiority of the proposed methodology over the existing related fuzzy programming approaches....

  16. Robust stochastic fuzzy possibilistic programming for environmental decision making under uncertainty

    International Nuclear Information System (INIS)

    Zhang, Xiaodong; Huang, Guo H.; Nie, Xianghui

    2009-01-01

    Nonpoint source (NPS) water pollution is one of serious environmental issues, especially within an agricultural system. This study aims to propose a robust chance-constrained fuzzy possibilistic programming (RCFPP) model for water quality management within an agricultural system, where solutions for farming area, manure/fertilizer application amount, and livestock husbandry size under different scenarios are obtained and interpreted. Through improving upon the existing fuzzy possibilistic programming, fuzzy robust programming and chance-constrained programming approaches, the RCFPP can effectively reflect the complex system features under uncertainty, where implications of water quality/quantity restrictions for achieving regional economic development objectives are studied. By delimiting the uncertain decision space through dimensional enlargement of the original fuzzy constraints, the RCFPP enhances the robustness of the optimization processes and resulting solutions. The results of the case study indicate that useful information can be obtained through the proposed RCFPP model for providing feasible decision schemes for different agricultural activities under different scenarios (combinations of different p-necessity and p i levels). A p-necessity level represents the certainty or necessity degree of the imprecise objective function, while a p i level means the probabilities at which the constraints will be violated. A desire to acquire high agricultural income would decrease the certainty degree of the event that maximization of the objective be satisfied, and potentially violate water management standards; willingness to accept low agricultural income will run into the risk of potential system failure. The decision variables under combined p-necessity and p i levels were useful for the decision makers to justify and/or adjust the decision schemes for the agricultural activities through incorporation of their implicit knowledge. The results also suggest that

  17. A possibilistic approach for transient identification with 'don't know' response capability optimized by genetic algorithm

    International Nuclear Information System (INIS)

    Almeida, Jose Carlos S. de; Schirru, Roberto; Pereira, Claudio M.N.A.; Universidade Federal, Rio de Janeiro, RJ

    2002-01-01

    This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work, optimized by genetic algorithm. The idea behind this method is to split the complex classification problem into small and simple ones, so that the performance in the classification can be increased. In order to accomplish that, a genetic algorithm is used to learn, from realistic simulated data, the optimized time partitions, which the robustness and correctness in the classification are maximized. The use of a possibilistic classification approach propitiates natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know 'response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical. Application of the proposed approach to a nuclear transient indentification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. Obtained results are shown and commented. (author)

  18. NEAT : an efficient network enrichment analysis test

    NARCIS (Netherlands)

    Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

    2016-01-01

    BACKGROUND: Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be

  19. Approximability of Robust Network Design

    NARCIS (Netherlands)

    Olver, N.K.; Shepherd, F.B.

    2014-01-01

    We consider robust (undirected) network design (RND) problems where the set of feasible demands may be given by an arbitrary convex body. This model, introduced by Ben-Ameur and Kerivin [Ben-Ameur W, Kerivin H (2003) New economical virtual private networks. Comm. ACM 46(6):69-73], generalizes the

  20. Communication on the structure of biological networks

    Indian Academy of Sciences (India)

    An epidemic can also spread faster in neuronal networks than in the other biological networks studied here. Thus, the underlying undirected architecture of a neuronal network possesses certain conformation which is favourable for spreading different entities or information. Now, to explore the topological characteristics that ...

  1. The H0 function, a new index for detecting structural/topological complexity information in undirected graphs

    Science.gov (United States)

    Buscema, Massimo; Asadi-Zeydabadi, Masoud; Lodwick, Weldon; Breda, Marco

    2016-04-01

    Significant applications such as the analysis of Alzheimer's disease differentiated from dementia, or in data mining of social media, or in extracting information of drug cartel structural composition, are often modeled as graphs. The structural or topological complexity or lack of it in a graph is quite often useful in understanding and more importantly, resolving the problem. We are proposing a new index we call the H0function to measure the structural/topological complexity of a graph. To do this, we introduce the concept of graph pruning and its associated algorithm that is used in the development of our measure. We illustrate the behavior of our measure, the H0 function, through different examples found in the appendix. These examples indicate that the H0 function contains information that is useful and important characteristics of a graph. Here, we restrict ourselves to undirected.

  2. Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

    Science.gov (United States)

    Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

    2016-11-01

    Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

  3. Two fuzzy possibilistic bi-objective zero-one programming models for outsourcing the equipment maintenance problem

    Science.gov (United States)

    Vahdani, Behnam; Jolai, Fariborz; Tavakkoli-Moghaddam, Reza; Meysam Mousavi, S.

    2012-07-01

    Maintenance outsourcing can be regarded as a strategic weapon to increase productivity and customer satisfaction in many companies, and this critical activity can be performed in a more efficient and effective way. This article presents two novel fuzzy possibilistic bi-objective zero-one programming (FPBOZOP) models for outsourcing of the equipment maintenance. In these models, cost parameters, including outsourcing cost, risk cost, time operations for performing the equipment maintenance and reliability level, as well as other influential parameters are considered through the outsourcing process. Moreover, the presented models can measure the capability of the company in doing different activities, unlike previous studies, in order to see the possibility of maintenance in-house, and can lead to make a best decision on the basis of the models' results. Both models are developed under uncertainty, which bring top managers the possibility of assigning more than one equipment or project to the supplier so that the profit is maximized, and the cost is minimized by considering bi-objectives concurrently. Then, a new fuzzy mathematical programming based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed bi-objective zero-one programming (BOZOP) models and to reach a preferred compromise solution. Furthermore, a real-case study is utilized to demonstrate and to validate the effectiveness of the presented models. The computational results revealed that the models can be implemented in variety of problems in the domain of the equipment maintenance outsourcing and project outsourcing either from theory or application perspectives.

  4. A possibilistic approach to rotorcraft design through a multi-objective evolutionary algorithm

    Science.gov (United States)

    Chae, Han Gil

    constraints, and there has been no clear explanation for constraint handling in SPEA so far. In this thesis work, it is proposed that through a slight modification of the notion of dominance, it is possible to make SPEA manage constraints successfully. In light of the notion of possibility, a concept of solution that ensures a certain confidence level is proposed and implemented in a new evolutionary algorithm with a newly defined fuzzied version of the multi-objective optimization problem statement. In the new problem statement, function values and constraints are softened by possibility distributions that reflect the intuitive assessment of the expert. Multiple alternative solutions to the problem are found by the modified SPEA. Furthermore, the new method is applied to the sizing problem of a gyrodyne cofiguration which employs a tip-jet-driven rotor on top of a fixed-wing aircraft. The sizing environment includes a 6-DOF rotor trim model, a tip-jet model, a blade duct model and engine models for various concepts of air compression. However, the design problem of the gyrodyne is ill-defined, and there are only a few data available. Therefore, a large portion of the analysis involves intuitive information. The intuitive information is quantified, and sizing is performed through the possibilistic MOEA investigating the influences of the various factors. The trade-offs includes discrete variables for engine type and an optional tip burner, as well as continuous variables for rotor parameters and engine parameters.

  5. Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

    Science.gov (United States)

    Lestari, A. W.; Rustam, Z.

    2017-07-01

    In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

  6. Undirected (solitary birdsong in female and male blue-capped cordon-bleus (Uraeginthus cyanocephalus and its endocrine correlates.

    Directory of Open Access Journals (Sweden)

    Nicole Geberzahn

    Full Text Available BACKGROUND: Birdsong is a popular model system in research areas such as vocal communication, neuroethology or neuroendocrinology of behaviour. As most research has been conducted on species with male-only song production, the hormone-dependency of male song is well established. However, female singing and its mechanisms are poorly understood. METHODOLOGY/PRINCIPAL FINDINGS: We characterised the song and its endocrine correlates of blue-capped cordon-bleus (Uraeginthus cyanocephalus, a species in which both sexes sing. Like other estrildids, they produce directed song during courtship and undirected (or solitary song in isolation, i.e. when the mate is not visible or absent. We compare solitary song of blue-capped cordon-bleus to published descriptions of the song of its relative, the zebra finch (Taeniopygia guttata. Solitary song of cordon-bleus shared some overall song features with that of zebra finches but differed in spectro-temporal song features, sequential stereotypy and sequential organisation. The song of cordon-bleus was dimorphic with respect to the larger size of syllable repertoires, the higher song duration and the lower variability of pitch goodness (measuring the pureness of harmonic sounds in males. However, in both sexes the overall plasma testosterone concentrations were low (ca. 300 pg/ml and did not correlate with the sexually dimorphic song motor pattern. Despite such low concentrations, the increase in the rate of solitary song coincided with an increase in the level of testosterone. Furthermore, the latency to start singing after the separation from the mate was related to hormone levels. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that the occurrence of solitary song but not its motor pattern might be under the control of testosterone in female and male cordon-bleus.

  7. Sustainable and Resilient Garment Supply Chain Network Design with Fuzzy Multi-Objectives under Uncertainty

    Directory of Open Access Journals (Sweden)

    Sonia Irshad Mari

    2016-10-01

    Full Text Available Researchers and practitioners are taking more interest in developing sustainable garment supply chains in recent times. On the other hand, the supply chain manager drops sustainability objectives while coping with unexpected natural and man-made disruption risks. Hence, supply chain managers are now trying to develop sustainable supply chains that are simultaneously resilient enough to cope with disruption risks. Owing to the importance of the considered issue, this study proposed a network optimization model for a sustainable and resilient supply chain network by considering sustainability via embodied carbon footprints and carbon emissions and resilience by considering resilience index. In this paper, initially, a possibilistic fuzzy multi-objective sustainable and resilient supply chain network model is developed for the garment industry considering economic, sustainable, and resilience objectives. Secondly, a possibilistic fuzzy linguistic weight-based interactive solution method is proposed. Finally, a numerical case example is presented to show the applicability of the proposed model and solution methodology.

  8. A modified possibilistic fuzzy c-means clustering algorithm for bias field estimation and segmentation of brain MR image.

    Science.gov (United States)

    Ji, Ze-Xuan; Sun, Quan-Sen; Xia, De-Shen

    2011-07-01

    A modified possibilistic fuzzy c-means clustering algorithm is presented for fuzzy segmentation of magnetic resonance (MR) images that have been corrupted by intensity inhomogeneities and noise. By introducing a novel adaptive method to compute the weights of local spatial in the objective function, the new adaptive fuzzy clustering algorithm is capable of utilizing local contextual information to impose local spatial continuity, thus allowing the suppression of noise and helping to resolve classification ambiguity. To estimate the intensity inhomogeneity, the global intensity is introduced into the coherent local intensity clustering algorithm and takes the local and global intensity information into account. The segmentation target therefore is driven by two forces to smooth the derived optimal bias field and improve the accuracy of the segmentation task. The proposed method has been successfully applied to 3 T, 7 T, synthetic and real MR images with desirable results. Comparisons with other approaches demonstrate the superior performance of the proposed algorithm. Moreover, the proposed algorithm is robust to initialization, thereby allowing fully automatic applications. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. Communications and Cooperation in Public Network Situations

    NARCIS (Netherlands)

    Suijs, J.P.M.; Borm, P.E.M.; Hamers, H.J.M.; Koster, M.A.L.; Quant, M.

    2001-01-01

    This paper focuses on sharing the costs and revenues of maintaining a public network communication structure.Revenues are assumed to be bilateral and communication links are publicly available but costly.It is assumed that agents are located at the vertices of an undirected graph in which the edges

  10. Deep Belief Networks for dimensionality reduction

    NARCIS (Netherlands)

    Noulas, A.K.; Kröse, B.J.A.

    2008-01-01

    Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art

  11. Dynamic Network Formation Using Ant Colony Optimization

    Science.gov (United States)

    2009-03-01

    Problem (DVRP) ............................................ 36 2.7.2 Dynamic Traveling Salesman Problem (DTSP) ....................................... 41...47 2.8.3 Distributed Traveling Salesman Problem ................................................. 48 2.8.4 FIRE Ant...uses the fixed cost of the network in its calculation and commodities are not included in the problem formulation . Using a probabilistic undirected

  12. Markov Networks in Evolutionary Computation

    CERN Document Server

    Shakya, Siddhartha

    2012-01-01

    Markov networks and other probabilistic graphical modes have recently received an upsurge in attention from Evolutionary computation community, particularly in the area of Estimation of distribution algorithms (EDAs).  EDAs have arisen as one of the most successful experiences in the application of machine learning methods in optimization, mainly due to their efficiency to solve complex real-world optimization problems and their suitability for theoretical analysis. This book focuses on the different steps involved in the conception, implementation and application of EDAs that use Markov networks, and undirected models in general. It can serve as a general introduction to EDAs but covers also an important current void in the study of these algorithms by explaining the specificities and benefits of modeling optimization problems by means of undirected probabilistic models. All major developments to date in the progressive introduction of Markov networks based EDAs are reviewed in the book. Hot current researc...

  13. An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty.

    Science.gov (United States)

    Li, Y P; Huang, G H

    2010-09-15

    Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty. Copyright 2010 Elsevier B.V. All rights reserved.

  14. An interval-possibilistic basic-flexible programming method for air quality management of municipal energy system through introducing electric vehicles.

    Science.gov (United States)

    Yu, L; Li, Y P; Huang, G H; Shan, B G

    2017-09-01

    Contradictions of sustainable transportation development and environmental issues have been aggravated significantly and been one of the major concerns for energy systems planning and management. A heavy emphasis is placed on stimulation of electric vehicles (EVs) to handle these problems associated with various complexities and uncertainties in municipal energy system (MES). In this study, an interval-possibilistic basic-flexible programming (IPBFP) method is proposed for planning MES of Qingdao, where uncertainties expressed as interval-flexible variables and interval-possibilistic parameters can be effectively reflected. Support vector regression (SVR) is used for predicting electricity demand of the city under various scenarios. Solutions of EVs stimulation levels and satisfaction levels in association with flexible constraints and predetermined necessity degrees are analyzed, which can help identify the optimized energy-supply patterns that could plunk for improvement of air quality and hedge against violation of soft constraints. Results disclose that largely developing EVs can help facilitate the city's energy system with an environment-effective way. However, compared to the rapid growth of transportation, the EVs' contribution of improving the city's air quality is limited. It is desired that, to achieve an environmentally sustainable MES, more concerns should be focused on the integration of increasing renewable energy resources, stimulating EVs as well as improving energy transmission, transport and storage. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Possibilistic Clustering Technique-Based Traffic Light Control for Handling Emergency Vehicle

    OpenAIRE

    F. Titouna; S. Benferhat; K. Aksa; C. Titouna

    2012-01-01

    A traffic light gives security from traffic congestion,reducing the traffic jam, and organizing the traffic flow. Furthermore,increasing congestion level in public road networks is a growingproblem in many countries. Using Intelligent Transportation Systemsto provide emergency vehicles a green light at intersections canreduce driver confusion, reduce conflicts, and improve emergencyresponse times. Nowadays, the technology of wireless sensornetworks can solve many problems and can offer a good...

  16. Analysis of protein-protein interaction networks by means of annotated graph mining algorithms

    NARCIS (Netherlands)

    Rahmani, Hossein

    2012-01-01

    This thesis discusses solutions to several open problems in Protein-Protein Interaction (PPI) networks with the aid of Knowledge Discovery. PPI networks are usually represented as undirected graphs, with nodes corresponding to proteins and edges representing interactions among protein pairs. A large

  17. Information theoretic description of networks

    Science.gov (United States)

    Wilhelm, Thomas; Hollunder, Jens

    2007-11-01

    We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rdictatorship network. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.

  18. The Vulnerability of Some Networks including Cycles via Domination Parameters

    Directory of Open Access Journals (Sweden)

    Tufan Turaci

    2016-01-01

    Full Text Available Let G=(V(G,E(G be an undirected simple connected graph. A network is usually represented by an undirected simple graph where vertices represent processors and edges represent links between processors. Finding the vulnerability values of communication networks modeled by graphs is important for network designers. The vulnerability value of a communication network shows the resistance of the network after the disruption of some centers or connection lines until a communication breakdown. The domination number and its variations are the most important vulnerability parameters for network vulnerability. Some variations of domination numbers are the 2-domination number, the bondage number, the reinforcement number, the average lower domination number, the average lower 2-domination number, and so forth. In this paper, we study the vulnerability of cycles and related graphs, namely, fans, k-pyramids, and n-gon books, via domination parameters. Then, exact solutions of the domination parameters are obtained for the above-mentioned graphs.

  19. Network similarity and statistical analysis of earthquake seismic data

    OpenAIRE

    Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

    2016-01-01

    We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We cal...

  20. Earthquake Complex Network Analysis Before and After the Mw 8.2 Earthquake in Iquique, Chile

    Science.gov (United States)

    Pasten, D.

    2017-12-01

    The earthquake complex networks have shown that they are abble to find specific features in seismic data set. In space, this networkshave shown a scale-free behavior for the probability distribution of connectivity, in directed networks and theyhave shown a small-world behavior, for the undirected networks.In this work, we present an earthquake complex network analysis for the large earthquake Mw 8.2 in the north ofChile (near to Iquique) in April, 2014. An earthquake complex network is made dividing the three dimensional space intocubic cells, if one of this cells contain an hypocenter, we name this cell like a node. The connections between nodes aregenerated in time. We follow the time sequence of seismic events and we are making the connections betweennodes. Now, we have two different networks: a directed and an undirected network. Thedirected network takes in consideration the time-direction of the connections, that is very important for the connectivityof the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out ofthe node i plus the self-connections (if two seismic events occurred successive in time in the same cubic cell, we havea self-connection). The undirected network is made removing the direction of the connections and the self-connectionsfrom the directed network. For undirected networks, we are considering only if two nodes are or not connected.We have built a directed complex network and an undirected complex network, before and after the large earthquake in Iquique. We have used magnitudes greater than Mw = 1.0 and Mw = 3.0. We found that this method can recognize the influence of thissmall seismic events in the behavior of the network and we found that the size of the cell used to build the network isanother important factor to recognize the influence of the large earthquake in this complex system. This method alsoshows a difference in the values of the critical exponent γ (for the probability

  1. Most Undirected Random Graphs Are Amplifiers of Selection for Birth-Death Dynamics, but Suppressors of Selection for Death-Birth Dynamics

    Science.gov (United States)

    Hindersin, Laura; Traulsen, Arne

    2015-01-01

    We analyze evolutionary dynamics on graphs, where the nodes represent individuals of a population. The links of a node describe which other individuals can be displaced by the offspring of the individual on that node. Amplifiers of selection are graphs for which the fixation probability is increased for advantageous mutants and decreased for disadvantageous mutants. A few examples of such amplifiers have been developed, but so far it is unclear how many such structures exist and how to construct them. Here, we show that almost any undirected random graph is an amplifier of selection for Birth-death updating, where an individual is selected to reproduce with probability proportional to its fitness and one of its neighbors is replaced by that offspring at random. If we instead focus on death-Birth updating, in which a random individual is removed and its neighbors compete for the empty spot, then the same ensemble of graphs consists of almost only suppressors of selection for which the fixation probability is decreased for advantageous mutants and increased for disadvantageous mutants. Thus, the impact of population structure on evolutionary dynamics is a subtle issue that will depend on seemingly minor details of the underlying evolutionary process. PMID:26544962

  2. Deep Belief Networks for dimensionality reduction

    OpenAIRE

    Noulas, A.K.; Kröse, B.J.A.

    2008-01-01

    Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art training method for DBNs is contrastive divergence, an efficient learning technique that can approximate and follow the gradient of the data likelihood with respect to the model parameters. In this wo...

  3. Hidden neural networks

    DEFF Research Database (Denmark)

    Krogh, Anders Stærmose; Riis, Søren Kamaric

    1999-01-01

    A general framework for hybrids of hidden Markov models (HMMs) and neural networks (NNs) called hidden neural networks (HNNs) is described. The article begins by reviewing standard HMMs and estimation by conditional maximum likelihood, which is used by the HNN. In the HNN, the usual HMM probability...... parameters are replaced by the outputs of state-specific neural networks. As opposed to many other hybrids, the HNN is normalized globally and therefore has a valid probabilistic interpretation. All parameters in the HNN are estimated simultaneously according to the discriminative conditional maximum...... likelihood criterion. The HNN can be viewed as an undirected probabilistic independence network (a graphical model), where the neural networks provide a compact representation of the clique functions. An evaluation of the HNN on the task of recognizing broad phoneme classes in the TIMIT database shows clear...

  4. Extracting weights from edge directions to find communities in directed networks

    International Nuclear Information System (INIS)

    Lai, Darong; Lu, Hongtao; Nardini, Christine

    2010-01-01

    Community structures are found to exist ubiquitously in real-world complex networks. We address here the problem of community detection in directed networks. Most of the previous literature ignores edge directions and applies methods designed for community detection in undirected networks, which discards valuable information and often fails when different communities are defined on the basis of incoming and outgoing edges. We suggest extracting information about edge directions using a PageRank random walk and translating such information into edge weights. After extraction we obtain a new weighted directed network in which edge directions can then be safely ignored. We thus transform community detection in directed networks into community detection in reweighted undirected networks. Such an approach can benefit directly from the large volume of algorithms for the detection of communities in undirected networks already developed, since it is not obvious how to extend these algorithms to account for directed networks and the procedure is often difficult. Validations on synthetic and real-world networks demonstrate that the proposed framework can effectively detect communities in directed networks

  5. Relational analysis of CpG islands methylation and gene expression in human lymphomas using possibilistic C-means clustering and modified cluster fuzzy density.

    Science.gov (United States)

    Sjahputera, Ozy; Keller, James M; Davis, J Wade; Taylor, Kristen H; Rahmatpanah, Farahnaz; Shi, Huidong; Anderson, Derek T; Blisard, Samuel N; Luke, Robert H; Popescu, Mihail; Arthur, Gerald C; Caldwell, Charles W

    2007-01-01

    Heterogeneous genetic and epigenetic alterations are commonly found in human non-Hodgkin's lymphomas (NHL). One such epigenetic alteration is aberrant methylation of gene promoter-related CpG islands, where hypermethylation frequently results in transcriptional inactivation of target genes, while a decrease or loss of promoter methylation (hypomethylation) is frequently associated with transcriptional activation. Discovering genes with these relationships in NHL or other types of cancers could lead to a better understanding of the pathobiology of these diseases. The simultaneous analysis of promoter methylation using Differential Methylation Hybridization (DMH) and its associated gene expression using Expressed CpG Island Sequence Tag (ECIST) microarrays generates a large volume of methylation-expression relational data. To analyze this data, we propose a set of algorithms based on fuzzy sets theory, in particular Possibilistic c-Means (PCM) and cluster fuzzy density. For each gene, these algorithms calculate measures of confidence of various methylation-expression relationships in each NHL subclass. Thus, these tools can be used as a means of high volume data exploration to better guide biological confirmation using independent molecular biology methods.

  6. Identification of water quality management policy of watershed system with multiple uncertain interactions using a multi-level-factorial risk-inference-based possibilistic-probabilistic programming approach.

    Science.gov (United States)

    Liu, Jing; Li, Yongping; Huang, Guohe; Fu, Haiyan; Zhang, Junlong; Cheng, Guanhui

    2017-06-01

    In this study, a multi-level-factorial risk-inference-based possibilistic-probabilistic programming (MRPP) method is proposed for supporting water quality management under multiple uncertainties. The MRPP method can handle uncertainties expressed as fuzzy-random-boundary intervals, probability distributions, and interval numbers, and analyze the effects of uncertainties as well as their interactions on modeling outputs. It is applied to plan water quality management in the Xiangxihe watershed. Results reveal that a lower probability of satisfying the objective function (θ) as well as a higher probability of violating environmental constraints (q i ) would correspond to a higher system benefit with an increased risk of violating system feasibility. Chemical plants are the major contributors to biological oxygen demand (BOD) and total phosphorus (TP) discharges; total nitrogen (TN) would be mainly discharged by crop farming. It is also discovered that optimistic decision makers should pay more attention to the interactions between chemical plant and water supply, while decision makers who possess a risk-averse attitude would focus on the interactive effect of q i and benefit of water supply. The findings can help enhance the model's applicability and identify a suitable water quality management policy for environmental sustainability according to the practical situations.

  7. Network epidemiology and plant trade networks.

    Science.gov (United States)

    Pautasso, Marco; Jeger, Mike J

    2014-01-01

    Models of epidemics in complex networks are improving our predictive understanding of infectious disease outbreaks. Nonetheless, applying network theory to plant pathology is still a challenge. This overview summarizes some key developments in network epidemiology that are likely to facilitate its application in the study and management of plant diseases. Recent surveys have provided much-needed datasets on contact patterns and human mobility in social networks, but plant trade networks are still understudied. Human (and plant) mobility levels across the planet are unprecedented-there is thus much potential in the use of network theory by plant health authorities and researchers. Given the directed and hierarchical nature of plant trade networks, there is a need for plant epidemiologists to further develop models based on undirected and homogeneous networks. More realistic plant health scenarios would also be obtained by developing epidemic models in dynamic, rather than static, networks. For plant diseases spread by the horticultural and ornamental trade, there is the challenge of developing spatio-temporal epidemic simulations integrating network data. The use of network theory in plant epidemiology is a promising avenue and could contribute to anticipating and preventing plant health emergencies such as European ash dieback.

  8. Sensitive Dependence of Optimal Network Dynamics on Network Structure

    Directory of Open Access Journals (Sweden)

    Takashi Nishikawa

    2017-11-01

    Full Text Available The relation between network structure and dynamics is determinant for the behavior of complex systems in numerous domains. An important long-standing problem concerns the properties of the networks that optimize the dynamics with respect to a given performance measure. Here, we show that such optimization can lead to sensitive dependence of the dynamics on the structure of the network. Specifically, using diffusively coupled systems as examples, we demonstrate that the stability of a dynamical state can exhibit sensitivity to unweighted structural perturbations (i.e., link removals and node additions for undirected optimal networks and to weighted perturbations (i.e., small changes in link weights for directed optimal networks. As mechanisms underlying this sensitivity, we identify discontinuous transitions occurring in the complement of undirected optimal networks and the prevalence of eigenvector degeneracy in directed optimal networks. These findings establish a unified characterization of networks optimized for dynamical stability, which we illustrate using Turing instability in activator-inhibitor systems, synchronization in power-grid networks, network diffusion, and several other network processes. Our results suggest that the network structure of a complex system operating near an optimum can potentially be fine-tuned for a significantly enhanced stability compared to what one might expect from simple extrapolation. On the other hand, they also suggest constraints on how close to the optimum the system can be in practice. Finally, the results have potential implications for biophysical networks, which have evolved under the competing pressures of optimizing fitness while remaining robust against perturbations.

  9. Network rewiring dynamics with convergence towards a star network.

    Science.gov (United States)

    Whigham, P A; Dick, G; Parry, M

    2016-10-01

    Network rewiring as a method for producing a range of structures was first introduced in 1998 by Watts & Strogatz ( Nature 393 , 440-442. (doi:10.1038/30918)). This approach allowed a transition from regular through small-world to a random network. The subsequent interest in scale-free networks motivated a number of methods for developing rewiring approaches that converged to scale-free networks. This paper presents a rewiring algorithm (RtoS) for undirected, non-degenerate, fixed size networks that transitions from regular, through small-world and scale-free to star-like networks. Applications of the approach to models for the spread of infectious disease and fixation time for a simple genetics model are used to demonstrate the efficacy and application of the approach.

  10. Earthquake Complex Network applied along the Chilean Subduction Zone.

    Science.gov (United States)

    Martin, F.; Pasten, D.; Comte, D.

    2017-12-01

    In recent years the earthquake complex networks have been used as a useful tool to describe and characterize the behavior of seismicity. The earthquake complex network is built in space, dividing the three dimensional space in cubic cells. If the cubic cell contains a hypocenter, we call this cell like a node. The connections between nodes follows the time sequence of the occurrence of the seismic events. In this sense, we have a spatio-temporal configuration of a specific region using the seismicity in that zone. In this work, we are applying complex networks to characterize the subduction zone along the coast of Chile using two networks: a directed and an undirected network. The directed network takes in consideration the time-direction of the connections, that is very important for the connectivity of the network: we are considering the connectivity, ki of the i-th node, like the number of connections going out from the node i and we add the self-connections (if two seismic events occurred successive in time in the same cubic cell, we have a self-connection). The undirected network is the result of remove the direction of the connections and the self-connections from the directed network. These two networks were building using seismic data events recorded by CSN (Chilean Seismological Center) in Chile. This analysis includes the last largest earthquakes occurred in Iquique (April 2014) and in Illapel (September 2015). The result for the directed network shows a change in the value of the critical exponent along the Chilean coast. The result for the undirected network shows a small-world behavior without important changes in the topology of the network. Therefore, the complex network analysis shows a new form to characterize the Chilean subduction zone with a simple method that could be compared with another methods to obtain more details about the behavior of the seismicity in this region.

  11. NEAT: an efficient network enrichment analysis test.

    Science.gov (United States)

    Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C

    2016-09-05

    Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises as the null distribution in this context. NEAT can be applied not only to undirected, but to directed and partially directed networks as well. Our simulations indicate that NEAT is considerably faster than alternative resampling-based methods, and that its capacity to detect enrichments is at least as good as the one of alternative tests. We discuss applications of NEAT to network analyses in yeast by testing for enrichment of the Environmental Stress Response target gene set with GO Slim and KEGG functional gene sets, and also by inspecting associations between functional sets themselves. NEAT is a flexible and efficient test for network enrichment analysis that aims to overcome some limitations of existing resampling-based tests. The method is implemented in the R package neat, which can be freely downloaded from CRAN ( https://cran.r-project.org/package=neat ).

  12. A new fuzzy mathematical model for green supply chain network design

    Directory of Open Access Journals (Sweden)

    Mohsen Sadegh Amalnick

    2017-01-01

    Full Text Available The environmental changes caused by industrial activities have spurred a significant interest in designing supply chain networks by considering environmental issues such as CO2 emission. The pivotal role of taking uncertainty and risk into account in closed-loop supply chain networks has induced numerous researchers and practitioners to develop appropriate decision making tools to cope with these issues in such networks. To design a supply chain regarding environmental impacts under uncertainty of the input data and to cope with the operational risks, this paper proposes a multi objective possibilistic optimization model. The proposed model minimizes traditional costs such as cost of products shipment, purchasing machines and so on, as well as minimizing the environmental impact, and as a results strikes a balance between the two objective functions. Furthermore, in order to solve the proposed multi objective fuzzy mathematical programming model, an interactive fuzzy solution approach is applied. Numerical experiments are used to prove the applicability and feasibility of the developed possibilistic programming model and the usefulness of the applied hybrid solution approach.

  13. An empirical study of an agglomeration network

    International Nuclear Information System (INIS)

    Zhang, Yichao; Zhang, Zhaochun; Guan, Jihong

    2007-01-01

    Recently, researchers have reported many models mimicking real network evolution growth, among which some are based on network aggregation growth. However, until now, relatively few experiments have been reported. Accordingly, in this paper, photomicrographs of real materials (the agglomeration in the filtrate of slurry formed by a GaP-nanoparticle conglomerate dispersed in water) are analyzed within the framework of complex network theory. By data mapping from photomicrographs we generate undirected networks and as a definition of degree we adopt the number of pixel's nearest neighbors while adjacent pixels define a connection or an edge. We study the topological structure of these networks including degree distribution, clustering coefficient and average path length. In addition, we discuss the self-similarity and synchronizability of the networks. We find that the synchronizability of high-concentration agglomeration is better than that of low-concentration agglomeration; we also find that agglomeration networks possess good self-similar features

  14. Directed network modules

    International Nuclear Information System (INIS)

    Palla, Gergely; Farkas, Illes J; Pollner, Peter; Derenyi, Imre; Vicsek, Tamas

    2007-01-01

    A search technique locating network modules, i.e. internally densely connected groups of nodes in directed networks is introduced by extending the clique percolation method originally proposed for undirected networks. After giving a suitable definition for directed modules we investigate their percolation transition in the Erdos-Renyi graph both analytically and numerically. We also analyse four real-world directed networks, including Google's own web-pages, an email network, a word association graph and the transcriptional regulatory network of the yeast Saccharomyces cerevisiae. The obtained directed modules are validated by additional information available for the nodes. We find that directed modules of real-world graphs inherently overlap and the investigated networks can be classified into two major groups in terms of the overlaps between the modules. Accordingly, in the word-association network and Google's web-pages, overlaps are likely to contain in-hubs, whereas the modules in the email and transcriptional regulatory network tend to overlap via out-hubs

  15. Symbolic walk in regular networks

    International Nuclear Information System (INIS)

    Ermann, Leonardo; Carlo, Gabriel G

    2015-01-01

    We find that a symbolic walk (SW)—performed by a walker with memory given by a Bernoulli shift—is able to distinguish between the random or chaotic topology of a given network. We show this result by means of studying the undirected baker network, which is defined by following the Ulam approach for the baker transformation in order to introduce the effect of deterministic chaos into its structure. The chaotic topology is revealed through the central role played by the nodes associated with the positions corresponding to the shortest periodic orbits of the generating map. They are the overwhelmingly most visited nodes in the limit cycles at which the SW asymptotically arrives. Our findings contribute to linking deterministic chaotic dynamics with the properties of networks constructed using the Ulam approach. (paper)

  16. Asymmetric network connectivity using weighted harmonic averages

    Science.gov (United States)

    Morrison, Greg; Mahadevan, L.

    2011-02-01

    We propose a non-metric measure of the "closeness" felt between two nodes in an undirected, weighted graph using a simple weighted harmonic average of connectivity, that is a real-valued Generalized Erdös Number (GEN). While our measure is developed with a collaborative network in mind, the approach can be of use in a variety of artificial and real-world networks. We are able to distinguish between network topologies that standard distance metrics view as identical, and use our measure to study some simple analytically tractable networks. We show how this might be used to look at asymmetry in authorship networks such as those that inspired the integer Erdös numbers in mathematical coauthorships. We also show the utility of our approach to devise a ratings scheme that we apply to the data from the NetFlix prize, and find a significant improvement using our method over a baseline.

  17. Consensus problem in directed networks of multi-agents via nonlinear protocols

    International Nuclear Information System (INIS)

    Liu Xiwei; Chen Tianping; Lu Wenlian

    2009-01-01

    In this Letter, the consensus problem via distributed nonlinear protocols for directed networks is investigated. Its dynamical behaviors are described by ordinary differential equations (ODEs). Based on graph theory, matrix theory and the Lyapunov direct method, some sufficient conditions of nonlinear protocols guaranteeing asymptotical or exponential consensus are presented and rigorously proved. The main contribution of this work is that for nonlinearly coupled networks, we generalize the results for undirected networks to directed networks. Consensus under pinning control technique is also developed here. Simulations are also given to show the validity of the theories.

  18. The Value of Information in Distributed Decision Networks

    Science.gov (United States)

    2016-03-04

    vertex set V is a single agent gathering information Y about a random variable X through a channel of fixed capacity c. The state of the world W can...Constraints We now define a mathematical framework for networks. Let G = (V,E) be an undirected random network (graph) drawn from a known distribution pG, 1...assume two discrete states w1 and w2 with a known probabilities, and the distribution of X depends on W ; that is, X ∼ pi if W = wi where pi belongs

  19. A possibilistic approach for transient identification with 'don't know' response capability optimized by genetic algorithm; Uma abordagem possibilistica para identificacao de transientes, com geracao de resposta 'nao sei', otimizada por algoritmo genetico

    Energy Technology Data Exchange (ETDEWEB)

    Almeida, Jose Carlos S. de [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]. E-mail: jcsa@ien.gov.br; Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear]. E-mail: schirru@cnen.gov.br; Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil)]|[Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia. Programa de Engenharia Nuclear; E-mail: cmnap@ien.gov.br, claudio@lmp.ufrj.br

    2002-07-01

    This work describes a possibilistic approach for transient identification based on the minimum centroids set method, proposed in previous work, optimized by genetic algorithm. The idea behind this method is to split the complex classification problem into small and simple ones, so that the performance in the classification can be increased. In order to accomplish that, a genetic algorithm is used to learn, from realistic simulated data, the optimized time partitions, which the robustness and correctness in the classification are maximized. The use of a possibilistic classification approach propitiates natural and consistent classification rules, leading naturally to a good heuristic to handle the 'don't know 'response, in case of unrecognized transient, which is fairly desirable in transient classification systems where safety is critical. Application of the proposed approach to a nuclear transient indentification problem reveals good capability of the genetic algorithm in learning optimized possibilistic classification rules for efficient diagnosis including 'don't know' response. Obtained results are shown and commented. (author)

  20. Networking

    OpenAIRE

    Rauno Lindholm, Daniel; Boisen Devantier, Lykke; Nyborg, Karoline Lykke; Høgsbro, Andreas; Fries, de; Skovlund, Louise

    2016-01-01

    The purpose of this project was to examine what influencing factor that has had an impact on the presumed increasement of the use of networking among academics on the labour market and how it is expressed. On the basis of the influence from globalization on the labour market it can be concluded that the globalization has transformed the labour market into a market based on the organization of networks. In this new organization there is a greater emphasis on employees having social qualificati...

  1. The construction of an amino acid network for understanding protein structure and function.

    Science.gov (United States)

    Yan, Wenying; Zhou, Jianhong; Sun, Maomin; Chen, Jiajia; Hu, Guang; Shen, Bairong

    2014-06-01

    Amino acid networks (AANs) are undirected networks consisting of amino acid residues and their interactions in three-dimensional protein structures. The analysis of AANs provides novel insight into protein science, and several common amino acid network properties have revealed diverse classes of proteins. In this review, we first summarize methods for the construction and characterization of AANs. We then compare software tools for the construction and analysis of AANs. Finally, we review the application of AANs for understanding protein structure and function, including the identification of functional residues, the prediction of protein folding, analyzing protein stability and protein-protein interactions, and for understanding communication within and between proteins.

  2. Competitive Dynamics on Complex Networks

    Science.gov (United States)

    Zhao, Jiuhua; Liu, Qipeng; Wang, Xiaofan

    2014-07-01

    We consider a dynamical network model in which two competitors have fixed and different states, and each normal agent adjusts its state according to a distributed consensus protocol. The state of each normal agent converges to a steady value which is a convex combination of the competitors' states, and is independent of the initial states of agents. This implies that the competition result is fully determined by the network structure and positions of competitors in the network. We compute an Influence Matrix (IM) in which each element characterizing the influence of an agent on another agent in the network. We use the IM to predict the bias of each normal agent and thus predict which competitor will win. Furthermore, we compare the IM criterion with seven node centrality measures to predict the winner. We find that the competitor with higher Katz Centrality in an undirected network or higher PageRank in a directed network is most likely to be the winner. These findings may shed new light on the role of network structure in competition and to what extent could competitors adjust network structure so as to win the competition.

  3. Detecting communities by asymmetric intimacy in directed-weighted network

    Science.gov (United States)

    Wang, Xingyuan; Qin, Xiaomeng

    Community detection and analysis have attracted wide public concerns over the recent years. Meanwhile, many related algorithms in complex networks have been proposed. However, most of them concentrate on undirected and unweighted networks. Concerning the significant theoretical value and potential application foreground for directed-weighted networks, in this paper, a novel hierarchical communities detection algorithm (termed as DCBAI) has been proposed on the basis of asymmetric intimacy between nodes. Community structures are effectively detected by node clustering algorithm in directed-weighted network, and a set of optimal communities are generated. In addition, a new and asymmetric parameter is adopted to measure the intimate relationship between nodes. We make some simulation using the proposed algorithm in real-world networks and artificial networks, and the result obtained proves that the parameter can describe the direct and indirect relationships between two nodes. Eventually, comparison with similar algorithms shows that our proposed algorithm has better performance.

  4. Identification of important nodes in directed biological networks: a network motif approach.

    Directory of Open Access Journals (Sweden)

    Pei Wang

    Full Text Available Identification of important nodes in complex networks has attracted an increasing attention over the last decade. Various measures have been proposed to characterize the importance of nodes in complex networks, such as the degree, betweenness and PageRank. Different measures consider different aspects of complex networks. Although there are numerous results reported on undirected complex networks, few results have been reported on directed biological networks. Based on network motifs and principal component analysis (PCA, this paper aims at introducing a new measure to characterize node importance in directed biological networks. Investigations on five real-world biological networks indicate that the proposed method can robustly identify actually important nodes in different networks, such as finding command interneurons, global regulators and non-hub but evolutionary conserved actually important nodes in biological networks. Receiver Operating Characteristic (ROC curves for the five networks indicate remarkable prediction accuracy of the proposed measure. The proposed index provides an alternative complex network metric. Potential implications of the related investigations include identifying network control and regulation targets, biological networks modeling and analysis, as well as networked medicine.

  5. Potential theory for directed networks.

    Directory of Open Access Journals (Sweden)

    Qian-Ming Zhang

    Full Text Available Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i We propose a new mechanism for the local organization of directed networks; (ii We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation.

  6. Potential Theory for Directed Networks

    Science.gov (United States)

    Zhang, Qian-Ming; Lü, Linyuan; Wang, Wen-Qiang; Zhou, Tao

    2013-01-01

    Uncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are less understood than those of undirected networks. This article proposes a hypothesis named potential theory, which assumes that every directed link corresponds to a decrease of a unit potential and subgraphs with definable potential values for all nodes are preferred. Combining the potential theory with the clustering and homophily mechanisms, it is deduced that the Bi-fan structure consisting of 4 nodes and 4 directed links is the most favored local structure in directed networks. Our hypothesis receives strongly positive supports from extensive experiments on 15 directed networks drawn from disparate fields, as indicated by the most accurate and robust performance of Bi-fan predictor within the link prediction framework. In summary, our main contribution is twofold: (i) We propose a new mechanism for the local organization of directed networks; (ii) We design the corresponding link prediction algorithm, which can not only testify our hypothesis, but also find out direct applications in missing link prediction and friendship recommendation. PMID:23408979

  7. Analysis of the enzyme network involved in cattle milk production using graph theory.

    Science.gov (United States)

    Ghorbani, Sholeh; Tahmoorespur, Mojtaba; Masoudi Nejad, Ali; Nasiri, Mohammad; Asgari, Yazdan

    2015-06-01

    Understanding cattle metabolism and its relationship with milk products is important in bovine breeding. A systemic view could lead to consequences that will result in a better understanding of existing concepts. Topological indices and quantitative characterizations mostly result from the application of graph theory on biological data. In the present work, the enzyme network involved in cattle milk production was reconstructed and analyzed based on available bovine genome information using several public datasets (NCBI, Uniprot, KEGG, and Brenda). The reconstructed network consisted of 3605 reactions named by KEGG compound numbers and 646 enzymes that catalyzed the corresponding reactions. The characteristics of the directed and undirected network were analyzed using Graph Theory. The mean path length was calculated to be4.39 and 5.41 for directed and undirected networks, respectively. The top 11 hub enzymes whose abnormality could harm bovine health and reduce milk production were determined. Therefore, the aim of constructing the enzyme centric network was twofold; first to find out whether such network followed the same properties of other biological networks, and second, to find the key enzymes. The results of the present study can improve our understanding of milk production in cattle. Also, analysis of the enzyme network can help improve the modeling and simulation of biological systems and help design desired phenotypes to increase milk production quality or quantity.

  8. Mining Important Nodes in Directed Weighted Complex Networks

    Directory of Open Access Journals (Sweden)

    Yunyun Yang

    2017-01-01

    Full Text Available In complex networks, mining important nodes has been a matter of concern by scholars. In recent years, scholars have focused on mining important nodes in undirected unweighted complex networks. But most of the methods are not applicable to directed weighted complex networks. Therefore, this paper proposes a Two-Way-PageRank method based on PageRank for further discussion of mining important nodes in directed weighted complex networks. We have mainly considered the frequency of contact between nodes and the length of time of contact between nodes. We have considered the source of the nodes (in-degree and the whereabouts of the nodes (out-degree simultaneously. We have given node important performance indicators. Through numerical examples, we analyze the impact of variation of some parameters on node important performance indicators. Finally, the paper has verified the accuracy and validity of the method through empirical network data.

  9. The functional consequences of mutualistic network architecture.

    Directory of Open Access Journals (Sweden)

    José M Gómez

    Full Text Available The architecture and properties of many complex networks play a significant role in the functioning of the systems they describe. Recently, complex network theory has been applied to ecological entities, like food webs or mutualistic plant-animal interactions. Unfortunately, we still lack an accurate view of the relationship between the architecture and functioning of ecological networks. In this study we explore this link by building individual-based pollination networks from eight Erysimum mediohispanicum (Brassicaceae populations. In these individual-based networks, each individual plant in a population was considered a node, and was connected by means of undirected links to conspecifics sharing pollinators. The architecture of these unipartite networks was described by means of nestedness, connectivity and transitivity. Network functioning was estimated by quantifying the performance of the population described by each network as the number of per-capita juvenile plants produced per population. We found a consistent relationship between the topology of the networks and their functioning, since variation across populations in the average per-capita production of juvenile plants was positively and significantly related with network nestedness, connectivity and clustering. Subtle changes in the composition of diverse pollinator assemblages can drive major consequences for plant population performance and local persistence through modifications in the structure of the inter-plant pollination networks.

  10. Role models for complex networks

    Science.gov (United States)

    Reichardt, J.; White, D. R.

    2007-11-01

    We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

  11. Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

    Science.gov (United States)

    Quintanilla-Domínguez, Joel; Ojeda-Magaña, Benjamín; Marcano-Cedeño, Alexis; Cortina-Januchs, María G.; Vega-Corona, Antonio; Andina, Diego

    2011-12-01

    A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection.

  12. Generalised power graph compression reveals dominant relationship patterns in complex networks.

    Science.gov (United States)

    Ahnert, Sebastian E

    2014-03-25

    We introduce a framework for the discovery of dominant relationship patterns in complex networks, by compressing the networks into power graphs with overlapping power nodes. When paired with enrichment analysis of node classification terms, the most compressible sets of edges provide a highly informative sketch of the dominant relationship patterns that define the network. In addition, this procedure also gives rise to a novel, link-based definition of overlapping node communities in which nodes are defined by their relationships with sets of other nodes, rather than through connections within the community. We show that this completely general approach can be applied to undirected, directed, and bipartite networks, yielding valuable insights into the large-scale structure of real-world networks, including social networks and food webs. Our approach therefore provides a novel way in which network architecture can be studied, defined and classified.

  13. Fractional quantum mechanics on networks: Long-range dynamics and quantum transport.

    Science.gov (United States)

    Riascos, A P; Mateos, José L

    2015-11-01

    In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

  14. A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

    Science.gov (United States)

    Goekoop, Rutger; Goekoop, Jaap G

    2014-01-01

    The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. To examine the ability of network community detection (NCD) to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS). Principal component analysis (PCA) was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS). An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS) was optimized using a previously published technique. In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "Depression", "Mania", "Anxiety", "Psychosis", "Retardation", and "Behavioral Disorganization". Network metrics were used to quantify the continuities between the elementary syndromes. We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a 'Psychopathology Web'. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.

  15. A network view on psychiatric disorders: network clusters of symptoms as elementary syndromes of psychopathology.

    Directory of Open Access Journals (Sweden)

    Rutger Goekoop

    Full Text Available INTRODUCTION: The vast number of psychopathological syndromes that can be observed in clinical practice can be described in terms of a limited number of elementary syndromes that are differentially expressed. Previous attempts to identify elementary syndromes have shown limitations that have slowed progress in the taxonomy of psychiatric disorders. AIM: To examine the ability of network community detection (NCD to identify elementary syndromes of psychopathology and move beyond the limitations of current classification methods in psychiatry. METHODS: 192 patients with unselected mental disorders were tested on the Comprehensive Psychopathological Rating Scale (CPRS. Principal component analysis (PCA was performed on the bootstrapped correlation matrix of symptom scores to extract the principal component structure (PCS. An undirected and weighted network graph was constructed from the same matrix. Network community structure (NCS was optimized using a previously published technique. RESULTS: In the optimal network structure, network clusters showed a 89% match with principal components of psychopathology. Some 6 network clusters were found, including "Depression", "Mania", "Anxiety", "Psychosis", "Retardation", and "Behavioral Disorganization". Network metrics were used to quantify the continuities between the elementary syndromes. CONCLUSION: We present the first comprehensive network graph of psychopathology that is free from the biases of previous classifications: a 'Psychopathology Web'. Clusters within this network represent elementary syndromes that are connected via a limited number of bridge symptoms. Many problems of previous classifications can be overcome by using a network approach to psychopathology.

  16. Advanced mobile networking, sensing, and controls.

    Energy Technology Data Exchange (ETDEWEB)

    Feddema, John Todd; Kilman, Dominique Marie; Byrne, Raymond Harry; Young, Joseph G.; Lewis, Christopher L.; Van Leeuwen, Brian P.; Robinett, Rush D. III; Harrington, John J.

    2005-03-01

    This report describes an integrated approach for designing communication, sensing, and control systems for mobile distributed systems. Graph theoretic methods are used to analyze the input/output reachability and structural controllability and observability of a decentralized system. Embedded in each network node, this analysis will automatically reconfigure an ad hoc communication network for the sensing and control task at hand. The graph analysis can also be used to create the optimal communication flow control based upon the spatial distribution of the network nodes. Edge coloring algorithms tell us that the minimum number of time slots in a planar network is equal to either the maximum number of adjacent nodes (or degree) of the undirected graph plus some small number. Therefore, the more spread out that the nodes are, the fewer number of time slots are needed for communication, and the smaller the latency between nodes. In a coupled system, this results in a more responsive sensor network and control system. Network protocols are developed to propagate this information, and distributed algorithms are developed to automatically adjust the number of time slots available for communication. These protocols and algorithms must be extremely efficient and only updated as network nodes move. In addition, queuing theory is used to analyze the delay characteristics of Carrier Sense Multiple Access (CSMA) networks. This report documents the analysis, simulation, and implementation of these algorithms performed under this Laboratory Directed Research and Development (LDRD) effort.

  17. PhysarumSpreader: A New Bio-Inspired Methodology for Identifying Influential Spreaders in Complex Networks.

    Science.gov (United States)

    Wang, Hongping; Zhang, Yajuan; Zhang, Zili; Mahadevan, Sankaran; Deng, Yong

    2015-01-01

    Identifying influential spreaders in networks, which contributes to optimizing the use of available resources and efficient spreading of information, is of great theoretical significance and practical value. A random-walk-based algorithm LeaderRank has been shown as an effective and efficient method in recognizing leaders in social network, which even outperforms the well-known PageRank method. As LeaderRank is initially developed for binary directed networks, further extensions should be studied in weighted networks. In this paper, a generalized algorithm PhysarumSpreader is proposed by combining LeaderRank with a positive feedback mechanism inspired from an amoeboid organism called Physarum Polycephalum. By taking edge weights into consideration and adding the positive feedback mechanism, PhysarumSpreader is applicable in both directed and undirected networks with weights. By taking two real networks for examples, the effectiveness of the proposed method is demonstrated by comparing with other standard centrality measures.

  18. PhysarumSpreader: A New Bio-Inspired Methodology for Identifying Influential Spreaders in Complex Networks.

    Directory of Open Access Journals (Sweden)

    Hongping Wang

    Full Text Available Identifying influential spreaders in networks, which contributes to optimizing the use of available resources and efficient spreading of information, is of great theoretical significance and practical value. A random-walk-based algorithm LeaderRank has been shown as an effective and efficient method in recognizing leaders in social network, which even outperforms the well-known PageRank method. As LeaderRank is initially developed for binary directed networks, further extensions should be studied in weighted networks. In this paper, a generalized algorithm PhysarumSpreader is proposed by combining LeaderRank with a positive feedback mechanism inspired from an amoeboid organism called Physarum Polycephalum. By taking edge weights into consideration and adding the positive feedback mechanism, PhysarumSpreader is applicable in both directed and undirected networks with weights. By taking two real networks for examples, the effectiveness of the proposed method is demonstrated by comparing with other standard centrality measures.

  19. Link Prediction in Directed Network and Its Application in Microblog

    Directory of Open Access Journals (Sweden)

    Yan Yu

    2014-01-01

    Full Text Available Link prediction tries to infer the likelihood of the existence of a link between two nodes in a network. It has important theoretical and practical value. To date, many link prediction algorithms have been proposed. However, most of these studies assumed that links of network are undirected. In this paper, we focus on link prediction in directed networks. We provide an efficient and effective link prediction method, which consists of three steps as follows: (1 we locate the similar nodes of a target node; (2 we identify candidates that the similar nodes link to; and (3 we rank candidates using weighing schemes. We conduct experiments to evaluate the accuracy of our proposed method using real microblog data. The experimental results show that the proposed method is promising.

  20. Asygnosis and asygnotic networks

    Directory of Open Access Journals (Sweden)

    Edward M. Roche

    2016-05-01

    Full Text Available The purpose of this paper is to create a dialogue between disparate academic disciplines around the topics of decision making, human communication networks, and information exchange. The emergence of modern telecommunications, including social media, gaming platforms, and instant messaging has enabled the emergence of massive online global communities numbering into the tens and hundreds of millions of persons regardless of culture and language capable of exchanging ideas, images, and impressions in real time. The unprecedented scope and scale of these networks challenges contemporary theories in management and decision making, political organization and governance of institutions, sociology, and communications. Our argument is that these theories are outdated and must be rethought. We propose a simple model, "asygnosis", in which decisions and strategies are the product of the continuous (non-discrete flows of information, ideas and impressions (“memes” along ever-changing communication pathways between individuals and/or machines. These networks reflect the undirected emergence, exchange and demise of knowledge that forms around a specific idea or activity. They challenge traditional assumptions about rationality, causality, and the use of organizational structures as control mechanisms which form the basis of most social, economic and political theories. After developing the concept in detail of asyngnosis and asyngnotic networks, we apply it to current issues including unpredictable events that takes place without direct control such as the rise of spontaneous terrorism, and other social and political phenomenon such as the Arab Spring and Occupy Wall Street. Finally, the paper suggests areas of future research in a number of disciplines that might help develop the concept further, test assumptions, and lead to new insights into this emerging phenomenon.

  1. The generation of random directed networks with prescribed 1-node and 2-node degree correlations

    Energy Technology Data Exchange (ETDEWEB)

    Zamora-Lopez, Gorka; Kurths, Juergen [Institute of Physics, University of Potsdam, PO Box 601553, 14415 Potsdam (Germany); Zhou Changsong [Department of Physics, Hong Kong Baptist University, Kowloon Tong, Hong Kong (China); Zlatic, Vinko [Rudjer Boskovic Institute, PO Box 180, HR-10002 Zagreb (Croatia)

    2008-06-06

    The generation of random networks is a very common problem in complex network research. In this paper, we have studied the correlation nature of several real networks and found that, typically, a large number of links are deterministic, i.e. they cannot be randomized. This finding permits fast generation of ensembles of maximally random networks with prescribed 1-node and 2-node degree correlations. When the introduction of self-loops or multiple-links are not desired, random network generation methods typically reach blocked states. Here, a mechanism is proposed, the 'force-and-drop' method, to overcome such states. Our algorithm can be easily simplified for undirected graphs and reduced to account for any subclass of 2-node degree correlations.

  2. Structural Modeling and Characteristics Analysis of Flow Interaction Networks in the Internet

    International Nuclear Information System (INIS)

    Wu Xiao-Yu; Gu Ren-Tao; Pan Zhuo-Ya; Jin Wei-Qi; Ji Yue-Feng

    2015-01-01

    Applying network duality and elastic mechanics, we investigate the interactions among Internet flows by constructing a weighted undirected network, where the vertices and the edges represent the flows and the mutual dependence between flows, respectively. Based on the obtained flow interaction network, we find the existence of ‘super flow’ in the Internet, indicating that some flows have a great impact on a huge number of other flows; moreover, one flow can spread its influence to another through a limited quantity of flows (less than 5 in the experimental simulations), which shows strong small-world characteristics like the social network. To reflect the flow interactions in the physical network congestion evaluation, the ‘congestion coefficient’ is proposed as a new metric which shows a finer observation on congestion than the conventional one. (paper)

  3. Complex interdependent supply chain networks: Cascading failure and robustness

    Science.gov (United States)

    Tang, Liang; Jing, Ke; He, Jie; Stanley, H. Eugene

    2016-02-01

    A supply chain network is a typical interdependent network composed of an undirected cyber-layer network and a directed physical-layer network. To analyze the robustness of this complex interdependent supply chain network when it suffers from disruption events that can cause nodes to fail, we use a cascading failure process that focuses on load propagation. We consider load propagation via connectivity links as node failure spreads through one layer of an interdependent network, and we develop a priority redistribution strategy for failed loads subject to flow constraint. Using a giant component function and a one-to-one directed interdependence relation between nodes in a cyber-layer network and physical-layer network, we construct time-varied functional equations to quantify the dynamic process of failed loads propagation in an interdependent network. Finally, we conduct a numerical simulation for two cases, i.e., single node removal and multiple node removal at the initial disruption. The simulation results show that when we increase the number of removed nodes in an interdependent supply chain network its robustness undergoes a first-order discontinuous phase transition, and that even removing a small number of nodes will cause it to crash.

  4. Covering the Monitoring Network: A Unified Framework to Protect E-Commerce Security

    Directory of Open Access Journals (Sweden)

    Lirong Qiu

    2017-01-01

    Full Text Available Multimedia applications in smart electronic commerce (e-commerce, such as online trading and Internet marketing, always face security in storage and transmission of digital images and videos. This study addresses the problem of security in e-commerce and proposes a unified framework to analyze the security data. First, to allocate the definite security resources optimally, we build our e-commerce monitoring model as an undirected network, where a monitored node is a vertex of the graph and a connection between vertices is an undirected edge. Moreover, we aim to find a minimal cover for the monitoring network as the optimal solution of resource allocation, which is defined as the network monitoring minimization problem (NMM. This problem is proved to be NP-hard. Second, by analyzing the latent threats, we design a novel and trusted monitoring system that can integrate incident monitoring, data analysis, risk assessment, and security warnings. This system does not touch users’ privacy data. Third, we propose a sequential model-based risk assessment method, which can predict the risk according to the text semantics. Our experimental results on web scale data demonstrate that our system is flexible enough when monitoring, which also verify the effectiveness and efficiency of our system.

  5. Node-pair reliability of network systems with small distances between adjacent nodes

    International Nuclear Information System (INIS)

    Malinowski, Jacek

    2007-01-01

    A new method for computing the node-pair reliability of network systems modeled by random graphs with nodes arranged in sequence is presented. It is based on a recursive algorithm using the 'sliding window' technique, the window being composed of several consecutive nodes. In a single step, the connectivity probabilities for all nodes included in the window are found. Subsequently, the window is moved one node forward. This process is repeated until, in the last step, the window reaches the terminal node. The connectivity probabilities found at that point are used to compute the node-pair reliability of the network system considered. The algorithm is designed especially for graphs with small distances between adjacent nodes, where the distance between two nodes is defined as the absolute value of the difference between the nodes' numbers. The maximal distance between any two adjacent nodes is denoted by Γ(G), where G symbolizes a random graph. If Γ(G)=2 then the method can be applied for directed as well as undirected graphs whose nodes and edges are subject to failure. This is important in view of the fact that many algorithms computing network reliability are designed for graphs with failure-prone edges and reliable nodes. If Γ(G)=3 then the method's applicability is limited to undirected graphs with reliable nodes. The main asset of the presented algorithms is their low numerical complexity-O(n), where n denotes the number of nodes

  6. Learning document semantic representation with hybrid deep belief network.

    Science.gov (United States)

    Yan, Yan; Yin, Xu-Cheng; Li, Sujian; Yang, Mingyuan; Hao, Hong-Wei

    2015-01-01

    High-level abstraction, for example, semantic representation, is vital for document classification and retrieval. However, how to learn document semantic representation is still a topic open for discussion in information retrieval and natural language processing. In this paper, we propose a new Hybrid Deep Belief Network (HDBN) which uses Deep Boltzmann Machine (DBM) on the lower layers together with Deep Belief Network (DBN) on the upper layers. The advantage of DBM is that it employs undirected connection when training weight parameters which can be used to sample the states of nodes on each layer more successfully and it is also an effective way to remove noise from the different document representation type; the DBN can enhance extract abstract of the document in depth, making the model learn sufficient semantic representation. At the same time, we explore different input strategies for semantic distributed representation. Experimental results show that our model using the word embedding instead of single word has better performance.

  7. Designing a capacitated multi-configuration logistics network under disturbances and parameter uncertainty: a real-world case of a drug supply chain

    Science.gov (United States)

    Shishebori, Davood; Babadi, Abolghasem Yousefi

    2018-03-01

    This study investigates the reliable multi-configuration capacitated logistics network design problem (RMCLNDP) under system disturbances, which relates to locating facilities, establishing transportation links, and also allocating their limited capacities to the customers conducive to provide their demand on the minimum expected total cost (including locating costs, link constructing costs, and also expected costs in normal and disturbance conditions). In addition, two types of risks are considered; (I) uncertain environment, (II) system disturbances. A two-level mathematical model is proposed for formulating of the mentioned problem. Also, because of the uncertain parameters of the model, an efficacious possibilistic robust optimization approach is utilized. To evaluate the model, a drug supply chain design (SCN) is studied. Finally, an extensive sensitivity analysis was done on the critical parameters. The obtained results show that the efficiency of the proposed approach is suitable and is worthwhile for analyzing the real practical problems.

  8. On Directed Edge-Disjoint Spanning Trees in Product Networks, An Algorithmic Approach

    Directory of Open Access Journals (Sweden)

    A.R. Touzene

    2014-12-01

    Full Text Available In (Ku et al. 2003, the authors have proposed a construction of edge-disjoint spanning trees EDSTs in undirected product networks. Their construction method focuses more on showing the existence of a maximum number (n1+n2-1 of EDSTs in product network of two graphs, where factor graphs have respectively n1 and n2 EDSTs. In this paper, we propose a new systematic and algorithmic approach to construct (n1+n2 directed routed EDST in the product networks. The direction of an edge is added to support bidirectional links in interconnection networks. Our EDSTs can be used straightforward to develop efficient collective communication algorithms for both models store-and-forward and wormhole.

  9. Alignment and integration of complex networks by hypergraph-based spectral clustering

    Science.gov (United States)

    Michoel, Tom; Nachtergaele, Bruno

    2012-11-01

    Complex networks possess a rich, multiscale structure reflecting the dynamical and functional organization of the systems they model. Often there is a need to analyze multiple networks simultaneously, to model a system by more than one type of interaction, or to go beyond simple pairwise interactions, but currently there is a lack of theoretical and computational methods to address these problems. Here we introduce a framework for clustering and community detection in such systems using hypergraph representations. Our main result is a generalization of the Perron-Frobenius theorem from which we derive spectral clustering algorithms for directed and undirected hypergraphs. We illustrate our approach with applications for local and global alignment of protein-protein interaction networks between multiple species, for tripartite community detection in folksonomies, and for detecting clusters of overlapping regulatory pathways in directed networks.

  10. Evolution of Linux operating system network

    Science.gov (United States)

    Xiao, Guanping; Zheng, Zheng; Wang, Haoqin

    2017-01-01

    Linux operating system (LOS) is a sophisticated man-made system and one of the most ubiquitous operating systems. However, there is little research on the structure and functionality evolution of LOS from the prospective of networks. In this paper, we investigate the evolution of the LOS network. 62 major releases of LOS ranging from versions 1.0 to 4.1 are modeled as directed networks in which functions are denoted by nodes and function calls are denoted by edges. It is found that the size of the LOS network grows almost linearly, while clustering coefficient monotonically decays. The degree distributions are almost the same: the out-degree follows an exponential distribution while both in-degree and undirected degree follow power-law distributions. We further explore the functionality evolution of the LOS network. It is observed that the evolution of functional modules is shown as a sequence of seven events (changes) succeeding each other, including continuing, growth, contraction, birth, splitting, death and merging events. By means of a statistical analysis of these events in the top 4 largest components (i.e., arch, drivers, fs and net), it is shown that continuing, growth and contraction events occupy more than 95% events. Our work exemplifies a better understanding and describing of the dynamics of LOS evolution.

  11. Size reduction of complex networks preserving modularity

    International Nuclear Information System (INIS)

    Arenas, A; Duch, J; Fernandez, A; Gomez, S

    2007-01-01

    The ubiquity of modular structure in real-world complex networks is the focus of attention in many trials to understand the interplay between network topology and functionality. The best approaches to the identification of modular structure are based on the optimization of a quality function known as modularity. However this optimization is a hard task provided that the computational complexity of the problem is in the non-deterministic polynomial-time hard (NP-hard) class. Here we propose an exact method for reducing the size of weighted (directed and undirected) complex networks while maintaining their modularity. This size reduction allows use of heuristic algorithms that optimize modularity for a better exploration of the modularity landscape. We compare the modularity obtained in several real complex-networks by using the extremal optimization algorithm, before and after the size reduction, showing the improvement obtained. We speculate that the proposed analytical size reduction could be extended to an exact coarse graining of the network in the scope of real-space renormalization

  12. Opinion control in complex networks

    Science.gov (United States)

    Masuda, Naoki

    2015-03-01

    In many political elections, the electorate appears to be a composite of partisan and independent voters. Given that partisans are not likely to convert to a different party, an important goal for a political party could be to mobilize independent voters toward the party with the help of strong leadership, mass media, partisans, and the effects of peer-to-peer influence. Based on the exact solution of classical voter model dynamics in the presence of perfectly partisan voters (i.e., zealots), we propose a computational method that uses pinning control strategy to maximize the share of a party in a social network of independent voters. The party, corresponding to the controller or zealots, optimizes the nodes to be controlled given the information about the connectivity of independent voters and the set of nodes that the opposing party controls. We show that controlling hubs is generally a good strategy, but the optimized strategy is even better. The superiority of the optimized strategy is particularly eminent when the independent voters are connected as directed (rather than undirected) networks.

  13. Dimensionality reduction and spectral properties of multilayer networks

    Science.gov (United States)

    Sánchez-García, Rubén J.; Cozzo, Emanuele; Moreno, Yamir

    2014-05-01

    Network representations are useful for describing the structure of a large variety of complex systems. Although most studies of real-world networks suppose that nodes are connected by only a single type of edge, most natural and engineered systems include multiple subsystems and layers of connectivity. This new paradigm has attracted a great deal of attention and one fundamental challenge is to characterize multilayer networks both structurally and dynamically. One way to address this question is to study the spectral properties of such networks. Here we apply the framework of graph quotients, which occurs naturally in this context, and the associated eigenvalue interlacing results to the adjacency and Laplacian matrices of undirected multilayer networks. Specifically, we describe relationships between the eigenvalue spectra of multilayer networks and their two most natural quotients, the network of layers and the aggregate network, and show the dynamical implications of working with either of the two simplified representations. Our work thus contributes in particular to the study of dynamical processes whose critical properties are determined by the spectral properties of the underlying network.

  14. Blockmodeling techniques for complex networks

    Science.gov (United States)

    Ball, Brian Joseph

    The class of network models known as stochastic blockmodels has recently been gaining popularity. In this dissertation, we present new work that uses blockmodels to answer questions about networks. We create a blockmodel based on the idea of link communities, which naturally gives rise to overlapping vertex communities. We derive a fast and accurate algorithm to fit the model to networks. This model can be related to another blockmodel, which allows the method to efficiently find nonoverlapping communities as well. We then create a heuristic based on the link community model whose use is to find the correct number of communities in a network. The heuristic is based on intuitive corrections to likelihood ratio tests. It does a good job finding the correct number of communities in both real networks and synthetic networks generated from the link communities model. Two commonly studied types of networks are citation networks, where research papers cite other papers, and coauthorship networks, where authors are connected if they've written a paper together. We study a multi-modal network from a large dataset of Physics publications that is the combination of the two, allowing for directed links between papers as citations, and an undirected edge between a scientist and a paper if they helped to write it. This allows for new insights on the relation between social interaction and scientific production. We also have the publication dates of papers, which lets us track our measures over time. Finally, we create a stochastic model for ranking vertices in a semi-directed network. The probability of connection between two vertices depends on the difference of their ranks. When this model is fit to high school friendship networks, the ranks appear to correspond with a measure of social status. Students have reciprocated and some unreciprocated edges with other students of closely similar rank that correspond to true friendship, and claim an aspirational friendship with a much

  15. Exploring community structure in biological networks with random graphs

    Science.gov (United States)

    2014-01-01

    Background Community structure is ubiquitous in biological networks. There has been an increased interest in unraveling the community structure of biological systems as it may provide important insights into a system’s functional components and the impact of local structures on dynamics at a global scale. Choosing an appropriate community detection algorithm to identify the community structure in an empirical network can be difficult, however, as the many algorithms available are based on a variety of cost functions and are difficult to validate. Even when community structure is identified in an empirical system, disentangling the effect of community structure from other network properties such as clustering coefficient and assortativity can be a challenge. Results Here, we develop a generative model to produce undirected, simple, connected graphs with a specified degrees and pattern of communities, while maintaining a graph structure that is as random as possible. Additionally, we demonstrate two important applications of our model: (a) to generate networks that can be used to benchmark existing and new algorithms for detecting communities in biological networks; and (b) to generate null models to serve as random controls when investigating the impact of complex network features beyond the byproduct of degree and modularity in empirical biological networks. Conclusion Our model allows for the systematic study of the presence of community structure and its impact on network function and dynamics. This process is a crucial step in unraveling the functional consequences of the structural properties of biological systems and uncovering the mechanisms that drive these systems. PMID:24965130

  16. Biological network analysis with CentiScaPe: centralities and experimental dataset integration [v2; ref status: indexed, http://f1000r.es/55u

    Directory of Open Access Journals (Sweden)

    Giovanni Scardoni

    2015-07-01

    Full Text Available The growing dimension and complexity of the available experimental data generating biological networks have increased the need for tools that help in categorizing nodes by their topological relevance. Here we present CentiScaPe, a Cytoscape app specifically designed to calculate centrality indexes used for the identification of the most important nodes in a network. CentiScaPe is a comprehensive suite of algorithms dedicated to network nodes centrality analysis, computing several centralities for undirected, directed and weighted networks. The results of the topological analysis can be integrated with data set from lab experiments, like expression or phosphorylation levels for each protein represented in the network. Our app opens new perspectives in the analysis of biological networks, since the integration of topological analysis with lab experimental data enhance the predictive power of the bioinformatics analysis.

  17. Robustness of complex networks with both unidirectional and bidirectional links against cascading failures

    Science.gov (United States)

    Ding, Lin; Leung, Victor C. M.; Tan, Min-Sheng

    2017-09-01

    The robustness of complex networks against cascading failures has been of great interest, while most of the researchers have considered undirected networks. However, to be more realistic, a part of links of many real systems should be described as unidirectional. In this paper, by applying three link direction-determining (DD) strategies, the tolerance of cascading failures is investigated in various networks with both unidirectional and bidirectional links. By extending the utilization of a classical global betweenness method, we propose a new cascading model, taking into account the weights of nodes and the directions of links. Then, the effects of unidirectional links on the network robustness against cascaded attacks are examined under the global load-based distribution mechanism. The simulation results show that the link-directed methods could not always lead to the decrease of the network robustness as indicated in the previous studies. For small-world networks, these methods certainly make the network weaker. However, for scale-free networks, the network robustness can be significantly improved by the link-directed method, especially for the method with non-random DD strategies. These results are independent of the weight parameter of the nodes. Due to the strongly improved robustness and easy realization with low cost on networks, the method for enforcing proper links to the unidirectional ones may be useful for leading to insights into the control of cascading failures in real-world networks, like communication and transportation networks.

  18. Motif structure and cooperation in real-world complex networks

    Science.gov (United States)

    Salehi, Mostafa; Rabiee, Hamid R.; Jalili, Mahdi

    2010-12-01

    Networks of dynamical nodes serve as generic models for real-world systems in many branches of science ranging from mathematics to physics, technology, sociology and biology. Collective behavior of agents interacting over complex networks is important in many applications. The cooperation between selfish individuals is one of the most interesting collective phenomena. In this paper we address the interplay between the motifs’ cooperation properties and their abundance in a number of real-world networks including yeast protein-protein interaction, human brain, protein structure, email communication, dolphins’ social interaction, Zachary karate club and Net-science coauthorship networks. First, the amount of cooperativity for all possible undirected subgraphs with three to six nodes is calculated. To this end, the evolutionary dynamics of the Prisoner’s Dilemma game is considered and the cooperativity of each subgraph is calculated as the percentage of cooperating agents at the end of the simulation time. Then, the three- to six-node motifs are extracted for each network. The significance of the abundance of a motif, represented by a Z-value, is obtained by comparing them with some properly randomized versions of the original network. We found that there is always a group of motifs showing a significant inverse correlation between their cooperativity amount and Z-value, i.e. the more the Z-value the less the amount of cooperativity. This suggests that networks composed of well-structured units do not have good cooperativity properties.

  19. Optimal localization of diffusion sources in complex networks

    Science.gov (United States)

    Hu, Zhao-Long; Han, Xiao; Lai, Ying-Cheng; Wang, Wen-Xu

    2017-04-01

    Locating sources of diffusion and spreading from minimum data is a significant problem in network science with great applied values to the society. However, a general theoretical framework dealing with optimal source localization is lacking. Combining the controllability theory for complex networks and compressive sensing, we develop a framework with high efficiency and robustness for optimal source localization in arbitrary weighted networks with arbitrary distribution of sources. We offer a minimum output analysis to quantify the source locatability through a minimal number of messenger nodes that produce sufficient measurement for fully locating the sources. When the minimum messenger nodes are discerned, the problem of optimal source localization becomes one of sparse signal reconstruction, which can be solved using compressive sensing. Application of our framework to model and empirical networks demonstrates that sources in homogeneous and denser networks are more readily to be located. A surprising finding is that, for a connected undirected network with random link weights and weak noise, a single messenger node is sufficient for locating any number of sources. The framework deepens our understanding of the network source localization problem and offers efficient tools with broad applications.

  20. Hopping in the Crowd to Unveil Network Topology

    Science.gov (United States)

    Asllani, Malbor; Carletti, Timoteo; Di Patti, Francesca; Fanelli, Duccio; Piazza, Francesco

    2018-04-01

    We introduce a nonlinear operator to model diffusion on a complex undirected network under crowded conditions. We show that the asymptotic distribution of diffusing agents is a nonlinear function of the nodes' degree and saturates to a constant value for sufficiently large connectivities, at variance with standard diffusion in the absence of excluded-volume effects. Building on this observation, we define and solve an inverse problem, aimed at reconstructing the a priori unknown connectivity distribution. The method gathers all the necessary information by repeating a limited number of independent measurements of the asymptotic density at a single node, which can be chosen randomly. The technique is successfully tested against both synthetic and real data and is also shown to estimate with great accuracy the total number of nodes.

  1. Consume, Modify, Share (CMS): The Interplay between Individual Decisions and Structural Network Properties in the Diffusion of Information

    Science.gov (United States)

    Koren, Hila; Kaminer, Ido

    2016-01-01

    Widely used information diffusion models such as Independent Cascade Model, Susceptible Infected Recovered (SIR) and others fail to acknowledge that information is constantly subject to modification. Some aspects of information diffusion are best explained by network structural characteristics while in some cases strong influence comes from individual decisions. We introduce reinvention, the ability to modify information, as an individual level decision that affects the diffusion process as a whole. Based on a combination of constructs from the Diffusion of Innovations and the Critical Mass Theories, the present study advances the CMS (consume, modify, share) model which accounts for the interplay between network structure and human behavior and interactions. The model's building blocks include processes leading up to and following the formation of a critical mass of information adopters and disseminators. We examine the formation of an inflection point, information reach, sustainability of the diffusion process and collective value creation. The CMS model is tested on two directed networks and one undirected network, assuming weak or strong ties and applying constant and relative modification schemes. While all three networks are designed for disseminating new knowledge they differ in structural properties. Our findings suggest that modification enhances the diffusion of information in networks that support undirected connections and carries the biggest effect when information is shared via weak ties. Rogers' diffusion model and traditional information contagion models are fine tuned. Our results show that modifications not only contribute to a sustainable diffusion process, but also aid information in reaching remote areas of the network. The results point to the importance of cultivating weak ties, allowing reciprocal interaction among nodes and supporting the modification of information in promoting diffusion processes. These results have theoretical and

  2. New Graphical Model for Computing Optimistic Decisions in Possibility Theory Framework

    OpenAIRE

    Ismahane Zeddigha; Salem Benferhat; Faiza Khellaf

    2016-01-01

    This paper first proposes a new graphical model for decision making under uncertainty based on min-based possibilistic networks. A decision problem under uncertainty is described by means of two distinct min-based possibilistic networks: the first one expresses agent's knowledge while the second one encodes agent's preferences representing a qualitative utility. We then propose an efficient algorithm for computing optimistic optimal decisions using our new model for representing possibilistic...

  3. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Directory of Open Access Journals (Sweden)

    Dániel Bánky

    Full Text Available Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks that compensates for the low degree (non-hub vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well, but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus, and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures

  4. Equal opportunity for low-degree network nodes: a PageRank-based method for protein target identification in metabolic graphs.

    Science.gov (United States)

    Bánky, Dániel; Iván, Gábor; Grolmusz, Vince

    2013-01-01

    Biological network data, such as metabolic-, signaling- or physical interaction graphs of proteins are increasingly available in public repositories for important species. Tools for the quantitative analysis of these networks are being developed today. Protein network-based drug target identification methods usually return protein hubs with large degrees in the networks as potentially important targets. Some known, important protein targets, however, are not hubs at all, and perturbing protein hubs in these networks may have several unwanted physiological effects, due to their interaction with numerous partners. Here, we show a novel method applicable in networks with directed edges (such as metabolic networks) that compensates for the low degree (non-hub) vertices in the network, and identifies important nodes, regardless of their hub properties. Our method computes the PageRank for the nodes of the network, and divides the PageRank by the in-degree (i.e., the number of incoming edges) of the node. This quotient is the same in all nodes in an undirected graph (even for large- and low-degree nodes, that is, for hubs and non-hubs as well), but may differ significantly from node to node in directed graphs. We suggest to assign importance to non-hub nodes with large PageRank/in-degree quotient. Consequently, our method gives high scores to nodes with large PageRank, relative to their degrees: therefore non-hub important nodes can easily be identified in large networks. We demonstrate that these relatively high PageRank scores have biological relevance: the method correctly finds numerous already validated drug targets in distinct organisms (Mycobacterium tuberculosis, Plasmodium falciparum and MRSA Staphylococcus aureus), and consequently, it may suggest new possible protein targets as well. Additionally, our scoring method was not chosen arbitrarily: its value for all nodes of all undirected graphs is constant; therefore its high value captures importance in the

  5. A new method to infer causal phenotype networks using QTL and phenotypic information.

    Directory of Open Access Journals (Sweden)

    Huange Wang

    Full Text Available In the context of genetics and breeding research on multiple phenotypic traits, reconstructing the directional or causal structure between phenotypic traits is a prerequisite for quantifying the effects of genetic interventions on the traits. Current approaches mainly exploit the genetic effects at quantitative trait loci (QTLs to learn about causal relationships among phenotypic traits. A requirement for using these approaches is that at least one unique QTL has been identified for each trait studied. However, in practice, especially for molecular phenotypes such as metabolites, this prerequisite is often not met due to limited sample sizes, high noise levels and small QTL effects. Here, we present a novel heuristic search algorithm called the QTL+phenotype supervised orientation (QPSO algorithm to infer causal directions for edges in undirected phenotype networks. The two main advantages of this algorithm are: first, it does not require QTLs for each and every trait; second, it takes into account associated phenotypic interactions in addition to detected QTLs when orienting undirected edges between traits. We evaluate and compare the performance of QPSO with another state-of-the-art approach, the QTL-directed dependency graph (QDG algorithm. Simulation results show that our method has broader applicability and leads to more accurate overall orientations. We also illustrate our method with a real-life example involving 24 metabolites and a few major QTLs measured on an association panel of 93 tomato cultivars. Matlab source code implementing the proposed algorithm is freely available upon request.

  6. Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

    Science.gov (United States)

    Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

    2017-07-01

    In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Methods for generating complex networks with selected structural properties for simulations: A review and tutorial for neuroscientists

    Directory of Open Access Journals (Sweden)

    Brenton J Prettejohn

    2011-03-01

    Full Text Available Many simulations of networks in computational neuroscience assume completely homogenous random networks of the Erd"{o}s-R'{e}nyi type, or regular networks, despite it being recognized for some time that anatomical brain networks are more complex in their connectivity and can, for example, exhibit the `scale-free' and `small-world' properties. We review the most well known algorithms for constructing networks with given non-homogeneous statistical properties and provide simple pseudo-code for reproducing such networks in software simulations. We also review some useful mathematical results and approximations associated with the statistics that describe these network models, including degree distribution, average path length and clustering coefficient. We demonstrate how such results can be used as partial verification and validation of implementations. Finally, we discuss a sometimes overlooked modeling choice that can be crucially important for the properties of simulated networks: that of network directedness. The most well known network algorithms produce undirected networks, and we emphasize this point by highlighting how simple adaptations can instead produce directed networks.

  8. Node similarity and modularity for finding communities in networks

    Science.gov (United States)

    Saoud, Bilal; Moussaoui, Abdelouahab

    2018-02-01

    Community detection in networks has become a very important axis of research for understanding the structure of networks. Several methods have been proposed to detect the most optimal community structure in networks. In this article, we present a novel method for detecting community structure ComDBNS (Community Detection Based on Node Similarity) for unweighted and undirected networks; it performs in two steps. The first step uses the similarity between endpoints of each link to find the inter-community links to remove in order to create basic groups of nodes properly connected. In the second step we propose a strategy to merge these initial groups to identify the final community structure (with k communities or the structure that maximizes the modularity in Community Detection Based on Node Similarity and Modularity Q (ComDBNSQ)). The proposed method is tested on the real and computer-generated networks, and it demonstrates the effectiveness and correctness of the method. Also, the method saves the time complexity.

  9. Link Prediction in Weighted Networks: A Weighted Mutual Information Model.

    Directory of Open Access Journals (Sweden)

    Boyao Zhu

    Full Text Available The link-prediction problem is an open issue in data mining and knowledge discovery, which attracts researchers from disparate scientific communities. A wealth of methods have been proposed to deal with this problem. Among these approaches, most are applied in unweighted networks, with only a few taking the weights of links into consideration. In this paper, we present a weighted model for undirected and weighted networks based on the mutual information of local network structures, where link weights are applied to further enhance the distinguishable extent of candidate links. Empirical experiments are conducted on four weighted networks, and results show that the proposed method can provide more accurate predictions than not only traditional unweighted indices but also typical weighted indices. Furthermore, some in-depth discussions on the effects of weak ties in link prediction as well as the potential to predict link weights are also given. This work may shed light on the design of algorithms for link prediction in weighted networks.

  10. Constructing Social Networks from Unstructured Group Dialog in Virtual Worlds

    Science.gov (United States)

    Shah, Fahad; Sukthankar, Gita

    Virtual worlds and massively multi-player online games are rich sources of information about large-scale teams and groups, offering the tantalizing possibility of harvesting data about group formation, social networks, and network evolution. However these environments lack many of the cues that facilitate natural language processing in other conversational settings and different types of social media. Public chat data often features players who speak simultaneously, use jargon and emoticons, and only erratically adhere to conversational norms. In this paper, we present techniques for inferring the existence of social links from unstructured conversational data collected from groups of participants in the Second Life virtual world. We present an algorithm for addressing this problem, Shallow Semantic Temporal Overlap (SSTO), that combines temporal and language information to create directional links between participants, and a second approach that relies on temporal overlap alone to create undirected links between participants. Relying on temporal overlap is noisy, resulting in a low precision and networks with many extraneous links. In this paper, we demonstrate that we can ameliorate this problem by using network modularity optimization to perform community detection in the noisy networks and severing cross-community links. Although using the content of the communications still results in the best performance, community detection is effective as a noise reduction technique for eliminating the extra links created by temporal overlap alone.

  11. The QAP weighted network analysis method and its application in international services trade

    Science.gov (United States)

    Xu, Helian; Cheng, Long

    2016-04-01

    Based on QAP (Quadratic Assignment Procedure) correlation and complex network theory, this paper puts forward a new method named QAP Weighted Network Analysis Method. The core idea of the method is to analyze influences among relations in a social or economic group by building a QAP weighted network of networks of relations. In the QAP weighted network, a node depicts a relation and an undirect edge exists between any pair of nodes if there is significant correlation between relations. As an application of the QAP weighted network, we study international services trade by using the QAP weighted network, in which nodes depict 10 kinds of services trade relations. After the analysis of international services trade by QAP weighted network, and by using distance indicators, hierarchy tree and minimum spanning tree, the conclusion shows that: Firstly, significant correlation exists in all services trade, and the development of any one service trade will stimulate the other nine. Secondly, as the economic globalization goes deeper, correlations in all services trade have been strengthened continually, and clustering effects exist in those services trade. Thirdly, transportation services trade, computer and information services trade and communication services trade have the most influence and are at the core in all services trade.

  12. Sensitivity of directed networks to the addition and pruning of edges and vertices

    Science.gov (United States)

    Goltsev, A. V.; Timár, G.; Mendes, J. F. F.

    2017-08-01

    Directed networks have various topologically different extensive components, in contrast to a single giant component in undirected networks. We study the sensitivity (response) of the sizes of these extensive components in directed complex networks to the addition and pruning of edges and vertices. We introduce the susceptibility, which quantifies this sensitivity. We show that topologically different parts of a directed network have different sensitivity to the addition and pruning of edges and vertices and, therefore, they are characterized by different susceptibilities. These susceptibilities diverge at the critical point of the directed percolation transition, signaling the appearance (or disappearance) of the giant strongly connected component in the infinite size limit. We demonstrate this behavior in randomly damaged real and synthetic directed complex networks, such as the World Wide Web, Twitter, the Caenorhabditis elegans neural network, directed Erdős-Rényi graphs, and others. We reveal a nonmonotonic dependence of the sensitivity to random pruning of edges or vertices in the case of C. elegans and Twitter that manifests specific structural peculiarities of these networks. We propose the measurements of the susceptibilities during the addition or pruning of edges and vertices as a new method for studying structural peculiarities of directed networks.

  13. Critical controllability analysis of directed biological networks using efficient graph reduction.

    Science.gov (United States)

    Ishitsuka, Masayuki; Akutsu, Tatsuya; Nacher, Jose C

    2017-10-30

    Network science has recently integrated key concepts from control theory and has applied them to the analysis of the controllability of complex networks. One of the proposed frameworks uses the Minimum Dominating Set (MDS) approach, which has been successfully applied to the identification of cancer-related proteins and in analyses of large-scale undirected networks, such as proteome-wide protein interaction networks. However, many real systems are better represented by directed networks. Therefore, fast algorithms are required for the application of MDS to directed networks. Here, we propose an algorithm that utilises efficient graph reduction to identify critical control nodes in large-scale directed complex networks. The algorithm is 176-fold faster than existing methods and increases the computable network size to 65,000 nodes. We then applied the developed algorithm to metabolic pathways consisting of 70 plant species encompassing major plant lineages ranging from algae to angiosperms and to signalling pathways from C. elegans, D. melanogaster and H. sapiens. The analysis not only identified functional pathways enriched with critical control molecules but also showed that most control categories are largely conserved across evolutionary time, from green algae and early basal plants to modern angiosperm plant lineages.

  14. Network structure detection and analysis of Shanghai stock market

    Directory of Open Access Journals (Sweden)

    Sen Wu

    2015-04-01

    Full Text Available Purpose: In order to investigate community structure of the component stocks of SSE (Shanghai Stock Exchange 180-index, a stock correlation network is built to find the intra-community and inter-community relationship. Design/methodology/approach: The stock correlation network is built taking the vertices as stocks and edges as correlation coefficients of logarithm returns of stock price. It is built as undirected weighted at first. GN algorithm is selected to detect community structure after transferring the network into un-weighted with different thresholds. Findings: The result of the network community structure analysis shows that the stock market has obvious industrial characteristics. Most of the stocks in the same industry or in the same supply chain are assigned to the same community. The correlation of the internal stock prices’ fluctuation is closer than in different communities. The result of community structure detection also reflects correlations among different industries. Originality/value: Based on the analysis of the community structure in Shanghai stock market, the result reflects some industrial characteristics, which has reference value to relationship among industries or sub-sectors of listed companies.

  15. Top-k Spatial Preference Queries in Directed Road Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Attique

    2016-09-01

    Full Text Available Top-k spatial preference queries rank objects based on the score of feature objects in their spatial neighborhood. Top-k preference queries are crucial for a wide range of location based services such as hotel browsing and apartment searching. In recent years, a lot of research has been conducted on processing of top-k spatial preference queries in Euclidean space. While few algorithms study top-k preference queries in road networks, they all focus on undirected road networks. In this paper, we investigate the problem of processing the top-k spatial preference queries in directed road networks where each road segment has a particular orientation. Computation of data object scores requires examining the scores of each feature object in its spatial neighborhood. This may cause the computational delay, thus resulting in a high query processing time. In this paper, we address this problem by proposing a pruning and grouping of feature objects to reduce the number of feature objects. Furthermore, we present an efficient algorithm called TOPS that can process top-k spatial preference queries in directed road networks. Experimental results indicate that our algorithm significantly reduces the query processing time compared to period solution for a wide range of problem settings.

  16. Degree correlations in directed scale-free networks.

    Science.gov (United States)

    Williams, Oliver; Del Genio, Charo I

    2014-01-01

    Scale-free networks, in which the distribution of the degrees obeys a power-law, are ubiquitous in the study of complex systems. One basic network property that relates to the structure of the links found is the degree assortativity, which is a measure of the correlation between the degrees of the nodes at the end of the links. Degree correlations are known to affect both the structure of a network and the dynamics of the processes supported thereon, including the resilience to damage, the spread of information and epidemics, and the efficiency of defence mechanisms. Nonetheless, while many studies focus on undirected scale-free networks, the interactions in real-world systems often have a directionality. Here, we investigate the dependence of the degree correlations on the power-law exponents in directed scale-free networks. To perform our study, we consider the problem of building directed networks with a prescribed degree distribution, providing a method for proper generation of power-law-distributed directed degree sequences. Applying this new method, we perform extensive numerical simulations, generating ensembles of directed scale-free networks with exponents between 2 and 3, and measuring ensemble averages of the Pearson correlation coefficients. Our results show that scale-free networks are on average uncorrelated across directed links for three of the four possible degree-degree correlations, namely in-degree to in-degree, in-degree to out-degree, and out-degree to out-degree. However, they exhibit anticorrelation between the number of outgoing connections and the number of incoming ones. The findings are consistent with an entropic origin for the observed disassortativity in biological and technological networks.

  17. The G protein-coupled receptor heterodimer network (GPCR-HetNet) and its hub components.

    Science.gov (United States)

    Borroto-Escuela, Dasiel O; Brito, Ismel; Romero-Fernandez, Wilber; Di Palma, Michael; Oflijan, Julia; Skieterska, Kamila; Duchou, Jolien; Van Craenenbroeck, Kathleen; Suárez-Boomgaard, Diana; Rivera, Alicia; Guidolin, Diego; Agnati, Luigi F; Fuxe, Kjell

    2014-05-14

    G protein-coupled receptors (GPCRs) oligomerization has emerged as a vital characteristic of receptor structure. Substantial experimental evidence supports the existence of GPCR-GPCR interactions in a coordinated and cooperative manner. However, despite the current development of experimental techniques for large-scale detection of GPCR heteromers, in order to understand their connectivity it is necessary to develop novel tools to study the global heteroreceptor networks. To provide insight into the overall topology of the GPCR heteromers and identify key players, a collective interaction network was constructed. Experimental interaction data for each of the individual human GPCR protomers was obtained manually from the STRING and SCOPUS databases. The interaction data were used to build and analyze the network using Cytoscape software. The network was treated as undirected throughout the study. It is comprised of 156 nodes, 260 edges and has a scale-free topology. Connectivity analysis reveals a significant dominance of intrafamily versus interfamily connections. Most of the receptors within the network are linked to each other by a small number of edges. DRD2, OPRM, ADRB2, AA2AR, AA1R, OPRK, OPRD and GHSR are identified as hubs. In a network representation 10 modules/clusters also appear as a highly interconnected group of nodes. Information on this GPCR network can improve our understanding of molecular integration. GPCR-HetNet has been implemented in Java and is freely available at http://www.iiia.csic.es/~ismel/GPCR-Nets/index.html.

  18. Empirical Bayes conditional independence graphs for regulatory network recovery

    Science.gov (United States)

    Mahdi, Rami; Madduri, Abishek S.; Wang, Guoqing; Strulovici-Barel, Yael; Salit, Jacqueline; Hackett, Neil R.; Crystal, Ronald G.; Mezey, Jason G.

    2012-01-01

    Motivation: Computational inference methods that make use of graphical models to extract regulatory networks from gene expression data can have difficulty reconstructing dense regions of a network, a consequence of both computational complexity and unreliable parameter estimation when sample size is small. As a result, identification of hub genes is of special difficulty for these methods. Methods: We present a new algorithm, Empirical Light Mutual Min (ELMM), for large network reconstruction that has properties well suited for recovery of graphs with high-degree nodes. ELMM reconstructs the undirected graph of a regulatory network using empirical Bayes conditional independence testing with a heuristic relaxation of independence constraints in dense areas of the graph. This relaxation allows only one gene of a pair with a putative relation to be aware of the network connection, an approach that is aimed at easing multiple testing problems associated with recovering densely connected structures. Results: Using in silico data, we show that ELMM has better performance than commonly used network inference algorithms including GeneNet, ARACNE, FOCI, GENIE3 and GLASSO. We also apply ELMM to reconstruct a network among 5492 genes expressed in human lung airway epithelium of healthy non-smokers, healthy smokers and individuals with chronic obstructive pulmonary disease assayed using microarrays. The analysis identifies dense sub-networks that are consistent with known regulatory relationships in the lung airway and also suggests novel hub regulatory relationships among a number of genes that play roles in oxidative stress and secretion. Availability and implementation: Software for running ELMM is made available at http://mezeylab.cb.bscb.cornell.edu/Software.aspx. Contact: ramimahdi@yahoo.com or jgm45@cornell.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:22685074

  19. The tYNA platform for comparative interactomics: a web tool for managing, comparing and mining multiple networks.

    Science.gov (United States)

    Yip, Kevin Y; Yu, Haiyuan; Kim, Philip M; Schultz, Martin; Gerstein, Mark

    2006-12-01

    Biological processes involve complex networks of interactions between molecules. Various large-scale experiments and curation efforts have led to preliminary versions of complete cellular networks for a number of organisms. To grapple with these networks, we developed TopNet-like Yale Network Analyzer (tYNA), a Web system for managing, comparing and mining multiple networks, both directed and undirected. tYNA efficiently implements methods that have proven useful in network analysis, including identifying defective cliques, finding small network motifs (such as feed-forward loops), calculating global statistics (such as the clustering coefficient and eccentricity), and identifying hubs and bottlenecks. It also allows one to manage a large number of private and public networks using a flexible tagging system, to filter them based on a variety of criteria, and to visualize them through an interactive graphical interface. A number of commonly used biological datasets have been pre-loaded into tYNA, standardized and grouped into different categories. The tYNA system can be accessed at http://networks.gersteinlab.org/tyna. The source code, JavaDoc API and WSDL can also be downloaded from the website. tYNA can also be accessed from the Cytoscape software using a plugin.

  20. Probabilistic Inference in General Graphical Models through Sampling in Stochastic Networks of Spiking Neurons

    Science.gov (United States)

    Pecevski, Dejan; Buesing, Lars; Maass, Wolfgang

    2011-01-01

    An important open problem of computational neuroscience is the generic organization of computations in networks of neurons in the brain. We show here through rigorous theoretical analysis that inherent stochastic features of spiking neurons, in combination with simple nonlinear computational operations in specific network motifs and dendritic arbors, enable networks of spiking neurons to carry out probabilistic inference through sampling in general graphical models. In particular, it enables them to carry out probabilistic inference in Bayesian networks with converging arrows (“explaining away”) and with undirected loops, that occur in many real-world tasks. Ubiquitous stochastic features of networks of spiking neurons, such as trial-to-trial variability and spontaneous activity, are necessary ingredients of the underlying computational organization. We demonstrate through computer simulations that this approach can be scaled up to neural emulations of probabilistic inference in fairly large graphical models, yielding some of the most complex computations that have been carried out so far in networks of spiking neurons. PMID:22219717

  1. Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks

    Directory of Open Access Journals (Sweden)

    Lindsay eRutter

    2013-07-01

    Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.

  2. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  3. Identifying influential spreaders in complex networks through local effective spreading paths

    Science.gov (United States)

    Wang, Xiaojie; Zhang, Xue; Yi, Dongyun; Zhao, Chengli

    2017-05-01

    How to effectively identify a set of influential spreaders in complex networks is of great theoretical and practical value, which can help to inhibit the rapid spread of epidemics, promote the sales of products by word-of-mouth advertising, and so on. A naive strategy is to select the top ranked nodes as identified by some centrality indices, and other strategies are mainly based on greedy methods and heuristic methods. However, most of those approaches did not concern the connections between nodes. Usually, the distances between the selected spreaders are very close, leading to a serious overlapping of their influence. As a consequence, the global influence of the spreaders in networks will be greatly reduced, which largely restricts the performance of those methods. In this paper, a simple and efficient method is proposed to identify a set of discrete yet influential spreaders. By analyzing the spreading paths in the network, we present the concept of effective spreading paths and measure the influence of nodes via expectation calculation. The numerical analysis in undirected and directed networks all show that our proposed method outperforms many other centrality-based and heuristic benchmarks, especially in large-scale networks. Besides, experimental results on different spreading models and parameters demonstrates the stability and wide applicability of our method.

  4. Altered brain structural networks in attention deficit/hyperactivity disorder children revealed by cortical thickness.

    Science.gov (United States)

    Liu, Tian; Chen, Yanni; Li, Chenxi; Li, Youjun; Wang, Jue

    2017-07-04

    This study investigated the cortical thickness and topological features of human brain anatomical networks related to attention deficit/hyperactivity disorder. Data were collected from 40 attention deficit/hyperactivity disorder children and 40 normal control children. Interregional correlation matrices were established by calculating the correlations of cortical thickness between all pairs of cortical regions (68 regions) of the whole brain. Further thresholds were applied to create binary matrices to construct a series of undirected and unweighted graphs, and global, local, and nodal efficiencies were computed as a function of the network cost. These experimental results revealed abnormal cortical thickness and correlations in attention deficit/hyperactivity disorder, and showed that the brain structural networks of attention deficit/hyperactivity disorder subjects had inefficient small-world topological features. Furthermore, their topological properties were altered abnormally. In particular, decreased global efficiency combined with increased local efficiency in attention deficit/hyperactivity disorder children led to a disorder-related shift of the network topological structure toward regular networks. In addition, nodal efficiency, cortical thickness, and correlation analyses revealed that several brain regions were altered in attention deficit/hyperactivity disorder patients. These findings are in accordance with a hypothesis of dysfunctional integration and segregation of the brain in patients with attention deficit/hyperactivity disorder and provide further evidence of brain dysfunction in attention deficit/hyperactivity disorder patients by observing cortical thickness on magnetic resonance imaging.

  5. A Local Poisson Graphical Model for inferring networks from sequencing data.

    Science.gov (United States)

    Allen, Genevera I; Liu, Zhandong

    2013-09-01

    Gaussian graphical models, a class of undirected graphs or Markov Networks, are often used to infer gene networks based on microarray expression data. Many scientists, however, have begun using high-throughput sequencing technologies such as RNA-sequencing or next generation sequencing to measure gene expression. As the resulting data consists of counts of sequencing reads for each gene, Gaussian graphical models are not optimal for this discrete data. In this paper, we propose a novel method for inferring gene networks from sequencing data: the Local Poisson Graphical Model. Our model assumes a Local Markov property where each variable conditional on all other variables is Poisson distributed. We develop a neighborhood selection algorithm to fit our model locally by performing a series of l1 penalized Poisson, or log-linear, regressions. This yields a fast parallel algorithm for estimating networks from next generation sequencing data. In simulations, we illustrate the effectiveness of our methods for recovering network structure from count data. A case study on breast cancer microRNAs (miRNAs), a novel application of graphical models, finds known regulators of breast cancer genes and discovers novel miRNA clusters and hubs that are targets for future research.

  6. Analytical maximum-likelihood method to detect patterns in real networks

    International Nuclear Information System (INIS)

    Squartini, Tiziano; Garlaschelli, Diego

    2011-01-01

    In order to detect patterns in real networks, randomized graph ensembles that preserve only part of the topology of an observed network are systematically used as fundamental null models. However, the generation of them is still problematic. Existing approaches are either computationally demanding and beyond analytic control or analytically accessible but highly approximate. Here, we propose a solution to this long-standing problem by introducing a fast method that allows one to obtain expectation values and standard deviations of any topological property analytically, for any binary, weighted, directed or undirected network. Remarkably, the time required to obtain the expectation value of any property analytically across the entire graph ensemble is as short as that required to compute the same property using the adjacency matrix of the single original network. Our method reveals that the null behavior of various correlation properties is different from what was believed previously, and is highly sensitive to the particular network considered. Moreover, our approach shows that important structural properties (such as the modularity used in community detection problems) are currently based on incorrect expressions, and provides the exact quantities that should replace them.

  7. Random Walks on Directed Networks: Inference and Respondent-Driven Sampling

    Directory of Open Access Journals (Sweden)

    Malmros Jens

    2016-06-01

    Full Text Available Respondent-driven sampling (RDS is often used to estimate population properties (e.g., sexual risk behavior in hard-to-reach populations. In RDS, already sampled individuals recruit population members to the sample from their social contacts in an efficient snowball-like sampling procedure. By assuming a Markov model for the recruitment of individuals, asymptotically unbiased estimates of population characteristics can be obtained. Current RDS estimation methodology assumes that the social network is undirected, that is, all edges are reciprocal. However, empirical social networks in general also include a substantial number of nonreciprocal edges. In this article, we develop an estimation method for RDS in populations connected by social networks that include reciprocal and nonreciprocal edges. We derive estimators of the selection probabilities of individuals as a function of the number of outgoing edges of sampled individuals. The proposed estimators are evaluated on artificial and empirical networks and are shown to generally perform better than existing estimators. This is the case in particular when the fraction of directed edges in the network is large.

  8. Network Theory Integrated Life Cycle Assessment for an Electric Power System

    Directory of Open Access Journals (Sweden)

    Heetae Kim

    2015-08-01

    Full Text Available In this study, we allocate Greenhouse gas (GHG emissions of electricity transmission to the consumers. As an allocation basis, we introduce energy distance. Energy distance takes the transmission load on the electricity energy system into account in addition to the amount of electricity consumption. As a case study, we estimate regional GHG emissions of electricity transmission loss in Chile. Life cycle assessment (LCA is used to estimate the total GHG emissions of the Chilean electric power system. The regional GHG emission of transmission loss is calculated from the total GHG emissions. We construct the network model of Chilean electric power grid as an undirected network with 466 nodes and 543 edges holding the topology of the power grid based on the statistical record. We analyze the total annual GHG emissions of the Chilean electricity energy system as 23.07 Mt CO2-eq. and 1.61 Mt CO2-eq. for the transmission loss, respectively. The total energy distance for the electricity transmission accounts for 12,842.10 TWh km based on network analysis. We argue that when the GHG emission of electricity transmission loss is estimated, the electricity transmission load should be separately considered. We propose network theory as a useful complement to LCA analysis for the complex allocation. Energy distance is especially useful on a very large-scale electric power grid such as an intercontinental transmission network.

  9. Explosive percolation on directed networks due to monotonic flow of activity

    Science.gov (United States)

    Waagen, Alex; D'Souza, Raissa M.; Lu, Tsai-Ching

    2017-07-01

    An important class of real-world networks has directed edges, and in addition, some rank ordering on the nodes, for instance the popularity of users in online social networks. Yet, nearly all research related to explosive percolation has been restricted to undirected networks. Furthermore, information on such rank-ordered networks typically flows from higher-ranked to lower-ranked individuals, such as follower relations, replies, and retweets on Twitter. Here we introduce a simple percolation process on an ordered, directed network where edges are added monotonically with respect to the rank ordering. We show with a numerical approach that the emergence of a dominant strongly connected component appears to be discontinuous. Large-scale connectivity occurs at very high density compared with most percolation processes, and this holds not just for the strongly connected component structure but for the weakly connected component structure as well. We present analysis with branching processes, which explains this unusual behavior and gives basic intuition for the underlying mechanisms. We also show that before the emergence of a dominant strongly connected component, multiple giant strongly connected components may exist simultaneously. By adding a competitive percolation rule with a small bias to link uses of similar rank, we show this leads to formation of two distinct components, one of high-ranked users, and one of low-ranked users, with little flow between the two components.

  10. Driving and driven architectures of directed small-world human brain functional networks.

    Directory of Open Access Journals (Sweden)

    Chaogan Yan

    Full Text Available Recently, increasing attention has been focused on the investigation of the human brain connectome that describes the patterns of structural and functional connectivity networks of the human brain. Many studies of the human connectome have demonstrated that the brain network follows a small-world topology with an intrinsically cohesive modular structure and includes several network hubs in the medial parietal regions. However, most of these studies have only focused on undirected connections between regions in which the directions of information flow are not taken into account. How the brain regions causally influence each other and how the directed network of human brain is topologically organized remain largely unknown. Here, we applied linear multivariate Granger causality analysis (GCA and graph theoretical approaches to a resting-state functional MRI dataset with a large cohort of young healthy participants (n = 86 to explore connectivity patterns of the population-based whole-brain functional directed network. This directed brain network exhibited prominent small-world properties, which obviously improved previous results of functional MRI studies showing weak small-world properties in the directed brain networks in terms of a kernel-based GCA and individual analysis. This brain network also showed significant modular structures associated with 5 well known subsystems: fronto-parietal, visual, paralimbic/limbic, subcortical and primary systems. Importantly, we identified several driving hubs predominantly located in the components of the attentional network (e.g., the inferior frontal gyrus, supplementary motor area, insula and fusiform gyrus and several driven hubs predominantly located in the components of the default mode network (e.g., the precuneus, posterior cingulate gyrus, medial prefrontal cortex and inferior parietal lobule. Further split-half analyses indicated that our results were highly reproducible between two

  11. Parameterized algorithmics for finding connected motifs in biological networks.

    Science.gov (United States)

    Betzler, Nadja; van Bevern, René; Fellows, Michael R; Komusiewicz, Christian; Niedermeier, Rolf

    2011-01-01

    We study the NP-hard LIST-COLORED GRAPH MOTIF problem which, given an undirected list-colored graph G = (V, E) and a multiset M of colors, asks for maximum-cardinality sets S ⊆ V and M' ⊆ M such that G[S] is connected and contains exactly (with respect to multiplicity) the colors in M'. LIST-COLORED GRAPH MOTIF has applications in the analysis of biological networks. We study LIST-COLORED GRAPH MOTIF with respect to three different parameterizations. For the parameters motif size |M| and solution size |S|, we present fixed-parameter algorithms, whereas for the parameter |V| - |M|, we show W[1]-hardness for general instances and achieve fixed-parameter tractability for a special case of LIST-COLORED GRAPH MOTIF. We implemented the fixed-parameter algorithms for parameters |M| and |S|, developed further speed-up heuristics for these algorithms, and applied them in the context of querying protein-interaction networks, demonstrating their usefulness for realistic instances. Furthermore, we show that extending the request for motif connectedness to stronger demands, such as biconnectedness or bridge-connectedness leads to W[1]-hard problems when the parameter is the motif size |M|.

  12. Dynamics of cluster structures in a financial market network

    Science.gov (United States)

    Kocheturov, Anton; Batsyn, Mikhail; Pardalos, Panos M.

    2014-11-01

    In the course of recent fifteen years the network analysis has become a powerful tool for studying financial markets. In this work we analyze stock markets of the USA and Sweden. We study cluster structures of a market network constructed from a correlation matrix of returns of the stocks traded in each of these markets. Such cluster structures are obtained by means of the P-Median Problem (PMP) whose objective is to maximize the total correlation between a set of stocks called medians of size p and other stocks. Every cluster structure is an undirected disconnected weighted graph in which every connected component (cluster) is a star, or a tree with one central node (called a median) and several leaf nodes connected with the median by weighted edges. Our main observation is that in non-crisis periods of time cluster structures change more chaotically, while during crises they show more stable behavior and fewer changes. Thus an increasing stability of a market graph cluster structure obtained via the PMP could be used as an indicator of a coming crisis.

  13. Beyond the power law: Uncovering stylized facts in interbank networks

    Science.gov (United States)

    Vandermarliere, Benjamin; Karas, Alexei; Ryckebusch, Jan; Schoors, Koen

    2015-06-01

    We use daily data on bilateral interbank exposures and monthly bank balance sheets to study network characteristics of the Russian interbank market over August 1998-October 2004. Specifically, we examine the distributions of (un)directed (un)weighted degree, nodal attributes (bank assets, capital and capital-to-assets ratio) and edge weights (loan size and counterparty exposure). We search for the theoretical distribution that fits the data best and report the "best" fit parameters. We observe that all studied distributions are heavy tailed. The fat tail typically contains 20% of the data and can be mostly described well by a truncated power law. Also the power law, stretched exponential and log-normal provide reasonably good fits to the tails of the data. In most cases, however, separating the bulk and tail parts of the data is hard, so we proceed to study the full range of the events. We find that the stretched exponential and the log-normal distributions fit the full range of the data best. These conclusions are robust to (1) whether we aggregate the data over a week, month, quarter or year; (2) whether we look at the "growth" versus "maturity" phases of interbank market development; and (3) with minor exceptions, whether we look at the "normal" versus "crisis" operation periods. In line with prior research, we find that the network topology changes greatly as the interbank market moves from a "normal" to a "crisis" operation period.

  14. CeFunMO: A centrality based method for discovering functional motifs with application in biological networks.

    Science.gov (United States)

    Kouhsar, Morteza; Razaghi-Moghadam, Zahra; Mousavian, Zaynab; Masoudi-Nejad, Ali

    2016-09-01

    Detecting functional motifs in biological networks is one of the challenging problems in systems biology. Given a multiset of colors as query and a list-colored graph (an undirected graph with a set of colors assigned to each of its vertices), the problem is reduced to finding connected subgraphs, which best cover the multiset of query. To solve this NP-complete problem, we propose a new color-based centrality measure for list-colored graphs. Based on this newly-defined measure of centrality, a novel polynomial time algorithm is developed to discover functional motifs in list-colored graphs, using a greedy strategy. This algorithm, called CeFunMO, has superior running time and acceptable accuracy in comparison with other well-known algorithms, such as RANGI and GraMoFoNe. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. A network of networks.

    Science.gov (United States)

    Iedema, Rick; Verma, Raj; Wutzke, Sonia; Lyons, Nigel; McCaughan, Brian

    2017-04-10

    Purpose To further our insight into the role of networks in health system reform, the purpose of this paper is to investigate how one agency, the NSW Agency for Clinical Innovation (ACI), and the multiple networks and enabling resources that it encompasses, govern, manage and extend the potential of networks for healthcare practice improvement. Design/methodology/approach This is a case study investigation which took place over ten months through the first author's participation in network activities and discussions with the agency's staff about their main objectives, challenges and achievements, and with selected services around the state of New South Wales to understand the agency's implementation and large system transformation activities. Findings The paper demonstrates that ACI accommodates multiple networks whose oversight structures, self-organisation and systems change approaches combined in dynamic ways, effectively yield a diversity of network governances. Further, ACI bears out a paradox of "centralised decentralisation", co-locating agents of innovation with networks of implementation and evaluation expertise. This arrangement strengthens and legitimates the role of the strategic hybrid - the healthcare professional in pursuit of change and improvement, and enhances their influence and impact on the wider system. Research limitations/implications While focussing the case study on one agency only, this study is unique as it highlights inter-network connections. Contributing to the literature on network governance, this paper identifies ACI as a "network of networks" through which resources, expectations and stakeholder dynamics are dynamically and flexibly mediated and enhanced. Practical implications The co-location of and dynamic interaction among clinical networks may create synergies among networks, nurture "strategic hybrids", and enhance the impact of network activities on health system reform. Social implications Network governance requires more

  16. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    Science.gov (United States)

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  17. Irreversibility and complex network behavior of stream flow fluctuations

    Science.gov (United States)

    Serinaldi, Francesco; Kilsby, Chris G.

    2016-05-01

    Exploiting the duality between time series and networks, directed horizontal visibility graphs (DHVGs) are used to perform an unprecedented analysis of the dynamics of stream flow fluctuations with focus on time irreversibility and long range dependence. The analysis relies on a large quality-controlled data set consisting of 699 daily time series recorded in the continental United States (CONUS) that are not affected by human activity and primarily reflects meteorological conditions. DHVGs allow a clear visualization and quantification of time irreversibility of flow dynamics, which can be interpreted as a signature of nonlinearity, and long range dependence resulting from the interaction of atmospheric, surface and underground processes acting at multiple spatio-temporal scales. Irreversibility is explored by mapping the time series into ingoing, outgoing, and undirected graphs and comparing the corresponding degree distributions. Using surrogate data preserving up to the second order linear temporal dependence properties of the observed series, DHVGs highlight the additional complexity introduced by nonlinearity into flow fluctuation dynamics. We show that the degree distributions do not decay exponentially as expected, but tend to follow a subexponential behavior, even though sampling uncertainty does not allow a clear distinction between apparent or true power law decay. These results confirm that the complexity of stream flow dynamics goes beyond a linear representation involving for instance the combination of linear processes with short and long range dependence, and requires modeling strategies accounting for temporal asymmetry and nonlinearity.

  18. Declarative Networking

    CERN Document Server

    Loo, Boon Thau

    2012-01-01

    Declarative Networking is a programming methodology that enables developers to concisely specify network protocols and services, which are directly compiled to a dataflow framework that executes the specifications. Declarative networking proposes the use of a declarative query language for specifying and implementing network protocols, and employs a dataflow framework at runtime for communication and maintenance of network state. The primary goal of declarative networking is to greatly simplify the process of specifying, implementing, deploying and evolving a network design. In addition, decla

  19. Ambiguity in Social Network Data for Presence, Sensitive-Attribute, Degree and Relationship Privacy Protection.

    Science.gov (United States)

    Rajaei, Mehri; Haghjoo, Mostafa S; Miyaneh, Eynollah Khanjari

    2015-01-01

    Maintaining privacy in network data publishing is a major challenge. This is because known characteristics of individuals can be used to extract new information about them. Recently, researchers have developed privacy methods based on k-anonymity and l-diversity to prevent re-identification or sensitive label disclosure through certain structural information. However, most of these studies have considered only structural information and have been developed for undirected networks. Furthermore, most existing approaches rely on generalization and node clustering so may entail significant information loss as all properties of all members of each group are generalized to the same value. In this paper, we introduce a framework for protecting sensitive attribute, degree (the number of connected entities), and relationships, as well as the presence of individuals in directed social network data whose nodes contain attributes. First, we define a privacy model that specifies privacy requirements for the above private information. Then, we introduce the technique of Ambiguity in Social Network data (ASN) based on anatomy, which specifies how to publish social network data. To employ ASN, individuals are partitioned into groups. Then, ASN publishes exact values of properties of individuals of each group with common group ID in several tables. The lossy join of those tables based on group ID injects uncertainty to reconstruct the original network. We also show how to measure different privacy requirements in ASN. Simulation results on real and synthetic datasets demonstrate that our framework, which protects from four types of private information disclosure, preserves data utility in tabular, topological and spectrum aspects of networks at a satisfactory level.

  20. Ambiguity in Social Network Data for Presence, Sensitive-Attribute, Degree and Relationship Privacy Protection.

    Directory of Open Access Journals (Sweden)

    Mehri Rajaei

    Full Text Available Maintaining privacy in network data publishing is a major challenge. This is because known characteristics of individuals can be used to extract new information about them. Recently, researchers have developed privacy methods based on k-anonymity and l-diversity to prevent re-identification or sensitive label disclosure through certain structural information. However, most of these studies have considered only structural information and have been developed for undirected networks. Furthermore, most existing approaches rely on generalization and node clustering so may entail significant information loss as all properties of all members of each group are generalized to the same value. In this paper, we introduce a framework for protecting sensitive attribute, degree (the number of connected entities, and relationships, as well as the presence of individuals in directed social network data whose nodes contain attributes. First, we define a privacy model that specifies privacy requirements for the above private information. Then, we introduce the technique of Ambiguity in Social Network data (ASN based on anatomy, which specifies how to publish social network data. To employ ASN, individuals are partitioned into groups. Then, ASN publishes exact values of properties of individuals of each group with common group ID in several tables. The lossy join of those tables based on group ID injects uncertainty to reconstruct the original network. We also show how to measure different privacy requirements in ASN. Simulation results on real and synthetic datasets demonstrate that our framework, which protects from four types of private information disclosure, preserves data utility in tabular, topological and spectrum aspects of networks at a satisfactory level.

  1. Identifying influential nodes in large-scale directed networks: the role of clustering.

    Science.gov (United States)

    Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

    2013-01-01

    Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

  2. Identifying influential nodes in large-scale directed networks: the role of clustering.

    Directory of Open Access Journals (Sweden)

    Duan-Bing Chen

    Full Text Available Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node's neighbors but do not directly make use of the interactions among it's neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors' influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about [Formula: see text] nodes, more than 15 times faster than PageRank.

  3. Identifying Influential Nodes in Large-Scale Directed Networks: The Role of Clustering

    Science.gov (United States)

    Chen, Duan-Bing; Gao, Hui; Lü, Linyuan; Zhou, Tao

    2013-01-01

    Identifying influential nodes in very large-scale directed networks is a big challenge relevant to disparate applications, such as accelerating information propagation, controlling rumors and diseases, designing search engines, and understanding hierarchical organization of social and biological networks. Known methods range from node centralities, such as degree, closeness and betweenness, to diffusion-based processes, like PageRank and LeaderRank. Some of these methods already take into account the influences of a node’s neighbors but do not directly make use of the interactions among it’s neighbors. Local clustering is known to have negative impacts on the information spreading. We further show empirically that it also plays a negative role in generating local connections. Inspired by these facts, we propose a local ranking algorithm named ClusterRank, which takes into account not only the number of neighbors and the neighbors’ influences, but also the clustering coefficient. Subject to the susceptible-infected-recovered (SIR) spreading model with constant infectivity, experimental results on two directed networks, a social network extracted from delicious.com and a large-scale short-message communication network, demonstrate that the ClusterRank outperforms some benchmark algorithms such as PageRank and LeaderRank. Furthermore, ClusterRank can also be applied to undirected networks where the superiority of ClusterRank is significant compared with degree centrality and k-core decomposition. In addition, ClusterRank, only making use of local information, is much more efficient than global methods: It takes only 191 seconds for a network with about nodes, more than 15 times faster than PageRank. PMID:24204833

  4. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago Vanderlei; Giannitsarou, Chrysi; Johnson, CR

    2017-01-01

    We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and define a network aggregator that preserves network cohesion.

  5. Network cosmology.

    Science.gov (United States)

    Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

    2012-01-01

    Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

  6. The network researchers' network

    DEFF Research Database (Denmark)

    Henneberg, Stephan C.; Jiang, Zhizhong; Naudé, Peter

    2009-01-01

    The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987). In thi...

  7. Uncertainty Modeling and Possibilistic Approach to Parameter Estimation.

    Science.gov (United States)

    1982-01-01

    G. HARMAN (Ed.), "On Noam Chomsky : Critical Essays," Anchor Press/Doubleday, New York, 1974. 17. E. H. LENNENBERG with appendices by N. Chomsky and...another reasonably educated speaker , as well as various combinations and operations on this ideas - yet cannot express this concepts easily within a

  8. Descriptive and network analyses of the equine contact network at an equestrian show in Ontario, Canada and implications for disease spread.

    Science.gov (United States)

    Spence, Kelsey L; O'Sullivan, Terri L; Poljak, Zvonimir; Greer, Amy L

    2017-06-21

    Identifying the contact structure within a population of horses attending a competition is an important element towards understanding the potential for the spread of equine pathogens as the horses subsequently travel from location to location. However, there is limited information in Ontario, Canada to quantify contact patterns of horses. The objective of this study was to describe the network of potential contacts associated with an equestrian show to determine how this network structure may influence potential disease transmission. This was a descriptive study of horses attending an equestrian show in southern Ontario, Canada on July 6 and 7, 2014. Horse show participants completed a questionnaire about their horse, travel patterns, and infection control practices. Questionnaire responses were received from horse owners of 79.7% (55/69) of the horses attending the show. Owners reported that horses attending the show were vaccinated for diseases such as rabies, equine influenza, and equine herpesvirus. Owners demonstrated high compliance with most infection control practices by reporting reduced opportunities for direct and indirect contact while away from home. The two-mode undirected network consisted of 820 nodes (41 locations and 779 horses). Eight percent of nodes in the network represented horses attending the show, 87% of nodes represented horses not attending the show, but boarded at individual home facilities, and 5% represented locations. The median degree of a horse in the network was 33 (range: 1-105). Developing disease management strategies without the explicit consideration of horses boarded at individual home facilities would underestimate the connectivity of horses in the population. The results of this study provides information that can be used by equestrian show organizers to configure event management in such a way that can limit the extent of potential disease spread.

  9. Ontology-based Deep Learning for Human Behavior Prediction with Explanations in Health Social Networks.

    Science.gov (United States)

    Phan, Nhathai; Dou, Dejing; Wang, Hao; Kil, David; Piniewski, Brigitte

    2017-04-01

    Human behavior modeling is a key component in application domains such as healthcare and social behavior research. In addition to accurate prediction, having the capacity to understand the roles of human behavior determinants and to provide explanations for the predicted behaviors is also important. Having this capacity increases trust in the systems and the likelihood that the systems actually will be adopted, thus driving engagement and loyalty. However, most prediction models do not provide explanations for the behaviors they predict. In this paper, we study the research problem, human behavior prediction with explanations , for healthcare intervention systems in health social networks. We propose an ontology-based deep learning model ( ORBM + ) for human behavior prediction over undirected and nodes-attributed graphs. We first propose a bottom-up algorithm to learn the user representation from health ontologies. Then the user representation is utilized to incorporate self-motivation , social influences , and environmental events together in a human behavior prediction model, which extends a well-known deep learning method, the Restricted Boltzmann Machine. ORBM + not only predicts human behaviors accurately, but also, it generates explanations for each predicted behavior. Experiments conducted on both real and synthetic health social networks have shown the tremendous effectiveness of our approach compared with conventional methods.

  10. Telecommunication networks

    CERN Document Server

    Iannone, Eugenio

    2011-01-01

    Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

  11. Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis.

    Science.gov (United States)

    Amrine, Katherine C H; Blanco-Ulate, Barbara; Cantu, Dario

    2015-01-01

    Intricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of the model plant Arabidopsis thaliana with microbial pathogens. This work was conducted to identify (i) modules of functionally related co-expressed genes that are differentially expressed in response to multiple biotic stresses, and (ii) hub genes that may function as core regulators of disease responses. Using Weighted Gene Co-expression Network Analysis (WGCNA) we constructed an undirected network leveraging a rich curated expression dataset comprising 272 microarrays that involved microbial infections of Arabidopsis plants with a wide array of fungal and bacterial pathogens with biotrophic, hemibiotrophic, and necrotrophic lifestyles. WGCNA produced a network with scale-free and small-world properties composed of 205 distinct clusters of co-expressed genes. Modules of functionally related co-expressed genes that are differentially regulated in response to multiple pathogens were identified by integrating differential gene expression testing with functional enrichment analyses of gene ontology terms, known disease associated genes, transcriptional regulators, and cis-regulatory elements. The significance of functional enrichments was validated by comparisons with randomly generated networks. Network topology was then analyzed to identify intra- and inter-modular gene hubs. Based on high connectivity, and centrality in meta-modules that are clearly enriched in defense responses, we propose a list of 66 target genes for reverse genetic experiments to further dissect the Arabidopsis immune system. Our results show that statistical-based data trimming prior to network analysis allows the integration of expression datasets generated by different groups, under different

  12. Assessment of Overlap of Phylogenetic Transmission Clusters and Communities in Simple Sexual Contact Networks: Applications to HIV-1

    Science.gov (United States)

    Villandre, Luc; Günthard, Huldrych F.; Kouyos, Roger; Stadler, Tanja

    2016-01-01

    Background Transmission patterns of sexually-transmitted infections (STIs) could relate to the structure of the underlying sexual contact network, whose features are therefore of interest to clinicians. Conventionally, we represent sexual contacts in a population with a graph, that can reveal the existence of communities. Phylogenetic methods help infer the history of an epidemic and incidentally, may help detecting communities. In particular, phylogenetic analyses of HIV-1 epidemics among men who have sex with men (MSM) have revealed the existence of large transmission clusters, possibly resulting from within-community transmissions. Past studies have explored the association between contact networks and phylogenies, including transmission clusters, producing conflicting conclusions about whether network features significantly affect observed transmission history. As far as we know however, none of them thoroughly investigated the role of communities, defined with respect to the network graph, in the observation of clusters. Methods The present study investigates, through simulations, community detection from phylogenies. We simulate a large number of epidemics over both unweighted and weighted, undirected random interconnected-islands networks, with islands corresponding to communities. We use weighting to modulate distance between islands. We translate each epidemic into a phylogeny, that lets us partition our samples of infected subjects into transmission clusters, based on several common definitions from the literature. We measure similarity between subjects’ island membership indices and transmission cluster membership indices with the adjusted Rand index. Results and Conclusion Analyses reveal modest mean correspondence between communities in graphs and phylogenetic transmission clusters. We conclude that common methods often have limited success in detecting contact network communities from phylogenies. The rarely-fulfilled requirement that network

  13. Step-by-Step Construction of Gene Co-expression Networks from High-Throughput Arabidopsis RNA Sequencing Data.

    Science.gov (United States)

    Contreras-López, Orlando; Moyano, Tomás C; Soto, Daniela C; Gutiérrez, Rodrigo A

    2018-01-01

    The rapid increase in the availability of transcriptomics data generated by RNA sequencing represents both a challenge and an opportunity for biologists without bioinformatics training. The challenge is handling, integrating, and interpreting these data sets. The opportunity is to use this information to generate testable hypothesis to understand molecular mechanisms controlling gene expression and biological processes (Fig. 1). A successful strategy to generate tractable hypotheses from transcriptomics data has been to build undirected network graphs based on patterns of gene co-expression. Many examples of new hypothesis derived from network analyses can be found in the literature, spanning different organisms including plants and specific fields such as root developmental biology.In order to make the process of constructing a gene co-expression network more accessible to biologists, here we provide step-by-step instructions using published RNA-seq experimental data obtained from a public database. Similar strategies have been used in previous studies to advance root developmental biology. This guide includes basic instructions for the operation of widely used open source platforms such as Bio-Linux, R, and Cytoscape. Even though the data we used in this example was obtained from Arabidopsis thaliana, the workflow developed in this guide can be easily adapted to work with RNA-seq data from any organism.

  14. Interconnected networks

    CERN Document Server

    2016-01-01

    This volume provides an introduction to and overview of the emerging field of interconnected networks which include multi layer or multiplex networks, as well as networks of networks. Such networks present structural and dynamical features quite different from those observed in isolated networks. The presence of links between different networks or layers of a network typically alters the way such interconnected networks behave – understanding the role of interconnecting links is therefore a crucial step towards a more accurate description of real-world systems. While examples of such dissimilar properties are becoming more abundant – for example regarding diffusion, robustness and competition – the root of such differences remains to be elucidated. Each chapter in this topical collection is self-contained and can be read on its own, thus making it also suitable as reference for experienced researchers wishing to focus on a particular topic.

  15. A minimum resource neural network framework for solving multiconstraint shortest path problems.

    Science.gov (United States)

    Zhang, Junying; Zhao, Xiaoxue; He, Xiaotao

    2014-08-01

    Characterized by using minimum hard (structural) and soft (computational) resources, a novel parameter-free minimal resource neural network (MRNN) framework is proposed for solving a wide range of single-source shortest path (SP) problems for various graph types. The problems are the k-shortest time path problems with any combination of three constraints: time, hop, and label constraints, and the graphs can be directed, undirected, or bidirected with symmetric and/or asymmetric traversal time, which can be real and time dependent. Isomorphic to the graph where the SP is to be sought, the network is activated by generating autowave at source neuron and the autowave travels automatically along the paths with the speed of a hop in an iteration. Properties of the network are studied, algorithms are presented, and computation complexity is analyzed. The framework guarantees globally optimal solutions of a series of problems during the iteration process of the network, which provides insight into why even the SP is still too long to be satisfied. The network facilitates very large scale integrated circuit implementation and adapt to very large scale problems due to its massively parallel processing and minimum resource utilization. When implemented in a sequentially processing computer, experiments on synthetic graphs, road maps of cities of the USA, and vehicle routing with time windows indicate that the MRNN is especially efficient for large scale sparse graphs and even dense graphs with some constraints, e.g., the CPU time taken and the iteration number used for the road maps of cities of the USA is even less than  ∼ 2% and 0.5% that of the Dijkstra's algorithm.

  16. Network analysis of pediatric eating disorder symptoms in a treatment-seeking, transdiagnostic sample.

    Science.gov (United States)

    Goldschmidt, Andrea B; Crosby, Ross D; Cao, Li; Moessner, Markus; Forbush, Kelsie T; Accurso, Erin C; Le Grange, Daniel

    2018-02-01

    Classifying eating disorders in youth is challenging in light of developmental considerations and high rates of diagnostic migration. Understanding the transactional relationships among eating disorder symptoms, both across the transdiagnostic spectrum and within specific diagnostic categories, may clarify which core eating disorder symptoms contribute to, and maintain, eating-related psychopathology in youth. We utilized network analysis to investigate interrelationships among eating disorder symptoms in 636 treatment-seeking children and adolescents (90.3% female) ages 6-18 years (M age = 15.4 ± 2.2). An undirected, weighted network of eating disorder symptoms was created using behavioral and attitudinal items from the Eating Disorder Examination. Across diagnostic groups, symptoms reflecting appearance-related concerns (e.g., dissatisfaction with shape and weight) and dietary restraint (e.g., a desire to have an empty stomach) were most strongly associated with other eating disorder symptoms in the network. Binge eating and compensatory behaviors (e.g., self-induced vomiting) were strongly connected to one another but not to other symptoms in the network. Network connectivity was similar across anorexia nervosa, bulimia nervosa, and otherwise specified feeding or eating disorder subgroups. Among treatment-seeking children and adolescents, dietary restraint and shape- and weight-related concerns appear to play key roles in the psychopathology of eating disorders, supporting cognitive-behavioral theories of onset and maintenance. Similarities across diagnostic categories provide support for a transdiagnostic classification scheme. Clinical interventions should seek to disrupt these symptoms early in treatment to achieve maximal outcomes. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  17. Network maintenance

    CERN Multimedia

    GS Department

    2009-01-01

    A site-wide network maintenance operation has been scheduled for Saturday 28 February. Most of the network devices of the general purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites throughout the day. This upgrade will not affect the Computer Centre itself, Building 613, the Technical Network and the LHC experiments, dedicated networks at the pits. For further details of this intervention, please contact Netops by phone 74927 or e-mail mailto:Netops@cern.ch. IT/CS Group

  18. Network maintenance

    CERN Multimedia

    IT Department

    2009-01-01

    A site wide network maintenance has been scheduled for Saturday 28 February. Most of the network devices of the General Purpose network will be upgraded to a newer software version, in order to improve our network monitoring capabilities. This will result in a series of short (2-5 minutes) random interruptions everywhere on the CERN sites along this day. This upgrade will not affect: the Computer centre itself, building 613, the Technical Network and the LHC experiments dedicated networks at the pits. Should you need more details on this intervention, please contact Netops by phone 74927 or email mailto:Netops@cern.ch. IT/CS Group

  19. Network Ambivalence

    Directory of Open Access Journals (Sweden)

    Patrick Jagoda

    2015-08-01

    Full Text Available The language of networks now describes everything from the Internet to the economy to terrorist organizations. In distinction to a common view of networks as a universal, originary, or necessary form that promises to explain everything from neural structures to online traffic, this essay emphasizes the contingency of the network imaginary. Network form, in its role as our current cultural dominant, makes scarcely imaginable the possibility of an alternative or an outside uninflected by networks. If so many things and relationships are figured as networks, however, then what is not a network? If a network points towards particular logics and qualities of relation in our historical present, what others might we envision in the future? In  many ways, these questions are unanswerable from within the contemporary moment. Instead of seeking an avant-garde approach (to move beyond networks or opting out of networks (in some cases, to recover elements of pre-networked existence, this essay proposes a third orientation: one of ambivalence that operates as a mode of extreme presence. I propose the concept of "network aesthetics," which can be tracked across artistic media and cultural forms, as a model, style, and pedagogy for approaching interconnection in the twenty-first century. The following essay is excerpted from Network Ambivalence (Forthcoming from University of Chicago Press. 

  20. Network neuroscience.

    Science.gov (United States)

    Bassett, Danielle S; Sporns, Olaf

    2017-02-23

    Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.

  1. Network Science

    National Research Council Canada - National Science Library

    Leland, Will

    2006-01-01

    OVERVIEW: (1) A committee of technical experts, military officers and R&D managers was assembled by the National Research Council to reach consensus on the nature of networks and network research. (2...

  2. Alliance networks

    OpenAIRE

    Sroka, Władzimierz

    2015-01-01

    The article deals with the problems of cooperation in network organizations. The structure of the text is divided into a couple of parts. Firstly, the increasing importance of alliance networks is described. Secondly, the concept of alliance networks as well as the essence of multinational corporations are presented. Beside theoretical deliberations, two practical cases are presented in the text too. First case relates to the Toyota keiretsu and the second one describes the network organizati...

  3. Network Simulation

    CERN Document Server

    Fujimoto, Richard

    2006-01-01

    "Network Simulation" presents a detailed introduction to the design, implementation, and use of network simulation tools. Discussion topics include the requirements and issues faced for simulator design and use in wired networks, wireless networks, distributed simulation environments, and fluid model abstractions. Several existing simulations are given as examples, with details regarding design decisions and why those decisions were made. Issues regarding performance and scalability are discussed in detail, describing how one can utilize distributed simulation methods to increase the

  4. Network Coding

    Indian Academy of Sciences (India)

    message symbols downstream, network coding achieves vast performance gains by permitting intermediate nodes to carry out algebraic oper- ations on the incoming data. In this article we present a tutorial introduction to network coding as well as an application to the e±cient operation of distributed data-storage networks.

  5. Network Coding

    Indian Academy of Sciences (India)

    Network coding is a technique to increase the amount of information °ow in a network by mak- ing the key observation that information °ow is fundamentally different from commodity °ow. Whereas, under traditional methods of opera- tion of data networks, intermediate nodes are restricted to simply forwarding their incoming.

  6. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimise the management of the Technical Network (TN), to facilitate understanding of the purpose of devices connected to the TN and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive e-mails from IT/CS asking them to add the corresponding information in the network database at "network-cern-ch". Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  7. Network workshop

    DEFF Research Database (Denmark)

    Bruun, Jesper; Evans, Robert Harry

    2014-01-01

    This paper describes the background for, realisation of and author reflections on a network workshop held at ESERA2013. As a new research area in science education, networks offer a unique opportunity to visualise and find patterns and relationships in complicated social or academic network data...... research community. With this workshop, participants were offered a way into network science based on authentic educational research data. The workshop was constructed as an inquiry lesson with emphasis on user autonomy. Learning activities had participants choose to work with one of two cases of networks...

  8. Network science

    CERN Document Server

    Barabasi, Albert-Laszlo

    2016-01-01

    Networks are everywhere, from the Internet, to social networks, and the genetic networks that determine our biological existence. Illustrated throughout in full colour, this pioneering textbook, spanning a wide range of topics from physics to computer science, engineering, economics and the social sciences, introduces network science to an interdisciplinary audience. From the origins of the six degrees of separation to explaining why networks are robust to random failures, the author explores how viruses like Ebola and H1N1 spread, and why it is that our friends have more friends than we do. Using numerous real-world examples, this innovatively designed text includes clear delineation between undergraduate and graduate level material. The mathematical formulas and derivations are included within Advanced Topics sections, enabling use at a range of levels. Extensive online resources, including films and software for network analysis, make this a multifaceted companion for anyone with an interest in network sci...

  9. Vulnerability of network of networks

    Science.gov (United States)

    Havlin, S.; Kenett, D. Y.; Bashan, A.; Gao, J.; Stanley, H. E.

    2014-10-01

    Our dependence on networks - be they infrastructure, economic, social or others - leaves us prone to crises caused by the vulnerabilities of these networks. There is a great need to develop new methods to protect infrastructure networks and prevent cascade of failures (especially in cases of coupled networks). Terrorist attacks on transportation networks have traumatized modern societies. With a single blast, it has become possible to paralyze airline traffic, electric power supply, ground transportation or Internet communication. How, and at which cost can one restructure the network such that it will become more robust against malicious attacks? The gradual increase in attacks on the networks society depends on - Internet, mobile phone, transportation, air travel, banking, etc. - emphasize the need to develop new strategies to protect and defend these crucial networks of communication and infrastructure networks. One example is the threat of liquid explosives a few years ago, which completely shut down air travel for days, and has created extreme changes in regulations. Such threats and dangers warrant the need for new tools and strategies to defend critical infrastructure. In this paper we review recent advances in the theoretical understanding of the vulnerabilities of interdependent networks with and without spatial embedding, attack strategies and their affect on such networks of networks as well as recently developed strategies to optimize and repair failures caused by such attacks.

  10. Human brain networks in physiological aging: a graph theoretical analysis of cortical connectivity from EEG data.

    Science.gov (United States)

    Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria

    2014-01-01

    Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.

  11. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Krigslund, Jeppe; Hansen, Jonas; Roetter, Daniel Enrique Lucani

    2015-01-01

    incorporate content caching and storage, all of which are key challenges of the future Internet and the upcoming 5G networks. This paper proposes some of the keys behind this intersection and supports it with use cases as well as a an implementation that integrated the Kodo library (NC) into OpenFlow (SDN......Software Defined Networking (SDN) and Network Coding (NC) are two key concepts in networking that have garnered a large attention in recent years. On the one hand, SDN's potential to virtualize services in the Internet allows a large flexibility not only for routing data, but also to manage...... buffering, scheduling, and processing over the network. On the other hand, NC has shown great potential for increasing robustness and performance when deployed on intermediate nodes in the network. This new paradigm changes the dynamics of network protocols, requiring new designs that exploit its potential...

  12. Network Coded Software Defined Networking

    DEFF Research Database (Denmark)

    Hansen, Jonas; Roetter, Daniel Enrique Lucani; Krigslund, Jeppe

    2015-01-01

    Software defined networking has garnered large attention due to its potential to virtualize services in the Internet, introducing flexibility in the buffering, scheduling, processing, and routing of data in network routers. SDN breaks the deadlock that has kept Internet network protocols stagnant...... for decades, while applications and physical links have evolved. This article advocates for the use of SDN to bring about 5G network services by incorporating network coding (NC) functionalities. The latter constitutes a major leap forward compared to the state-of-the- art store and forward Internet paradigm....... The inherent flexibility of both SDN and NC provides fertile ground to envision more efficient, robust, and secure networking designs, which may also incorporate content caching and storage, all of which are key challenges of the upcoming 5G networks. This article not only proposes the fundamentals...

  13. Innovation networks

    OpenAIRE

    Ahrweiler, Petra; Keane, Mark T.

    2013-01-01

    This paper advances a framework for modeling the component interactions between cognitive and social aspects of scientific creativity and technological innovation. Specifically, it aims to characterize Innovation Networks; those networks that involve the interplay of people, ideas and organizations to create new, technologically feasible, commercially-realizable products, processes and organizational structures. The tri-partite framework captures networks of ideas (Concept Level), people (Ind...

  14. Overlay Network

    OpenAIRE

    Kronstrand, Alexander; Holmqvist, Andreas

    2015-01-01

    Nowadays, optical fiber is widely used in several areas, especially in communication networking. The main reason is that optical fiber has low attenuation and high bandwidth. However, the switching functionality is performed in the electrical domain (inside the router), thus we have transmission delays in the network lanes. In this study we explore the possibility of developing a hardware “plug-in” that can be connected in parallel with routers of the network enabling the router with “plug-in...

  15. Technical Network

    CERN Multimedia

    2007-01-01

    In order to optimize the management of the Technical Network (TN), to ease the understanding and purpose of devices connected to the TN, and to improve security incident handling, the Technical Network Administrators and the CNIC WG have asked IT/CS to verify the "description" and "tag" fields of devices connected to the TN. Therefore, persons responsible for systems connected to the TN will receive email notifications from IT/CS asking them to add the corresponding information in the network database. Thank you very much for your cooperation. The Technical Network Administrators & the CNIC WG

  16. Network security

    CERN Document Server

    Perez, André

    2014-01-01

    This book introduces the security mechanisms deployed in Ethernet, Wireless-Fidelity (Wi-Fi), Internet Protocol (IP) and MultiProtocol Label Switching (MPLS) networks. These mechanisms are grouped throughout the book according to the following four functions: data protection, access control, network isolation, and data monitoring. Data protection is supplied by data confidentiality and integrity control services. Access control is provided by a third-party authentication service. Network isolation is supplied by the Virtual Private Network (VPN) service. Data monitoring consists of applying

  17. Network cohesion

    OpenAIRE

    Cavalcanti, Tiago V. V.; Giannitsarou, Chryssi; Johnson, Charles R.

    2016-01-01

    This is the final version of the article. It first appeared from Springer via http://dx.doi.org/10.1007/s00199-016-0992-1 We define a measure of network cohesion and show how it arises naturally in a broad class of dynamic models of endogenous perpetual growth with network externalities. Via a standard growth model, we show why network cohesion is crucial for conditional convergence and explain that as cohesion increases, convergence is faster. We prove properties of network cohesion and d...

  18. Analysis of inter-country input-output table based on bibliographic coupling network: How industrial sectors on the GVC compete for production resources

    Science.gov (United States)

    Guan, Jun; Xu, Xiaoyu; Xing, Lizhi

    2018-03-01

    The input-output table is comprehensive and detailed in describing national economic systems with abundance of economic relationships depicting information of supply and demand among industrial sectors. This paper focuses on how to quantify the degree of competition on the global value chain (GVC) from the perspective of econophysics. Global Industrial Strongest Relevant Network models are established by extracting the strongest and most immediate industrial relevance in the global economic system with inter-country input-output (ICIO) tables and then have them transformed into Global Industrial Resource Competition Network models to analyze the competitive relationships based on bibliographic coupling approach. Three indicators well suited for the weighted and undirected networks with self-loops are introduced here, including unit weight for competitive power, disparity in the weight for competitive amplitude and weighted clustering coefficient for competitive intensity. Finally, these models and indicators were further applied empirically to analyze the function of industrial sectors on the basis of the latest World Input-Output Database (WIOD) in order to reveal inter-sector competitive status during the economic globalization.

  19. Overlay networks toward information networking

    CERN Document Server

    Tarkoma, Sasu

    2010-01-01

    With their ability to solve problems in massive information distribution and processing, while keeping scaling costs low, overlay systems represent a rapidly growing area of R&D with important implications for the evolution of Internet architecture. Inspired by the author's articles on content based routing, Overlay Networks: Toward Information Networking provides a complete introduction to overlay networks. Examining what they are and what kind of structures they require, the text covers the key structures, protocols, and algorithms used in overlay networks. It reviews the current state of th

  20. Network Protocols

    NARCIS (Netherlands)

    Tanenbaum, A.S.

    1981-01-01

    Dunng the last ten years, many computer networks have been designed, implemented, and put into service in the United States, Canada, Europe, Japan, and elsewhere. From the experience obtamed with these networks, certain key design principles have begun to emerge, principles that can be used to

  1. Organizational Networks

    DEFF Research Database (Denmark)

    Sørensen, Ole Henning; Grande, Bård

    1996-01-01

    The paper focuses on the concept of organizational networks. Four different uses of the concept are identified and critically discussed.......The paper focuses on the concept of organizational networks. Four different uses of the concept are identified and critically discussed....

  2. Bipartite Networks

    NARCIS (Netherlands)

    Agneessens, F.; Moser, C.; Barnett, G.A.

    2011-01-01

    Bipartite networks refer to a specific kind of network in which the nodes (or actors) can be partitioned into two subsets based on the fact that no links exist between actors within each subset, but only between the two subsets. Due to the partition of actors in two sets and the absence of relations

  3. Networked Identities

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Larsen, Malene Charlotte

    2008-01-01

    In this article we take up a critique of the concept of Communities of Practice (CoP) voiced by several authors, who suggest that networks may provide a better metaphor to understand social forms of organisation and learning. Through a discussion of the notion of networked learning and the critique...

  4. Network Affordances

    DEFF Research Database (Denmark)

    Samson, Audrey; Soon, Winnie

    2015-01-01

    This paper examines the notion of network affordance within the context of network art. Building on Gibson's theory (Gibson, 1979) we understand affordance as the perceived and actual parameters of a thing. We expand on Gaver's affordance of predictability (Gaver, 1996) to include ecological...... and computational parameters of unpredictability. We illustrate the notion of unpredictability by considering four specific works that were included in a network art exhibiton, SPEED SHOW [2.0] Hong Kong. The paper discusses how the artworks are contingent upon the parameteric relations (Parisi, 2013......), of the network. We introduce network affordance as a dynamic framework that could articulate the experienced tension arising from the (visible) symbolic representation of computational processes and its hidden occurrences. We base our proposal on the experience of both organising the SPEED SHOW and participating...

  5. Managing Networks

    DEFF Research Database (Denmark)

    Jørgensen, Heidi; Vintergaard, Christian

    Logically it seems that companies pursuing different business strategies wouldalso manage their relationships with other firms accordingly. Nevertheless, due tothe lack of research in the field of network strategies, this link still remainsinadequately examined. Based on the well-known framework...... of organisationalbehaviour developed by Miles and Snow (1978), this paper argues that thepatterns of network behaviour practiced by firms greatly depend on the businesstypology of the company. That is, a company's business typology will to a certaindegree dictate the network identity of the company. In this paper evidence...... elementsdistinguishing the types of network behaviour in relation to the business typology.The paper thus strives to argue how different business typologies develop anetwork identity on the basis of their network behaviour. Due to the correlationbetween a company's strategy, structure and processes and its pattern...

  6. Technological Networks

    Science.gov (United States)

    Mitra, Bivas

    The study of networks in the form of mathematical graph theory is one of the fundamental pillars of discrete mathematics. However, recent years have witnessed a substantial new movement in network research. The focus of the research is shifting away from the analysis of small graphs and the properties of individual vertices or edges to consideration of statistical properties of large scale networks. This new approach has been driven largely by the availability of technological networks like the Internet [12], World Wide Web network [2], etc. that allow us to gather and analyze data on a scale far larger than previously possible. At the same time, technological networks have evolved as a socio-technological system, as the concepts of social systems that are based on self-organization theory have become unified in technological networks [13]. In today’s society, we have a simple and universal access to great amounts of information and services. These information services are based upon the infrastructure of the Internet and the World Wide Web. The Internet is the system composed of ‘computers’ connected by cables or some other form of physical connections. Over this physical network, it is possible to exchange e-mails, transfer files, etc. On the other hand, the World Wide Web (commonly shortened to the Web) is a system of interlinked hypertext documents accessed via the Internet where nodes represent web pages and links represent hyperlinks between the pages. Peer-to-peer (P2P) networks [26] also have recently become a popular medium through which huge amounts of data can be shared. P2P file sharing systems, where files are searched and downloaded among peers without the help of central servers, have emerged as a major component of Internet traffic. An important advantage in P2P networks is that all clients provide resources, including bandwidth, storage space, and computing power. In this chapter, we discuss these technological networks in detail. The review

  7. Accelerating networks

    International Nuclear Information System (INIS)

    Smith, David M D; Onnela, Jukka-Pekka; Johnson, Neil F

    2007-01-01

    Evolving out-of-equilibrium networks have been under intense scrutiny recently. In many real-world settings the number of links added per new node is not constant but depends on the time at which the node is introduced in the system. This simple idea gives rise to the concept of accelerating networks, for which we review an existing definition and-after finding it somewhat constrictive-offer a new definition. The new definition provided here views network acceleration as a time dependent property of a given system as opposed to being a property of the specific algorithm applied to grow the network. The definition also covers both unweighted and weighted networks. As time-stamped network data becomes increasingly available, the proposed measures may be easily applied to such empirical datasets. As a simple case study we apply the concepts to study the evolution of three different instances of Wikipedia, namely, those in English, German, and Japanese, and find that the networks undergo different acceleration regimes in their evolution

  8. Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs.

    Science.gov (United States)

    Le, Duc-Hau; Verbeke, Lieven; Son, Le Hoang; Chu, Dinh-Toi; Pham, Van-Huy

    2017-11-14

    MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable

  9. Social networks

    CERN Document Server

    Etaner-Uyar, A Sima

    2014-01-01

    The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many

  10. Network Warrior

    CERN Document Server

    Donahue, Gary

    2011-01-01

    Pick up where certification exams leave off. With this practical, in-depth guide to the entire network infrastructure, you'll learn how to deal with real Cisco networks, rather than the hypothetical situations presented on exams like the CCNA. Network Warrior takes you step by step through the world of routers, switches, firewalls, and other technologies based on the author's extensive field experience. You'll find new content for MPLS, IPv6, VoIP, and wireless in this completely revised second edition, along with examples of Cisco Nexus 5000 and 7000 switches throughout. Topics include: An

  11. computer networks

    Directory of Open Access Journals (Sweden)

    N. U. Ahmed

    2002-01-01

    Full Text Available In this paper, we construct a new dynamic model for the Token Bucket (TB algorithm used in computer networks and use systems approach for its analysis. This model is then augmented by adding a dynamic model for a multiplexor at an access node where the TB exercises a policing function. In the model, traffic policing, multiplexing and network utilization are formally defined. Based on the model, we study such issues as (quality of service QoS, traffic sizing and network dimensioning. Also we propose an algorithm using feedback control to improve QoS and network utilization. Applying MPEG video traces as the input traffic to the model, we verify the usefulness and effectiveness of our model.

  12. Heterodox networks

    DEFF Research Database (Denmark)

    Lala, Purnima; Kumar, Ambuj

    2016-01-01

    -Configurable Intelligent Distributed Antenna System (SCIDAS)’ that overlays intelligence over the conventional DAS architecture and latter is in the form of a swarm of intelligent hovering base stations working in a team to cooperatively resolve the PTC congestion at the Area of Event (AoE). A suitable network......It is imperative for the service providers to bring innovation in the network design to meet the exponential growth of mobile subscribers for multi-technology future wireless networks. As a matter of research, studies on providing services to moving subscriber groups aka ‘Place Time Capacity (PTC...... architecture of ‘Hovering Ad-hoc Network (HANET)’ for the latter will be deployed to assist and manage the overloaded primary base stations enhancing the on-demand coverage and capacity of the entire system. Proposed modes can either operate independently or as a cascaded architecture to form a Heterodox...

  13. Organizational Networks

    DEFF Research Database (Denmark)

    Grande, Bård; Sørensen, Ole Henning

    1998-01-01

    The paper focuses on the concept of organizational networks. Four different uses of the concept of organizational network are identified and critically discussed. Special focus is placed on how information and communication technologies as communication mediators and cognitive pictures influence...... the organizational forms discussed in the paper. It is asserted that the underlying organizational phenomena are not changing but that the manifestations and representations are shifting due to technological developments....

  14. Pintadas network

    OpenAIRE

    Cruz, Maria do Carmo Meirelles T.

    2006-01-01

    The Pintadas Network has been organized in Pintadas, a small municipality (11.254 inhabitants) in Bahia, located in the semi-arid region. It has been composed by civil society organizacions (social, productive, cultural and religious organizations and a credit cooperative), with support from the local town hall and from national and international institutions. The Network is a space for articulation, which intends to formulate, execute, follow-up, inspect and evaluate the municipal public pol...

  15. Neural networks

    International Nuclear Information System (INIS)

    Denby, Bruce; Lindsey, Clark; Lyons, Louis

    1992-01-01

    The 1980s saw a tremendous renewal of interest in 'neural' information processing systems, or 'artificial neural networks', among computer scientists and computational biologists studying cognition. Since then, the growth of interest in neural networks in high energy physics, fueled by the need for new information processing technologies for the next generation of high energy proton colliders, can only be described as explosive

  16. Network Flows

    Science.gov (United States)

    1988-12-01

    n Vlog n ), which is a linear time algorithm for all but the sparsest classes of shortest path problems. 3.4. Label Correcting Algorithms Label...11962] (Programming , Games and Transportation Networks), Iri (1969] (Network Flows, Transportation and Scheduling), Hu [1969] (Integer Programming and...though the improvements are not as dramatic as they have been for E>inic’s and the FIFO preflow push algorithms. For example, the 0(nm + n^ Vlog U

  17. An Analysis of Central Residues Between Ligand-Bound and Ligand-Free Protein Structures Based on Network Approach.

    Science.gov (United States)

    Amala, Arumugam; Emerson, Isacc Arnold

    2017-08-01

    Depiction of protein structures as networks of interacting residues has enabled us to understand the structure and function of the protein. Previous investigations on closeness centrality have identified protein functional sites from three- dimensional structures. It is well recognized that ligand binding to a receptor protein induces a wide range of structural changes. An interesting question is how central residues function during conformational changes triggered during ligand binding? The aim of this study is to comprehend at what extent central residues change during ligand binding to receptor proteins. To determine this, we examined 37 pairs of protein structures consisting of ligand-bound and ligand-free forms. These protein structures were modelled as an undirected network and significant central residues were obtained using residue centrality measures. In addition to these, the basic network parameters were also analysed. On analysing the residue centrality measures, we observed that 60% of central residues were common in both the ligand-bound and ligand-free states. The geometry of the central residues revealed that they were situated closer to the protein center of the mass. Finally, we demonstrated the effectiveness of central residues in amino acids substitutions and in the evolution itself. The closeness centrality was also analyzed among different protein domain sizes and the values gradually declined from single-domains to multi-domain proteins suggesting that the network has potential for hierarchical organization. Betweenness centrality measure was also used to determine the central residues and 31% of these residues were common between the holo/apo states. Findings reveal that central residues play a significant role in determining the functional properties of proteins. These results have implications in predicting binding/active site residues, specifically in the context of drug designing, if additional information concerning ligand binding is

  18. Sentient networks

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G.

    1998-03-01

    The engineering problems of constructing autonomous networks of sensors and data processors that can provide alerts for dangerous situations provide a new context for debating the question whether man-made systems can emulate the cognitive capabilities of the mammalian brain. In this paper we consider the question whether a distributed network of sensors and data processors can form ``perceptions`` based on sensory data. Because sensory data can have exponentially many explanations, the use of a central data processor to analyze the outputs from a large ensemble of sensors will in general introduce unacceptable latencies for responding to dangerous situations. A better idea is to use a distributed ``Helmholtz machine`` architecture in which the sensors are connected to a network of simple processors, and the collective state of the network as a whole provides an explanation for the sensory data. In general communication within such a network will require time division multiplexing, which opens the door to the possibility that with certain refinements to the Helmholtz machine architecture it may be possible to build sensor networks that exhibit a form of artificial consciousness.

  19. Complex Networks

    CERN Document Server

    Evsukoff, Alexandre; González, Marta

    2013-01-01

    In the last decade we have seen the emergence of a new inter-disciplinary field focusing on the understanding of networks which are dynamic, large, open, and have a structure sometimes called random-biased. The field of Complex Networks is helping us better understand many complex phenomena such as the spread of  deseases, protein interactions, social relationships, to name but a few. Studies in Complex Networks are gaining attention due to some major scientific breakthroughs proposed by network scientists helping us understand and model interactions contained in large datasets. In fact, if we could point to one event leading to the widespread use of complex network analysis is the availability of online databases. Theories of Random Graphs from Erdös and Rényi from the late 1950s led us to believe that most networks had random characteristics. The work on large online datasets told us otherwise. Starting with the work of Barabási and Albert as well as Watts and Strogatz in the late 1990s, we now know th...

  20. The Intellectual Structure of Research on Educational Technology in Science Education (ETiSE): A Co-citation Network Analysis of Publications in Selected Journals (2008-2013)

    Science.gov (United States)

    Tang, Kai-Yu; Tsai, Chin-Chung

    2016-01-01

    The main purpose of this paper is to investigate the intellectual structure of the research on educational technology in science education (ETiSE) within the most recent years (2008-2013). Based on the criteria for educational technology research and the citation threshold for educational co-citation analysis, a total of 137 relevant ETiSE papers were identified from the International Journal of Science Education, the Journal of Research in Science Teaching, Science Education, and the Journal of Science Education and Technology. Then, a series of methodologies were performed to analyze all 137 source documents, including document co-citation analysis, social network analysis, and exploratory factor analysis. As a result, 454 co-citation ties were obtained and then graphically visualized with an undirected network, presenting a global structure of the current ETiSE research network. In addition, four major underlying intellectual subfields within the main component of the ETiSE network were extracted and named as: (1) technology-enhanced science inquiry, (2) simulation and visualization for understanding, (3) technology-enhanced chemistry learning, and (4) game-based science learning. The most influential co-citation pairs and cross-boundary phenomena were then analyzed and visualized in a co-citation network. This is the very first attempt to illuminate the core ideas underlying ETiSE research by integrating the co-citation method, factor analysis, and the networking visualization technique. The findings of this study provide a platform for scholarly discussion of the dissemination and research trends within the current ETiSE literature.

  1. Neural Networks

    International Nuclear Information System (INIS)

    Smith, Patrick I.

    2003-01-01

    Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

  2. Brain network analysis: separating cost from topology using cost-integration.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    Full Text Available A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i differences in weighted costs and (ii differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.

  3. Brain network analysis: separating cost from topology using cost-integration.

    Science.gov (United States)

    Ginestet, Cedric E; Nichols, Thomas E; Bullmore, Ed T; Simmons, Andrew

    2011-01-01

    A statistically principled way of conducting brain network analysis is still lacking. Comparison of different populations of brain networks is hard because topology is inherently dependent on wiring cost, where cost is defined as the number of edges in an unweighted graph. In this paper, we evaluate the benefits and limitations associated with using cost-integrated topological metrics. Our focus is on comparing populations of weighted undirected graphs that differ in mean association weight, using global efficiency. Our key result shows that integrating over cost is equivalent to controlling for any monotonic transformation of the weight set of a weighted graph. That is, when integrating over cost, we eliminate the differences in topology that may be due to a monotonic transformation of the weight set. Our result holds for any unweighted topological measure, and for any choice of distribution over cost levels. Cost-integration is therefore helpful in disentangling differences in cost from differences in topology. By contrast, we show that the use of the weighted version of a topological metric is generally not a valid approach to this problem. Indeed, we prove that, under weak conditions, the use of the weighted version of global efficiency is equivalent to simply comparing weighted costs. Thus, we recommend the reporting of (i) differences in weighted costs and (ii) differences in cost-integrated topological measures with respect to different distributions over the cost domain. We demonstrate the application of these techniques in a re-analysis of an fMRI working memory task. We also provide a Monte Carlo method for approximating cost-integrated topological measures. Finally, we discuss the limitations of integrating topology over cost, which may pose problems when some weights are zero, when multiplicities exist in the ranks of the weights, and when one expects subtle cost-dependent topological differences, which could be masked by cost-integration.

  4. Nuclear networking.

    Science.gov (United States)

    Xie, Wei; Burke, Brian

    2017-07-04

    Nuclear lamins are intermediate filament proteins that represent important structural components of metazoan nuclear envelopes (NEs). By combining proteomics and superresolution microscopy, we recently reported that both A- and B-type nuclear lamins form spatially distinct filament networks at the nuclear periphery of mouse fibroblasts. In particular, A-type lamins exhibit differential association with nuclear pore complexes (NPCs). Our studies reveal that the nuclear lamina network in mammalian somatic cells is less ordered and more complex than that of amphibian oocytes, the only other system in which the lamina has been visualized at high resolution. In addition, the NPC component Tpr likely links NPCs to the A-type lamin network, an association that appears to be regulated by C-terminal modification of various A-type lamin isoforms. Many questions remain, however, concerning the structure and assembly of lamin filaments, as well as with their mode of association with other nuclear components such as peripheral chromatin.

  5. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    network” should not be seen as an organizational form but as a perspective that can be used to enrich one's understanding of organizations. The industrial network perspective has three basic building blocks: actors, resources, and activities. The three building blocks and their relations constitute...... the focus of operations management from managing the own organization to continuously developing and managing a network of external and internal resources forming a production system. This perspective may be called managing an “extraprise” rather than an “enterprise.” It should be noted that “an industrial...

  6. Industrial Networks

    DEFF Research Database (Denmark)

    Karlsson, Christer

    2015-01-01

    the focus of operations management from managing the own organization to continuously developing and managing a network of external and internal resources forming a production system. This perspective may be called managing an “extraprise” rather than an “enterprise.” It should be noted that “an industrial...... network” should not be seen as an organizational form but as a perspective that can be used to enrich one's understanding of organizations. The industrial network perspective has three basic building blocks: actors, resources, and activities. The three building blocks and their relations constitute...

  7. Regularized estimation of large-scale gene association networks using graphical Gaussian models.

    Science.gov (United States)

    Krämer, Nicole; Schäfer, Juliane; Boulesteix, Anne-Laure

    2009-11-24

    Graphical Gaussian models are popular tools for the estimation of (undirected) gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of samples is the estimation of the matrix of partial correlations. Since the (Moore-Penrose) inverse of the sample covariance matrix leads to poor estimates in this scenario, standard methods are inappropriate and adequate regularization techniques are needed. Popular approaches include biased estimates of the covariance matrix and high-dimensional regression schemes, such as the Lasso and Partial Least Squares. In this article, we investigate a general framework for combining regularized regression methods with the estimation of Graphical Gaussian models. This framework includes various existing methods as well as two new approaches based on ridge regression and adaptive lasso, respectively. These methods are extensively compared both qualitatively and quantitatively within a simulation study and through an application to six diverse real data sets. In addition, all proposed algorithms are implemented in the R package "parcor", available from the R repository CRAN. In our simulation studies, the investigated non-sparse regression methods, i.e. Ridge Regression and Partial Least Squares, exhibit rather conservative behavior when combined with (local) false discovery rate multiple testing in order to decide whether or not an edge is present in the network. For networks with higher densities, the difference in performance of the methods decreases. For sparse networks, we confirm the Lasso's well known tendency towards selecting too many edges, whereas the two-stage adaptive Lasso is an interesting alternative that provides sparser solutions. In our simulations, both sparse and non-sparse methods are able to reconstruct networks with cluster structures. On six real data sets, we also clearly distinguish the results obtained using the non-sparse methods and those obtained

  8. Regularized estimation of large-scale gene association networks using graphical Gaussian models

    Directory of Open Access Journals (Sweden)

    Schäfer Juliane

    2009-11-01

    Full Text Available Abstract Background Graphical Gaussian models are popular tools for the estimation of (undirected gene association networks from microarray data. A key issue when the number of variables greatly exceeds the number of samples is the estimation of the matrix of partial correlations. Since the (Moore-Penrose inverse of the sample covariance matrix leads to poor estimates in this scenario, standard methods are inappropriate and adequate regularization techniques are needed. Popular approaches include biased estimates of the covariance matrix and high-dimensional regression schemes, such as the Lasso and Partial Least Squares. Results In this article, we investigate a general framework for combining regularized regression methods with the estimation of Graphical Gaussian models. This framework includes various existing methods as well as two new approaches based on ridge regression and adaptive lasso, respectively. These methods are extensively compared both qualitatively and quantitatively within a simulation study and through an application to six diverse real data sets. In addition, all proposed algorithms are implemented in the R package "parcor", available from the R repository CRAN. Conclusion In our simulation studies, the investigated non-sparse regression methods, i.e. Ridge Regression and Partial Least Squares, exhibit rather conservative behavior when combined with (local false discovery rate multiple testing in order to decide whether or not an edge is present in the network. For networks with higher densities, the difference in performance of the methods decreases. For sparse networks, we confirm the Lasso's well known tendency towards selecting too many edges, whereas the two-stage adaptive Lasso is an interesting alternative that provides sparser solutions. In our simulations, both sparse and non-sparse methods are able to reconstruct networks with cluster structures. On six real data sets, we also clearly distinguish the results

  9. Network Coding

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 15; Issue 7. Network Coding. K V Rashmi Nihar B Shah P Vijay Kumar. General Article Volume 15 Issue 7 July 2010 pp 604-621. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/015/07/0604-0621 ...

  10. Network Survivability

    DEFF Research Database (Denmark)

    Marzo, José L.; Stidsen, Thomas Riis; Ruepp, Sarah Renée

    2010-01-01

    – are vital to modern services such as mobile telephony, online banking and VoIP. This book examines communication networking from a mathematical viewpoint. The contributing authors took part in the European COST action 293 – a four-year program of multidisciplinary research on this subject. In this book...

  11. Telecommunication Networks

    DEFF Research Database (Denmark)

    Olsen, Rasmus Løvenstein; Balachandran, Kartheepan; Hald, Sara Ligaard

    2014-01-01

    In this chapter, we look into the role of telecommunication networks and their capability of supporting critical infrastructure systems and applications. The focus is on smart grids as the key driving example, bearing in mind that other such systems do exist, e.g., water management, traffic control...

  12. Information spread in networks: Games, optimal control, and stabilization

    Science.gov (United States)

    Khanafer, Ali

    , that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control.

  13. Introduction to neural networks

    CERN Document Server

    James, Frederick E

    1994-02-02

    1. Introduction and overview of Artificial Neural Networks. 2,3. The Feed-forward Network as an inverse Problem, and results on the computational complexity of network training. 4.Physics applications of neural networks.

  14. Neural Networks

    Directory of Open Access Journals (Sweden)

    Schwindling Jerome

    2010-04-01

    Full Text Available This course presents an overview of the concepts of the neural networks and their aplication in the framework of High energy physics analyses. After a brief introduction on the concept of neural networks, the concept is explained in the frame of neuro-biology, introducing the concept of multi-layer perceptron, learning and their use as data classifer. The concept is then presented in a second part using in more details the mathematical approach focussing on typical use cases faced in particle physics. Finally, the last part presents the best way to use such statistical tools in view of event classifers, putting the emphasis on the setup of the multi-layer perceptron. The full article (15 p. corresponding to this lecture is written in french and is provided in the proceedings of the book SOS 2008.

  15. Networking Japan

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    and activities in Japan. One concrete example was the earthquake relief Japan received from alumni in 2011. The exchanges have also already inspired an explicit focus on private sector and middle income countries in the Japanese Development Cooperation Charter announced in February 2015.......Human Resource Development was the first and remains an important pillar in Japanese foreign aid. I will argue that Japan has access to a global network of alumni who will co-define Japanese foreign aid in the future, because Japan has encouraged alumni societies and networking since 1965. A total...... of more than a million people in more than 100 countries have attended courses in Japan funded fully or partly by Japanese ODA since the inception of the technical assistance programs in 1954 through the Colombo Plan and since 1959 through the Association of Overseas Technical Scholarships (AOTS from 2009...

  16. Loss Networks

    OpenAIRE

    Kelly, F. P.

    1991-01-01

    This paper describes work on the stochastic modelling of loss networks. Such systems have long been of interest to telephone engineers and are becoming increasingly important as models of computer and information systems. Throughout the century problems from this field have provided an impetus to the development of probability theory, pure and applied. This paper provides an introduction to the area and a review of recent work.

  17. Linear network theory

    CERN Document Server

    Sander, K F

    1964-01-01

    Linear Network Theory covers the significant algebraic aspect of network theory, with minimal reference to practical circuits. The book begins the presentation of network analysis with the exposition of networks containing resistances only, and follows it up with a discussion of networks involving inductance and capacity by way of the differential equations. Classification and description of certain networks, equivalent networks, filter circuits, and network functions are also covered. Electrical engineers, technicians, electronics engineers, electricians, and students learning the intricacies

  18. Temperature rise due to mechanical energy dissipation in undirectional thermoplastic composites(AS4/PEEK)

    Science.gov (United States)

    Georgious, I. T.; Sun, C. T.

    1992-01-01

    The history of temperature rise due to internal dissipation of mechanical energy in insulated off-axis uniaxial specimens of the unidirectional thermoplastic composite (AS4/PEEK) has been measured. The experiment reveals that the rate of temperature rise is a polynomial function of stress amplitude: It consists of a quadratic term and a sixth power term. This fact implies that the specific heat of the composite depends on the stretching its microstructure undergoes during deformation. The Einstein theory for specific heat is used to explain the dependence of the specific heat on the stretching of the microstructure.

  19. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  20. Networks of networks – An introduction

    International Nuclear Information System (INIS)

    Kenett, Dror Y.; Perc, Matjaž; Boccaletti, Stefano

    2015-01-01

    Graphical abstract: Interdependent network reciprocity. Only those blue cooperative domains that are initially present on both networks survive. Abstract: This is an introduction to the special issue titled “Networks of networks” that is in the making at Chaos, Solitons & Fractals. Recent research and reviews attest to the fact that networks of networks are the next frontier in network science [1–7]. Not only are interactions limited and thus inadequately described by well-mixed models, it is also a fact that the networks that should be an integral part of such models are often interconnected, thus making the processes that are unfolding on them interdependent. From the World economy and transportation systems to social media, it is clear that processes taking place in one network might significantly affect what is happening in many other networks. Within an interdependent system, each type of interaction has a certain relevance and meaning, so that treating all the links identically inevitably leads to information loss. Networks of networks, interdependent networks, or multilayer networks are therefore a much better and realistic description of such systems, and this Special Issue is devoted to their structure, dynamics and evolution, as well as to the study of emergent properties in multi-layered systems in general. Topics of interest include but are not limited to the spread of epidemics and information, percolation, diffusion, synchronization, collective behavior, and evolutionary games on networks of networks. Interdisciplinary work on all aspects of networks of networks, regardless of background and motivation, is very welcome.

  1. Green mobile networks a networking perspective

    CERN Document Server

    Ansari, Nirwan

    2016-01-01

    Combines the hot topics of energy efficiency and next generation mobile networking, examining techniques and solutions. Green communications is a very hot topic. Ever increasing mobile network bandwidth rates significantly impacts on operating costs due to aggregate network energy consumption. As such, design on 4G networks and beyond has increasingly started to focus on 'energy efficiency' or so-called 'green' networks. Many techniques and solutions have been proposed to enhance the energy efficiency of mobile networks, yet no book has provided an in-depth analysis of the energy consumption issues in mobile networks nor offers detailed theories, tools and solutions for solving the energy efficiency problems.

  2. Open innovation in networks

    DEFF Research Database (Denmark)

    Hu, Yimei

    Open innovation in networks has been a popular topic for long, this paper rethinks the concepts of innovation network and network organization, and clarifies the differences between them based on the network perspective. Network perspective means that: network is the context of firms; market...... and hierarchy can be analyzed from a network approach. Within a network perspective, there are different levels of network, and a firm may not always has the power to “manage” innovation networks due to different levels of power. Based on the strength of a firm’s power, its role may varies from manager...

  3. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2017-01-01

    the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century.......Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...

  4. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2017-01-01

    Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...... the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  5. ENLIGHT Network

    CERN Multimedia

    Ballantine, A; Dixon-Altaber, H; Dosanjh, M; Kuchina, L

    2011-01-01

    State-of-the-art techniques borrowed from particle accelerators and detectors are a key element in hadrontherapy and several European projects are actively fostering the collaboration amongst the various disciplines and countries. ENLIGHT was established in 2002 to coordinate these European efforts in hadron therapy. The ENLIGHT network is formed by the European hadrontherapy Community, with more than 300 participants from twenty European countries. A major achievement of ENLIGHT has been the blending of traditionally separate communities so that clinicians, physicists, biologists and engineers with experience and interest in particle therapy are working together.

  6. Network Society

    DEFF Research Database (Denmark)

    Clausen, Lars; Tække, Jesper

    2018-01-01

    Strategic communication needs a thorough understanding of the social forms of interaction, organization and social structure, it works within and through. Success is a scarce resource, and organizations compete to fulfill their mission and advance toward specific goals. In this chapter, we present...... the five strands of theory on the network society. Each theoretical position has its specific implications for acting toward strategic goals. In its entirety, the five perspectives give a thorough understanding of the conditions for successful strategic communication in the 21st century....

  7. Mesh network simulation

    OpenAIRE

    Pei, Ping; Petrenko, Y. N.

    2015-01-01

    A Mesh network simulation framework which provides a powerful and concise modeling chain for a network structure will be introduce in this report. Mesh networks has a special topologic structure. The paper investigates a message transfer in wireless mesh network simulation and how does it works in cellular network simulation. Finally the experimental result gave us the information that mesh networks have different principle in transmission way with cellular networks in transmission, and multi...

  8. Communication network exchange

    International Nuclear Information System (INIS)

    Woo, Seung Sul

    1988-05-01

    This book has two parts. The first parts is comprised of five chapters, which deals with communication network constitution with design of network and types, telephone network about outline and management of network, telephone network · data network · private network, international data telephone network about service and international data network and technical standards of quality of service, communication and data. The second parts handles exchange, which is about institution of switching, a manual exchange and step-by step exchange, a crossbar exchange, electronic exchange, international switching system, design of equipment of test and measurement.

  9. Network Visualization Project (NVP)

    Science.gov (United States)

    2016-07-01

    Visualization Project (NVP) by Terry Wen American Society of Engineering Education, Washington, DC Lisa M Marvel Computational and Information Sciences...front-end presentation and construction of the application itself. 15. SUBJECT TERMS computer network traffic, computer network security, computer ...network visualization, network traffic analysis, network forensics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18. NUMBER OF

  10. Visualization of Social Networks

    NARCIS (Netherlands)

    Boertjes, E.M.; Kotterink, B.; Jager, E.J.

    2011-01-01

    Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

  11. Animal transportation networks

    Science.gov (United States)

    Perna, Andrea; Latty, Tanya

    2014-01-01

    Many group-living animals construct transportation networks of trails, galleries and burrows by modifying the environment to facilitate faster, safer or more efficient movement. Animal transportation networks can have direct influences on the fitness of individuals, whereas the shape and structure of transportation networks can influence community dynamics by facilitating contacts between different individuals and species. In this review, we discuss three key areas in the study of animal transportation networks: the topological properties of networks, network morphogenesis and growth, and the behaviour of network users. We present a brief primer on elements of network theory, and then discuss the different ways in which animal groups deal with the fundamental trade-off between the competing network properties of travel efficiency, robustness and infrastructure cost. We consider how the behaviour of network users can impact network efficiency, and call for studies that integrate both network topology and user behaviour. We finish with a prospectus for future research. PMID:25165598

  12. Applied Learning Networks (ALN)

    National Research Council Canada - National Science Library

    Bannister, Joseph; Shen, Wei-Min; Touch, Joseph; Hou, Feili; Pingali, Venkata

    2007-01-01

    Applied Learning Networks (ALN) demonstrates that a network protocol can learn to improve its performance over time, showing how to incorporate learning methods into a general class of network protocols...

  13. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... with changing and increasing demands. Two-layer networks consist of one backbone network, which interconnects cluster networks. The clusters consist of nodes and links, which connect the nodes. One node in each cluster is a hub node, and the backbone interconnects the hub nodes of each cluster and thus...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks...

  14. Introduction to computer networking

    CERN Document Server

    Robertazzi, Thomas G

    2017-01-01

    This book gives a broad look at both fundamental networking technology and new areas that support it and use it. It is a concise introduction to the most prominent, recent technological topics in computer networking. Topics include network technology such as wired and wireless networks, enabling technologies such as data centers, software defined networking, cloud and grid computing and applications such as networks on chips, space networking and network security. The accessible writing style and non-mathematical treatment makes this a useful book for the student, network and communications engineer, computer scientist and IT professional. • Features a concise, accessible treatment of computer networking, focusing on new technological topics; • Provides non-mathematical introduction to networks in their most common forms today;< • Includes new developments in switching, optical networks, WiFi, Bluetooth, LTE, 5G, and quantum cryptography.

  15. Tunable Sparse Network Coding for Multicast Networks

    DEFF Research Database (Denmark)

    Feizi, Soheil; Roetter, Daniel Enrique Lucani; Sørensen, Chres Wiant

    2014-01-01

    This paper shows the potential and key enabling mechanisms for tunable sparse network coding, a scheme in which the density of network coded packets varies during a transmission session. At the beginning of a transmission session, sparsely coded packets are transmitted, which benefits decoding...... complexity. At the end of a transmission, when receivers have accumulated degrees of freedom, coding density is increased. We propose a family of tunable sparse network codes (TSNCs) for multicast erasure networks with a controllable trade-off between completion time performance to decoding complexity....... Coding density tuning can be performed by designing time-dependent coding matrices. In multicast networks, this tuning can be performed within the network by designing time-dependent pre- coding and network coding matrices with mild conditions on the network structure for specific densities. We present...

  16. Reconfigurable Network of Networks for Multiscale Computing

    National Research Council Canada - National Science Library

    Sutton, Jeff

    2001-01-01

    The Network of Networks (NoN) model, which is a neurobiologically motivated smart algorithm co-developed by the PI, is being applied for rapid and accurate image processing of forward and side scan sonar images in turbid environments...

  17. Basics of Computer Networking

    CERN Document Server

    Robertazzi, Thomas

    2012-01-01

    Springer Brief Basics of Computer Networking provides a non-mathematical introduction to the world of networks. This book covers both technology for wired and wireless networks. Coverage includes transmission media, local area networks, wide area networks, and network security. Written in a very accessible style for the interested layman by the author of a widely used textbook with many years of experience explaining concepts to the beginner.

  18. Packet Tracer network simulator

    CERN Document Server

    Jesin, A

    2014-01-01

    A practical, fast-paced guide that gives you all the information you need to successfully create networks and simulate them using Packet Tracer.Packet Tracer Network Simulator is aimed at students, instructors, and network administrators who wish to use this simulator to learn how to perform networking instead of investing in expensive, specialized hardware. This book assumes that you have a good amount of Cisco networking knowledge, and it will focus more on Packet Tracer rather than networking.

  19. The Economics of Networking

    DEFF Research Database (Denmark)

    Sørensen, Olav Jull

    The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory.......The literature on business networks is often oversocialized. The economic side of business is implicitly assumed. This paper analyses the economics of network behavior by loking at each of the key concepts in the Network Theory....

  20. Coded Network Function Virtualization

    DEFF Research Database (Denmark)

    Al-Shuwaili, A.; Simone, O.; Kliewer, J.

    2016-01-01

    Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off-the-shelf ha......Network function virtualization (NFV) prescribes the instantiation of network functions on general-purpose network devices, such as servers and switches. While yielding a more flexible and cost-effective network architecture, NFV is potentially limited by the fact that commercial off...

  1. Local Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio; Sørensen, Lene Tolstrup

    2011-01-01

    Online social networks have become essential for many users in their daily communication. Through a combination of the online social networks with opportunistic networks, a new concept arises: Local Social Networks. The target of local social networks is to promote social networking benefits...... in physical environment in order to leverage personal affinities in the users' surroundings. The purpose of this paper is to present and discuss the concept of local social networks as a new social communication system. Particularly, the preliminary architecture and the prototype of local social networks...

  2. Identity and Professional Networking.

    Science.gov (United States)

    Raj, Medha; Fast, Nathanael J; Fisher, Oliver

    2017-06-01

    Despite evidence that large professional networks afford a host of financial and professional benefits, people vary in how motivated they are to build such networks. To help explain this variance, the present article moves beyond a rational self-interest account to examine the possibility that identity shapes individuals' intentions to network. Study 1 established a positive association between viewing professional networking as identity-congruent and the tendency to prioritize strengthening and expanding one's professional network. Study 2 revealed that manipulating the salience of the self affects networking intentions, but only among those high in networking identity-congruence. Study 3 further established causality by experimentally manipulating identity-congruence to increase networking intentions. Study 4 examined whether identity or self-interest is a better predictor of networking intentions, providing support for the former. These findings indicate that identity influences the networks people develop. Implications for research on the self, identity-based motivation, and professional networking are discussed.

  3. Convex Congestion Network Problems

    NARCIS (Netherlands)

    Quant, M.; Reijnierse, J.H.

    2004-01-01

    This paper analyzes convex congestion network problems.It is shown that for network problems with convex congestion costs, an algorithm based on a shortest path algorithm, can be used to find an optimal network for any coalition. Furthermore an easy way of determining if a given network is optimal

  4. Synchronization of networks

    Indian Academy of Sciences (India)

    For networks with time-varying topology we compare the synchronization properties of these networks with the corresponding time-average network. We find that if the different coupling matrices corresponding to the time-varying networks commute with each other then the stability of the synchronized state for both the ...

  5. Technologies for Home Networking

    DEFF Research Database (Denmark)

    A broad overview of the home networking field, ranging from wireless technologies to practical applications. In the future, it is expected that private networks (e.g. home networks) will become part of the global network ecosystem, participating in sharing their own content, running IP...

  6. Hardening Software Defined Networks

    Science.gov (United States)

    2014-07-01

    the layers to act upon each other in very distinct ways. Examining the literature, we selected bipartite and tripartite network models are those...identify characteristics of multilayered networks . Bipartite and tripartite models are potentially most promising (and somewhat underutilized) in the... tripartite models are particularly well-suited to a confluence of traditional networks and software defined networks where SDN components are

  7. Energy Efficient Digital Networks

    Energy Technology Data Exchange (ETDEWEB)

    Lanzisera, Steven [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Brown, Richard [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2013-01-01

    Digital networks are the foundation of the information services, and play an expanding and indispensable role in our lives, via the Internet, email, mobile phones, etc. However, these networks consume energy, both through the direct energy use of the network interfaces and equipment that comprise the network, and in the effect they have on the operating patterns of devices connected to the network. The purpose of this research was to investigate a variety of technology and policy issues related to the energy use caused by digital networks, and to further develop several energy-efficiency technologies targeted at networks.

  8. Networking for big data

    CERN Document Server

    Yu, Shui; Misic, Jelena; Shen, Xuemin (Sherman)

    2015-01-01

    Networking for Big Data supplies an unprecedented look at cutting-edge research on the networking and communication aspects of Big Data. Starting with a comprehensive introduction to Big Data and its networking issues, it offers deep technical coverage of both theory and applications.The book is divided into four sections: introduction to Big Data, networking theory and design for Big Data, networking security for Big Data, and platforms and systems for Big Data applications. Focusing on key networking issues in Big Data, the book explains network design and implementation for Big Data. It exa

  9. Formation of multiple networks

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2013-01-01

    networks. Our model, motivated by an empirical analysis of real multi-layered network data, is a conservative extension of single-network models and emphasizes the additional level of complexity that we experience when we move from a single- to a more complete and realistic multi-network context.......While most research in Social Network Analysis has focused on single networks, the availability of complex on-line data about individuals and their mutual heterogenous connections has recently determined a renewed interest in multi-layer network analysis. To the best of our knowledge, in this paper...

  10. Network effects in railways

    DEFF Research Database (Denmark)

    Landex, Alex

    2012-01-01

    . Therefore, sections 3 and 4 describe the network effects for passengers and how they can be measured using passenger delay models. Before the concluding remarks in section 6, section 5 discusses how the operation can be improved by examining network effects in the planning process. © 2012 WIT Press....... each other everywhere in the network. First this paper describes network effects in general (section 1). In section 2 the network effects for trains and how they can be measured by scheduled waiting time is described. When the trains are affected by network effects the passengers are also affected......Railway operation is often affected by network effects as a change in one part of the network can influence other parts of the network. Network effects occur because the train runs may be quite long and since the railway system has a high degree of interdependencies as trains cannot cross/overtake...

  11. Networks in Cell Biology

    Science.gov (United States)

    Buchanan, Mark; Caldarelli, Guido; De Los Rios, Paolo; Rao, Francesco; Vendruscolo, Michele

    2010-05-01

    Introduction; 1. Network views of the cell Paolo De Los Rios and Michele Vendruscolo; 2. Transcriptional regulatory networks Sarath Chandra Janga and M. Madan Babu; 3. Transcription factors and gene regulatory networks Matteo Brilli, Elissa Calistri and Pietro Lió; 4. Experimental methods for protein interaction identification Peter Uetz, Björn Titz, Seesandra V. Rajagopala and Gerard Cagney; 5. Modeling protein interaction networks Francesco Rao; 6. Dynamics and evolution of metabolic networks Daniel Segré; 7. Hierarchical modularity in biological networks: the case of metabolic networks Erzsébet Ravasz Regan; 8. Signalling networks Gian Paolo Rossini; Appendix 1. Complex networks: from local to global properties D. Garlaschelli and G. Caldarelli; Appendix 2. Modelling the local structure of networks D. Garlaschelli and G. Caldarelli; Appendix 3. Higher-order topological properties S. Ahnert, T. Fink and G. Caldarelli; Appendix 4. Elementary mathematical concepts A. Gabrielli and G. Caldarelli; References.

  12. Network Coding Taxonomy

    OpenAIRE

    Adamson , Brian; Adjih , Cédric; Bilbao , Josu; Firoiu , Victor; Fitzek , Frank; Samah , Ghanem ,; Lochin , Emmanuel; Masucci , Antonia; Montpetit , Marie-Jose; Pedersen , Morten V.; Peralta , Goiuri; Roca , Vincent; Paresh , Saxena; Sivakumar , Senthil

    2017-01-01

    Internet Research Task Force - Working document of the Network Coding Research Group (NWCRG), draft-irtf-nwcrg-network-coding-taxonomy-05 (work in progress), https://datatracker.ietf.org/doc/draft-irtf-nwcrg-network-coding-taxonomy/; This document summarizes a recommended terminology for Network Coding concepts and constructs. It provides a comprehensive set of terms with unique names in order to avoid ambiguities in future Network Coding IRTF and IETF documents. This document is intended to ...

  13. Network of networks: Uncovering the secrets of entrepreneurs' networks

    NARCIS (Netherlands)

    Song, Y.

    2012-01-01

    This dissertation provides a novel methodology to study entrepreneurship and online social networks. We suggest that online social network data can be used as behavioural data to study entrepreneurial processes. Furthermore, our simulation model can be used as an additional approach to predict the

  14. Proliferation Networks and Financing

    International Nuclear Information System (INIS)

    Gruselle, Bruno

    2007-01-01

    The objective of this study is to propose practical solutions aimed at completing and strengthening the existing arrangement for the control of nuclear proliferation through a control of financial as well as material or immaterial flows. In a first part, the author proposes a systemic analysis of networks of suppliers and demanders. He notably evokes the Khan's network and the Iraqi acquisition network during the 1993-2001 period. He also proposes a modelling of proliferation networks (supplier networks and acquisition networks) and of their interactions. In a second part, the author examines possible means and policies aimed at neutralising proliferation networks: organisation, adaptation and improvement of intelligence tools in front of proliferation networks, and means, limitations and perspectives of network neutralisation. He also briefly addresses the possibility of military action to contain proliferation flows

  15. Morphological neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, G.X.; Sussner, P. [Univ. of Florida, Gainesville, FL (United States)

    1996-12-31

    The theory of artificial neural networks has been successfully applied to a wide variety of pattern recognition problems. In this theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the linear operation of multiplying neural values by their synaptic strengths and adding the results. Thresholding usually follows the linear operation in order to provide for nonlinearity of the network. In this paper we introduce a novel class of neural networks, called morphological neural networks, in which the operations of multiplication and addition are replaced by addition and maximum (or minimum), respectively. By taking the maximum (or minimum) of sums instead of the sum of products, morphological network computation is nonlinear before thresholding. As a consequence, the properties of morphological neural networks are drastically different than those of traditional neural network models. In this paper we consider some of these differences and provide some particular examples of morphological neural network.

  16. Computer network defense system

    Science.gov (United States)

    Urias, Vincent; Stout, William M. S.; Loverro, Caleb

    2017-08-22

    A method and apparatus for protecting virtual machines. A computer system creates a copy of a group of the virtual machines in an operating network in a deception network to form a group of cloned virtual machines in the deception network when the group of the virtual machines is accessed by an adversary. The computer system creates an emulation of components from the operating network in the deception network. The components are accessible by the group of the cloned virtual machines as if the group of the cloned virtual machines was in the operating network. The computer system moves network connections for the group of the virtual machines in the operating network used by the adversary from the group of the virtual machines in the operating network to the group of the cloned virtual machines, enabling protecting the group of the virtual machines from actions performed by the adversary.

  17. Network Transformations in Economy

    Directory of Open Access Journals (Sweden)

    Bolychev O.

    2014-09-01

    Full Text Available In the context of ever-increasing market competition, networked interactions play a special role in the economy. The network form of entrepreneurship is increasingly viewed as an effective organizational structure to create a market value embedded in innovative business solutions. The authors study the characteristics of a network as an economic category and emphasize certain similarities between Rus sian and international approaches to identifying interactions of economic systems based on the network principle. The paper focuses on the types of networks widely used in the economy. The authors analyze the transformation of business networks along two lines: from an intra- to an inter-firm network and from an inter-firm to an inter-organizational network. The possible forms of network formation are described depending on the strength of connections and the type of integration. The drivers and reasons behind process of transition from a hierarchical model of the organizational structure to a network type are identified. The authors analyze the advantages of creating inter-firm networks and discuss the features of inter-organizational networks as compares to inter-firm ones. The article summarizes the reasons for and advantages of participation in inter-rganizational networks and identifies the main barriers to the formation of inter-organizational network.

  18. Dynamic ad hoc networks

    CERN Document Server

    Rashvand, Habib

    2013-01-01

    Motivated by the exciting new application paradigm of using amalgamated technologies of the Internet and wireless, the next generation communication networks (also called 'ubiquitous', 'complex' and 'unstructured' networking) are changing the way we develop and apply our future systems and services at home and on local, national and global scales. Whatever the interconnection - a WiMAX enabled networked mobile vehicle, MEMS or nanotechnology enabled distributed sensor systems, Vehicular Ad hoc Networking (VANET) or Mobile Ad hoc Networking (MANET) - all can be classified under new networking s

  19. Social network data analytics

    CERN Document Server

    Aggarwal, Charu C

    2011-01-01

    Social network analysis applications have experienced tremendous advances within the last few years due in part to increasing trends towards users interacting with each other on the internet. Social networks are organized as graphs, and the data on social networks takes on the form of massive streams, which are mined for a variety of purposes. Social Network Data Analytics covers an important niche in the social network analytics field. This edited volume, contributed by prominent researchers in this field, presents a wide selection of topics on social network data mining such as Structural Pr

  20. Cisco networking essentials

    CERN Document Server

    McMillan, Troy

    2015-01-01

    Start a career in networking Cisco Networking Essentials, 2nd Edition provides the latest for those beginning a career in networking. This book provides the fundamentals of networking and leads you through the concepts, processes, and skills you need to master fundamental networking concepts. Thinking of taking the CCENT Cisco Certified Entry Networking Technician ICND1 Exam 100-101? This book has you covered! With coverage of important topics and objectives, each chapter outlines main points and provides clear, engaging discussion that will give you a sound understanding of core topics and c

  1. Intelligent networked teleoperation control

    CERN Document Server

    Li, Zhijun; Su, Chun-Yi

    2015-01-01

    This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

  2. Networks : Empowering Communities through Telecentre Networking

    International Development Research Centre (IDRC) Digital Library (Canada)

    The study revealed that although there are no formal telecentre networking activities in the region, those countries in which telecentres are strongest - Egypt, Syria, Lebanon and Morocco - have pulled together in loose networks for peer support. On the whole, however, telecentre programming is a lot weaker and more ...

  3. Do Policy Networks lead to Network Governing?

    DEFF Research Database (Denmark)

    Damgaard, Bodil

    This paper challenges the notion that creation of local policy networks necessarily leads to network governing. Through actor-centred case studies in the area of municipally implemented employment policy in Denmark it was found that the local governing mode is determined mainly by the municipality...

  4. Epidemic Network Failures in Optical Transport Networks

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Katsikas, Dimitrios; Fagertun, Anna Manolova

    2013-01-01

    This paper presents a failure propagation model for transport networks which are affected by epidemic failures. The network is controlled using the GMPLS protocol suite. The Susceptible Infected Disabled (SID) epidemic model is investigated and new signaling functionality of GMPLS to support...

  5. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs...... has much to offer in analyzing the policy process....

  6. Multilayer Social Networks

    DEFF Research Database (Denmark)

    Dickison, Mark; Magnani, Matteo; Rossi, Luca

    Multilayer networks, in particular multilayer social networks, where users belong to and interact on different networks at the same time, are an active research area in social network analysis, computer science, and physics. These networks have traditionally been studied within these separate...... research communities, leading to the development of several independent models and methods to deal with the same set of problems. This book unifies and consolidates existing practical and theoretical knowledge on multilayer networks including data collection and analysis, modeling, and mining of multilayer...... social network systems, the evolution of interconnected social networks, and dynamic processes such as information spreading. A single real dataset is used to illustrate the concepts presented throughout the book, demonstrating both the practical utility and the potential shortcomings of the various...

  7. Energy Sciences Network (ESnet)

    Data.gov (United States)

    Federal Laboratory Consortium — The Energy Sciences Network is the Department of Energy’s high-speed network that provides the high-bandwidth, reliable connections that link scientists at national...

  8. Wireshark network security

    CERN Document Server

    Verma, Piyush

    2015-01-01

    If you are network administrator or a security analyst with an interest in using Wireshark for security analysis, then this is the book for you. Basic familiarity with common network and application services terms and technologies is assumed.

  9. Fiber wireless networks

    Science.gov (United States)

    Nirmalathas, A.; Bakaul, M.; Lim, C.; Novak, D.; Waterhouse, R.

    2005-11-01

    Broadband wireless networks based on a number of new frequency windows at higher microwave and millimeter-wave frequencies have been actively pursued to provide ultra-high bandwidth services over a wireless networks. These networks will have a large number of antenna base-stations with high throughput. Significant reductions in antenna base-station complexity can be achieved if most of the signal routing and switching functions centralized at a central office in the network. In such a network, fiber feed networks can be effectively deployed to provide high bandwidth interconnections between multiple antenna base-stations and the central office. With wavelength division multiplexing, efficient optical fiber feed network architectures could be realised to provide interconnection to a large number of antenna base-stations. In this paper, we present an over view of our recent research into system technologies for fiber wireless networks.

  10. Temporal network epidemiology

    CERN Document Server

    Holme, Petter

    2017-01-01

    This book covers recent developments in epidemic process models and related data on temporally varying networks. It is widely recognized that contact networks are indispensable for describing, understanding, and intervening to stop the spread of infectious diseases in human and animal populations; “network epidemiology” is an umbrella term to describe this research field. More recently, contact networks have been recognized as being highly dynamic. This observation, also supported by an increasing amount of new data, has led to research on temporal networks, a rapidly growing area. Changes in network structure are often informed by epidemic (or other) dynamics, in which case they are referred to as adaptive networks. This volume gathers contributions by prominent authors working in temporal and adaptive network epidemiology, a field essential to understanding infectious diseases in real society.

  11. Determinants of Network Outcomes

    DEFF Research Database (Denmark)

    Ysa, Tamyko; Sierra, Vicenta; Esteve, Marc

    2014-01-01

    outcomes and that they enhance the level of trust. We also found that facilitative leadership has a positive impact on network management as well as on trust in the network. Our findings also show that complexity has a negative impact on trust. A key finding of our research is that managers may wield more......The literature on network management is extensive. However, it generally explores network structures, neglecting the impact of management strategies. In this article we assess the effect of management strategies on network outcomes, providing empirical evidence from 119 urban revitalization...... networks. We go beyond current work by testing a path model for the determinants of network outcomes and considering the interactions between the constructs: management strategies, trust, complexity, and facilitative leadership. Our results suggest that management strategies have a strong effect on network...

  12. Heterogeneous network architectures

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann

    2006-01-01

    and it is discussed that it is advantageous to heterogeneous networks and illustrated by a number of examples. Modeling and simulation is a well-known way of doing performance evaluation. An approach to event-driven simulation of communication networks is presented and mixed complexity modeling, which can simplify......Future networks will be heterogeneous! Due to the sheer size of networks (e.g., the Internet) upgrades cannot be instantaneous and thus heterogeneity appears. This means that instead of trying to find the olution, networks hould be designed as being heterogeneous. One of the key equirements here...... is flexibility. This thesis investigates such heterogeneous network architectures and how to make them flexible. A survey of algorithms for network design is presented, and it is described how using heuristics can increase the speed. A hierarchical, MPLS based network architecture is described...

  13. Virtualized Network Control (VNC)

    Energy Technology Data Exchange (ETDEWEB)

    Lehman, Thomas [Univ. of Southern California, Los Angeles, CA (United States); Guok, Chin [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Ghani, Nasir [Univ. of New Mexico, Albuquerque, NM (United States)

    2013-01-31

    The focus of this project was on the development of a "Network Service Plane" as an abstraction model for the control and provisioning of multi-layer networks. The primary motivation for this work were the requirements of next generation networked applications which will need to access advanced networking as a first class resource at the same level as compute and storage resources. A new class of "Intelligent Network Services" were defined in order to facilitate the integration of advanced network services into application specific workflows. This new class of network services are intended to enable real-time interaction between the application co-scheduling algorithms and the network for the purposes of workflow planning, real-time resource availability identification, scheduling, and provisioning actions.

  14. Network Memory Protocol

    National Research Council Canada - National Science Library

    Wilcox, D

    1997-01-01

    This report presents initial research into the design of a new computer system local area network transport layer protocol, designated the network memory protocol, which provides clients with direct...

  15. Class network routing

    Science.gov (United States)

    Bhanot, Gyan [Princeton, NJ; Blumrich, Matthias A [Ridgefield, CT; Chen, Dong [Croton On Hudson, NY; Coteus, Paul W [Yorktown Heights, NY; Gara, Alan G [Mount Kisco, NY; Giampapa, Mark E [Irvington, NY; Heidelberger, Philip [Cortlandt Manor, NY; Steinmacher-Burow, Burkhard D [Mount Kisco, NY; Takken, Todd E [Mount Kisco, NY; Vranas, Pavlos M [Bedford Hills, NY

    2009-09-08

    Class network routing is implemented in a network such as a computer network comprising a plurality of parallel compute processors at nodes thereof. Class network routing allows a compute processor to broadcast a message to a range (one or more) of other compute processors in the computer network, such as processors in a column or a row. Normally this type of operation requires a separate message to be sent to each processor. With class network routing pursuant to the invention, a single message is sufficient, which generally reduces the total number of messages in the network as well as the latency to do a broadcast. Class network routing is also applied to dense matrix inversion algorithms on distributed memory parallel supercomputers with hardware class function (multicast) capability. This is achieved by exploiting the fact that the communication patterns of dense matrix inversion can be served by hardware class functions, which results in faster execution times.

  16. Adaptive dynamical networks

    Science.gov (United States)

    Maslennikov, O. V.; Nekorkin, V. I.

    2017-10-01

    Dynamical networks are systems of active elements (nodes) interacting with each other through links. Examples are power grids, neural structures, coupled chemical oscillators, and communications networks, all of which are characterized by a networked structure and intrinsic dynamics of their interacting components. If the coupling structure of a dynamical network can change over time due to nodal dynamics, then such a system is called an adaptive dynamical network. The term ‘adaptive’ implies that the coupling topology can be rewired; the term ‘dynamical’ implies the presence of internal node and link dynamics. The main results of research on adaptive dynamical networks are reviewed. Key notions and definitions of the theory of complex networks are given, and major collective effects that emerge in adaptive dynamical networks are described.

  17. Innovations, status, and networks

    NARCIS (Netherlands)

    P. Wang (Pengfei)

    2016-01-01

    markdownabstractTo obtain and maintain competitive advantage, firms need to implement appropriate innovation strategies (i.e. exploration or exploitation) and acquire status in external networks. In this dissertation, I investigate how innovation strategy, status, and network structure jointly

  18. Cooperative Hurricane Network Obs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Observations from the Cooperative Hurricane Reporting Network (CHURN), a special network of stations that provided observations when tropical cyclones approached the...

  19. Local network assessment

    Science.gov (United States)

    Glen, D. V.

    1985-04-01

    Local networks, related standards activities of the Institute of Electrical and Electronics Engineers the American National Standards Institute and other elements are presented. These elements include: (1) technology choices such as topology, transmission media, and access protocols; (2) descriptions of standards for the 802 local area networks (LAN's); high speed local networks (HSLN's) and military specification local networks; and (3) intra- and internetworking using bridges and gateways with protocols Interconnection (OSI) reference model. The convergence of LAN/PBX technology is also described.

  20. Field Bus Communications Network

    International Nuclear Information System (INIS)

    Kwon, Uk Hyeon; Kim, Hyeong Seok; Kim, Dong Seong

    2004-10-01

    This book is about field bus communications network, introducing data communications network, field bus for industry and standardization of communication protocol, basic of data communication about structure, local area network, introduction of field bus for industry like utility of field bus, profibus, foundation field bus, worldFIP, device net, inter bus, control net, P-net and SERCOS, evaluation of field bus performance including computer simulation tool, and network modeling, and field bus practice.

  1. Patent Licensing Networks

    OpenAIRE

    Doh-Shin Jeon; Yassine Lefouili

    2014-01-01

    This paper investigates the patent licensing networks formed by competing firms. Assuming that licensing agreements can involve the payment of fixed fees only and that firms compete à la Cournot, we show that the complete network is always bilaterally efficient and that the monopoly network is bilaterally efficient if the patents are complementary enough. In the case of independent patents, we fully characterize the bilaterally efficient networks and find that when the cost reduction resultin...

  2. Linux Networking Cookbook

    CERN Document Server

    Schroder, Carla

    2008-01-01

    If you want a book that lays out the steps for specific Linux networking tasks, one that clearly explains the commands and configurations, this is the book for you. Linux Networking Cookbook is a soup-to-nuts collection of recipes that covers everything you need to know to perform your job as a Linux network administrator. You'll dive straight into the gnarly hands-on work of building and maintaining a computer network

  3. Cognitive Dynamic Optical Networks

    DEFF Research Database (Denmark)

    de Miguel, Ignacio; Duran, Ramon J.; Lorenzo, Ruben M.

    2013-01-01

    Cognitive networks are a promising solution for the control of heterogeneous optical networks. We review their fundamentals as well as a number of applications developed in the framework of the EU FP7 CHRON project.......Cognitive networks are a promising solution for the control of heterogeneous optical networks. We review their fundamentals as well as a number of applications developed in the framework of the EU FP7 CHRON project....

  4. PREFACE: Complex Networks: from Biology to Information Technology

    Science.gov (United States)

    Barrat, A.; Boccaletti, S.; Caldarelli, G.; Chessa, A.; Latora, V.; Motter, A. E.

    2008-06-01

    networks consists of an overview of recent studies on hierarchical networks of phase oscillators. By analysing the evolution of the synchronous dynamics, one can infer details about the underlying network topology. Thus a connection between the dynamical and topological properties of the system is established. The paper Network synchronisation: optimal and pessimal scale-free topologies by Donetti et al explores an optimisation algorithm to study the properties of optimally synchronisable unweighted networks with scale-free degree distribution. It is shown that optimisation leads to a tendency towards disassortativity while networks that are optimally 'un-synchronisable' have a highly assortative string-like structure. The paper Critical line in undirected Kauffman Boolean networks—the role of percolation by Fronczak and Fronczak demonstrates that the percolation underlying the process of damage spreading impacts the position of the critical line in random boolean networks. The critical line results from the fact that the ordered behaviour of small clusters shields the chaotic behaviour of the giant component. In Impact of the updating scheme on stationary states of networks, Radicchi et al explore an interpolation between synchronous and asynchronous updating in a one-dimensional chain of Ising spins to locate a phase transition between phases with an absorbing and a fluctuating stationary state. The properties of attractors in the yeast cell-cycle network are also shown to depend sensitively on the updating mode. As this last contribution shows, a large part of the theoretical activity in the field can be applied to the study of biological systems. The section Biological Applications brings together the following contributions: In Applying weighted network measures to microarray distance matrices, Ahnert et al present a new approach to the analysis of weighted networks, which provides a generalisation to any network measure defined on unweighted networks. The

  5. Innovation and network collaboration

    DEFF Research Database (Denmark)

    Kesting, Peter; Müller, Sabine; Jørgensen, Frances

    2011-01-01

    and their inherent shortage of resources. In this paper, we propose that human resource management (HRM) practices may provide a means by which SMEs can increase their innovation capacity through network collaboration. Following a brief presentation of the relevant literature on networks, and innovation in networks...

  6. Managing Knowledge Networks.

    Science.gov (United States)

    Contractor, Noshir S.; Monge, Peter R.

    2002-01-01

    Describes a multitheoretical, multilevel (MTML) model to study the management of knowledge networks. Considers theoretical mechanisms for emergence of knowledge networks and presents empirical findings about the emergence of knowledge networks. Concludes that it is necessary to utilize MTML models to integrate multiple social and communication…

  7. Neural Network Ensembles

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Salamon, Peter

    1990-01-01

    We propose several means for improving the performance an training of neural networks for classification. We use crossvalidation as a tool for optimizing network parameters and architecture. We show further that the remaining generalization error can be reduced by invoking ensembles of similar...... networks....

  8. Securing Personal Network Clusters

    NARCIS (Netherlands)

    Jehangir, A.; Heemstra de Groot, S.M.

    2007-01-01

    A Personal Network is a self-organizing, secure and private network of a user’s devices notwithstanding their geographic location. It aims to utilize pervasive computing to provide users with new and improved services. In this paper we propose a model for securing Personal Network clusters. Clusters

  9. Synchronization of networks

    Indian Academy of Sciences (India)

    time. Both the number of nodes and the edges connecting the nodes can vary with time. Such a time-varying topology can occur in social networks, computer networks, WWW, biological systems, spread of epidemics etc. Here, we investigate the synchronization properties of networks with time-varying structure and compare.

  10. Networks and Economic Behavior

    OpenAIRE

    Matthew O. Jackson

    2009-01-01

    Recent analyses of social networks, both empirical and theoretical, are discussed, with a focus on how social networks influence economic behavior, as well as how social networks form. Some challenges of such research are discussed as are some of the important considerations for the future.

  11. Synchronization of networks

    Indian Academy of Sciences (India)

    We study the synchronization of coupled dynamical systems on networks. The dynamics is governed by a local nonlinear oscillator for each node of the network and interactions connecting different nodes via the links of the network. We consider existence and stability conditions for both single- and multi-cluster ...

  12. Laws of Network Value

    Directory of Open Access Journals (Sweden)

    Juan M.C. Larrosa

    2016-12-01

    Full Text Available The valuation of a social network is an issue that has been addressed based on simplifying approaches. Various value laws have been stipulated, which are largely atheoretical but have been effectively used to estimate the potential economic value of social network-based firms. This review highlights the various contributions used in the recent literature on networks valuation laws.

  13. Network Profiling Using Flow

    Science.gov (United States)

    2012-08-01

    many well-known services in use today to list in this report. Protocols such as NTP, RDP, LDAP , SMB, and sqlnet may show up on the network. At some...point, verify that these services are appropriate for the network. For example, NetBIOS, LDAP , and SMB traffic should not be crossing the network

  14. OSI Network Management.

    Science.gov (United States)

    Harris, Ethan

    1990-01-01

    Management of heterogeneous networks is complicated by the persistence of proprietary management schemes. The need for integration of network management capabilities is pressing. The International Organization for Standardization is developing standards for managing networks as part of the Open Systems Interconnection (OSI) effort. OSI management…

  15. artificial neural network (ann)

    African Journals Online (AJOL)

    2004-08-18

    Aug 18, 2004 ... forecasting models and artificial intelligence techniques and have become one of the major research fields (Kher and Joshin, 2003). (a) Artificial Neural Network and Electrical Load. Prediction. Neural network analysis is an Artificial Intelligence. (AI) approach to mathematical modeling. Neural. Networks ...

  16. Networks around entrepreneurs

    DEFF Research Database (Denmark)

    Bertelsen, Rasmus Gjedssø; Ashourizadeh, Shayegheh; Jensen, Kent Wickstrøm

    2017-01-01

    Purpose: Entrepreneurs are networking with others to get advice for their businesses. The networking differs between men and women; notably, men are more often networking in the public sphere and women are more often networking in the private sphere. The aim here is to account for how such gender......Purpose: Entrepreneurs are networking with others to get advice for their businesses. The networking differs between men and women; notably, men are more often networking in the public sphere and women are more often networking in the private sphere. The aim here is to account for how...... such gendering of entrepreneurs’ networks differ between societies and cultures. Research Design: Based on survey data from the Global Entrepreneurships Monitor, a sample of 16,365 entrepreneurs is used to compare the gendering of entrepreneurs’ networks in China, and five countries largely located around...... the Persian Gulf, namely Yemen, Iran, Saudi Arabia, Qatar and United Arab Emirates. Findings: Analyses show that female entrepreneurs tend to have slightly larger private sphere networks than male entrepreneurs. The differences between male and female entrepreneurs’ networking in the public sphere...

  17. Localizing and placement of network node functions in a network

    NARCIS (Netherlands)

    Strijkers, R.J.; Meulenhoff, P.J.

    2014-01-01

    The invention enables placement and use of a network node function in a second network node instead of using the network node function in a first network node. The network node function is e.g. a server function or a router function. The second network node is typically located in or close to the

  18. Biometrics for home networks security

    KAUST Repository

    Ansari, Imran Shafique

    2009-01-01

    Hacking crimes committed to the home networks are increasing. Advanced network protection is not always possible for the home networks. In this paper we will study the ability of using biometric systems for authentication in home networks. ©2009 IEEE.

  19. Robustness of weighted networks

    Science.gov (United States)

    Bellingeri, Michele; Cassi, Davide

    2018-01-01

    Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

  20. Dominating biological networks.

    Directory of Open Access Journals (Sweden)

    Tijana Milenković

    Full Text Available Proteins are essential macromolecules of life that carry out most cellular processes. Since proteins aggregate to perform function, and since protein-protein interaction (PPI networks model these aggregations, one would expect to uncover new biology from PPI network topology. Hence, using PPI networks to predict protein function and role of protein pathways in disease has received attention. A debate remains open about whether network properties of "biologically central (BC" genes (i.e., their protein products, such as those involved in aging, cancer, infectious diseases, or signaling and drug-targeted pathways, exhibit some topological centrality compared to the rest of the proteins in the human PPI network.To help resolve this debate, we design new network-based approaches and apply them to get new insight into biological function and disease. We hypothesize that BC genes have a topologically central (TC role in the human PPI network. We propose two different concepts of topological centrality. We design a new centrality measure to capture complex wirings of proteins in the network that identifies as TC those proteins that reside in dense extended network neighborhoods. Also, we use the notion of domination and find dominating sets (DSs in the PPI network, i.e., sets of proteins such that every protein is either in the DS or is a neighbor of the DS. Clearly, a DS has a TC role, as it enables efficient communication between different network parts. We find statistically significant enrichment in BC genes of TC nodes and outperform the existing methods indicating that genes involved in key biological processes occupy topologically complex and dense regions of the network and correspond to its "spine" that connects all other network parts and can thus pass cellular signals efficiently throughout the network. To our knowledge, this is the first study that explores domination in the context of PPI networks.

  1. Logistical networking: a global storage network

    International Nuclear Information System (INIS)

    Beck, Micah; Moore, Terry

    2005-01-01

    The absence of an adequate distributed storage infrastructure for data buffering has become a significant impediment to the flow of work in the wide area, data intensive collaborations that are increasingly characteristic of leading edge research in several fields. One solution to this problem, pioneered under DOE's SciDAC program, is Logistical Networking, which provides a framework for a globally scalable, maximally interoperable storage network based on the Internet Backplane Protocol (IBP). This paper provides a brief overview of the Logistical Networking (LN) architecture, the middleware developed to exploit its value, and a few of the applications that some of research communities have made of it

  2. NASA's unique networking environment

    Science.gov (United States)

    Johnson, Marjory J.

    1988-01-01

    Networking is an infrastructure technology; it is a tool for NASA to support its space and aeronautics missions. Some of NASA's networking problems are shared by the commercial and/or military communities, and can be solved by working with these communities. However, some of NASA's networking problems are unique and will not be addressed by these other communities. Individual characteristics of NASA's space-mission networking enviroment are examined, the combination of all these characteristics that distinguish NASA's networking systems from either commercial or military systems is explained, and some research areas that are important for NASA to pursue are outlined.

  3. Wireless mesh networks

    CERN Document Server

    Held, Gilbert

    2005-01-01

    Wireless mesh networking is a new technology that has the potential to revolutionize how we access the Internet and communicate with co-workers and friends. Wireless Mesh Networks examines the concept and explores its advantages over existing technologies. This book explores existing and future applications, and examines how some of the networking protocols operate.The text offers a detailed analysis of the significant problems affecting wireless mesh networking, including network scale issues, security, and radio frequency interference, and suggests actual and potential solutions for each pro

  4. Learning conditional Gaussian networks

    DEFF Research Database (Denmark)

    Bøttcher, Susanne Gammelgaard

    This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....

  5. Manufacturing network evolution

    DEFF Research Database (Denmark)

    Yang, Cheng; Farooq, Sami; Johansen, John

    2011-01-01

    Purpose – This paper examines the effect of changes at the manufacturing plant level on other plants in the manufacturing network and also investigates the role of manufacturing plants on the evolution of a manufacturing network. Design/methodology/approach –The research questions are developed......, the complex phenomenon of a manufacturing network evolution is observed by combining the analysis of a manufacturing plant and network level. The historical trajectories of manufacturing networks that are presented in the case studies are examined in order to understand and determine the future shape...

  6. Next Generation Social Networks

    DEFF Research Database (Denmark)

    Sørensen, Lene Tolstrup; Skouby, Knud Erik

    2008-01-01

    When it comes to discussing the future of electronic communication, social networking is the buzzword. The Internet has become a platform where new social networks emerge and the Internet it itself support the more traditional computer supported communication. The way users build and verifies...... different online networks for communities of people who share interests or individuals who presents themselves through user produced content is what makes up the social networking of today. The purpose of this paper is to discuss perceived user requirements to the next generation social networks. The paper...

  7. Microsoft Windows networking essentials

    CERN Document Server

    Gibson, Darril

    2011-01-01

    The core concepts and technologies of Windows networking Networking can be a complex topic, especially for those new to the field of IT. This focused, full-color book takes a unique approach to teaching Windows networking to beginners by stripping down a network to its bare basics, thereby making each topic clear and easy to understand. Focusing on the new Microsoft Technology Associate (MTA) program, this book pares down to just the essentials, showing beginners how to gain a solid foundation for understanding networking concepts upon which more advanced topics and technologies can be built.

  8. Network Characterization Service (NCS)

    Energy Technology Data Exchange (ETDEWEB)

    Jin, Guojun [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Yang, George [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Crowley, Brian [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Agarwal, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2001-06-06

    Distributed applications require information to effectively utilize the network. Some of the information they require is the current and maximum bandwidth, current and minimum latency, bottlenecks, burst frequency, and congestion extent. This type of information allows applications to determine parameters like optimal TCP buffer size. In this paper, we present a cooperative information-gathering tool called the network characterization service (NCS). NCS runs in user space and is used to acquire network information. Its protocol is designed for scalable and distributed deployment, similar to DNS. Its algorithms provide efficient, speedy and accurate detection of bottlenecks, especially dynamic bottlenecks. On current and future networks, dynamic bottlenecks do and will affect network performance dramatically.

  9. Cisco Networking Essentials

    CERN Document Server

    McMillan, Troy

    2011-01-01

    An engaging approach for anyone beginning a career in networking As the world leader of networking products and services, Cisco products are constantly growing in demand. Yet, few books are aimed at those who are beginning a career in IT--until now. Cisco Networking Essentials provides a solid foundation on the Cisco networking products and services with thorough coverage of fundamental networking concepts. Author Troy McMillan applies his years of classroom instruction to effectively present high-level topics in easy-to-understand terms for beginners. With this indispensable full-color resour

  10. Computer-communication networks

    CERN Document Server

    Meditch, James S

    1983-01-01

    Computer- Communication Networks presents a collection of articles the focus of which is on the field of modeling, analysis, design, and performance optimization. It discusses the problem of modeling the performance of local area networks under file transfer. It addresses the design of multi-hop, mobile-user radio networks. Some of the topics covered in the book are the distributed packet switching queuing network design, some investigations on communication switching techniques in computer networks and the minimum hop flow assignment and routing subject to an average message delay constraint

  11. Managing Innovation Networks

    DEFF Research Database (Denmark)

    Awate, Snehal Suyash; Møller Larsen, Marcus; Mudambi, Ram

    In this article, we treat innovation as a multidimensional construct spanning people, technologies, and geographies. We study how these dimensions interact and impact firms' inventor networks and the ultimate innovation performance. We identify five distinct planes in which inventor networks reside...... of the costs and benefits of being centrally located on multiplex network versus having an equal distribution of ties between the different network layers. Using patent data on the global wind power industry, we find evidence suggesting that being centrally positioned on a multiplex network with an equal...

  12. Network topology analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Kalb, Jeffrey L.; Lee, David S.

    2008-01-01

    Emerging high-bandwidth, low-latency network technology has made network-based architectures both feasible and potentially desirable for use in satellite payload architectures. The selection of network topology is a critical component when developing these multi-node or multi-point architectures. This study examines network topologies and their effect on overall network performance. Numerous topologies were reviewed against a number of performance, reliability, and cost metrics. This document identifies a handful of good network topologies for satellite applications and the metrics used to justify them as such. Since often multiple topologies will meet the requirements of the satellite payload architecture under development, the choice of network topology is not easy, and in the end the choice of topology is influenced by both the design characteristics and requirements of the overall system and the experience of the developer.

  13. Liner Service Network Design

    DEFF Research Database (Denmark)

    Brouer, Berit Dangaard

    with leased containers. Computational results are reported for seven instances based on real-life shipping networks. Solving the relaxed linear path flow model with a column generation algorithm outperforms solving the relaxed linear arc flow model with the CPLEX barrier solver even for very small instances...... a predefined subset of services, while maintaining a full view of the cargo flows in the network. This could prove a valuable decisions support tool for planners when the network is incrementally adjusted to new market situations and to evaluate the consequence of strategic decisions. The thesis contributes......This thesis concerns design of liner shipping networks using operations research to optimize liner shipping networks at the strategic, tactical and operational level. Liner shipping networks are often compared to public transit networks as they consist of a set of scheduled sailings connecting...

  14. Attachment and social networks.

    Science.gov (United States)

    Gillath, Omri; C Karantzas, Gery; Lee, Juwon

    2018-02-21

    The current review covers two lines of research linking attachment and social networks. One focuses on attachment networks (the people who fulfill one's attachment needs), examining composition and age-related differences pertaining to these networks. The other line integrates attachment with social network analysis to investigate how individual differences in adult attachment are associated with the management and characteristics (e.g., density, multiplexity, and centrality) of people's social networks. We show that most people's attachment networks are small and hierarchical, with one figure being the primary attachment figure (often a mother or romantic partner, depending on age). Furthermore, attachment style predicts network characteristics and management, such that insecurity is associated with less closeness, multiplexity, centrality, and poorer management (less maintenance, more dissolution). Copyright © 2018 Elsevier Ltd. All rights reserved.

  15. Fulcrum Network Codes

    DEFF Research Database (Denmark)

    2015-01-01

    Fulcrum network codes, which are a network coding framework, achieve three objectives: (i) to reduce the overhead per coded packet to almost 1 bit per source packet; (ii) to operate the network using only low field size operations at intermediate nodes, dramatically reducing complexity...... in the network; and (iii) to deliver an end-to-end performance that is close to that of a high field size network coding system for high-end receivers while simultaneously catering to low-end ones that can only decode in a lower field size. Sources may encode using a high field size expansion to increase...... the number of dimensions seen by the network using a linear mapping. Receivers can tradeoff computational effort with network delay, decoding in the high field size, the low field size, or a combination thereof....

  16. Internet protocol network mapper

    Science.gov (United States)

    Youd, David W.; Colon III, Domingo R.; Seidl, Edward T.

    2016-02-23

    A network mapper for performing tasks on targets is provided. The mapper generates a map of a network that specifies the overall configuration of the network. The mapper inputs a procedure that defines how the network is to be mapped. The procedure specifies what, when, and in what order the tasks are to be performed. Each task specifies processing that is to be performed for a target to produce results. The procedure may also specify input parameters for a task. The mapper inputs initial targets that specify a range of network addresses to be mapped. The mapper maps the network by, for each target, executing the procedure to perform the tasks on the target. The results of the tasks represent the mapping of the network defined by the initial targets.

  17. Networks in ATLAS

    CERN Document Server

    Mc Kee, Shawn Patrick; The ATLAS collaboration

    2016-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  18. Networks in ATLAS

    CERN Document Server

    AUTHOR|(INSPIRE)INSPIRE-00260714; The ATLAS collaboration

    2017-01-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks....

  19. Cognitive Dynamic Optical Networks

    DEFF Research Database (Denmark)

    de Miguel, Ignacio; Duran, Ramon J.; Jimenez, Tamara

    2013-01-01

    The use of cognition is a promising element for the control of heterogeneous optical networks. Not only are cognitive networks able to sense current network conditions and act according to them, but they also take into account the knowledge acquired through past experiences; that is, they include...... learning with the aim of improving performance. In this paper, we review the fundamentals of cognitive networks and focus on their application to the optical networking area. In particular, a number of cognitive network architectures proposed so far, as well as their associated supporting technologies......, are reviewed. Moreover, several applications, mainly developed in the framework of the EU FP7 Cognitive Heterogeneous Reconfigurable Optical Network (CHRON) project, are also described....

  20. Management of surgical waiting lists through a Possibilistic Linear Multiobjective Programming problem

    OpenAIRE

    Pérez Gladish, Blanca María; Arenas Parra, María del Mar; Bilbao Terol, Amelia María; Rodríguez Uria, María Victoria

    2005-01-01

    This study attempts to apply a management science technique to improve the efficiency of Hospital Administration. We aim to design the performance of the surgical services at a Public Hospital that allows the Decision-Maker to plan surgical scheduling over one year in order to reduce waiting lists. Real decision problems usually involve several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems ...

  1. A robust fuzzy possibilistic AHP approach for partner selection in international strategic alliance

    OpenAIRE

    Vahid Reza Salamat; Alireza Aliahmadi; Mir Saman Pishvaee; Khalid Hafeez

    2018-01-01

    The international strategic alliance is an inevitable solution for making competitive advantage and reducing the risk in today’s business environment. Partner selection is an important part in success of partnerships, and meanwhile it is a complicated decision because of various dimensions of the problem and inherent conflicts of stockholders. The purpose of this paper is to provide a practical approach to the problem of partner selection in international strategic alliances, which fulfills t...

  2. Method of transient identification based on a possibilistic approach, optimized by genetic algorithm

    International Nuclear Information System (INIS)

    Almeida, Jose Carlos Soares de

    2001-02-01

    This work develops a method for transient identification based on a possible approach, optimized by Genetic Algorithm to optimize the number of the centroids of the classes that represent the transients. The basic idea of the proposed method is to optimize the partition of the search space, generating subsets in the classes within a partition, defined as subclasses, whose centroids are able to distinguish the classes with the maximum correct classifications. The interpretation of the subclasses as fuzzy sets and the possible approach provided a heuristic to establish influence zones of the centroids, allowing to achieve the 'don't know' answer for unknown transients, that is, outside the training set. (author)

  3. A Framework for the Statistical Analysis of Probability of Mission Success Based on Bayesian Theory

    Science.gov (United States)

    2014-06-01

    regression, and two non-probabilistic methods, fuzzy logic and neural networks, are discussed and compared below to determine which gives the best...2 2.3 Fuzzy Logic ...accurate measure than possibilistic methods, such as fuzzy logic discussed below [5]. Bayesian inference easily accounts for subjectivity and

  4. Cloud networking understanding cloud-based data center networks

    CERN Document Server

    Lee, Gary

    2014-01-01

    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

  5. Network planning under uncertainties

    Science.gov (United States)

    Ho, Kwok Shing; Cheung, Kwok Wai

    2008-11-01

    One of the main focuses for network planning is on the optimization of network resources required to build a network under certain traffic demand projection. Traditionally, the inputs to this type of network planning problems are treated as deterministic. In reality, the varying traffic requirements and fluctuations in network resources can cause uncertainties in the decision models. The failure to include the uncertainties in the network design process can severely affect the feasibility and economics of the network. Therefore, it is essential to find a solution that can be insensitive to the uncertain conditions during the network planning process. As early as in the 1960's, a network planning problem with varying traffic requirements over time had been studied. Up to now, this kind of network planning problems is still being active researched, especially for the VPN network design. Another kind of network planning problems under uncertainties that has been studied actively in the past decade addresses the fluctuations in network resources. One such hotly pursued research topic is survivable network planning. It considers the design of a network under uncertainties brought by the fluctuations in topology to meet the requirement that the network remains intact up to a certain number of faults occurring anywhere in the network. Recently, the authors proposed a new planning methodology called Generalized Survivable Network that tackles the network design problem under both varying traffic requirements and fluctuations of topology. Although all the above network planning problems handle various kinds of uncertainties, it is hard to find a generic framework under more general uncertainty conditions that allows a more systematic way to solve the problems. With a unified framework, the seemingly diverse models and algorithms can be intimately related and possibly more insights and improvements can be brought out for solving the problem. This motivates us to seek a

  6. Adverse Outcome Pathway Networks II: Network Analytics.

    Science.gov (United States)

    Villeneuve, Daniel L; Angrish, Michelle M; Fortin, Marie C; Katsiadaki, Ioanna; Leonard, Marc; Margiotta-Casaluci, Luigi; Munn, Sharon; O'Brien, Jason M; Pollesch, Nathan L; Smith, L Cody; Zhang, Xiaowei; Knapen, Dries

    2018-02-28

    Toxicological responses to stressors are more complex than the simple one biological perturbation to one adverse outcome model portrayed by individual adverse outcome pathways (AOPs). Consequently, the AOP framework was designed to facilitate de facto development of AOP networks that can aid understanding and prediction of pleiotropic and interactive effects more common to environmentally realistic, complex exposure scenarios. The present paper introduces nascent concepts related to the qualitative analysis of AOP networks. First, graph theory-based approaches for identifying important topological features are illustrated using two example AOP networks derived from existing AOP descriptions. Second, considerations for identifying the most significant path(s) through an AOP network from either a biological or risk assessment perspective are described. Finally, approaches for identifying interactions among AOPs that may result in additive, synergistic, or antagonistic responses, or previously undefined emergent patterns of response, are introduced. Along with a companion article (Knapen et al. part I), these concepts set the stage for development of tools and case studies that will facilitate more rigorous analysis of AOP networks, and the utility of AOP network-based predictions, for use in research and regulatory decision-making. Collectively, this work addresses one of the major themes identified through a SETAC Horizon Scanning effort focused on advancing the AOP framework. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  7. Serial Network Flow Monitor

    Science.gov (United States)

    Robinson, Julie A.; Tate-Brown, Judy M.

    2009-01-01

    Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

  8. Local dependency in networks

    Directory of Open Access Journals (Sweden)

    Kudĕlka Miloš

    2015-06-01

    Full Text Available Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network’s nodes from the structure in local surroundings of individual nodes. For the tasks we deal with in this article, the key technical parameter is locality. Since only the surroundings of the examined nodes are used in computations, there is no need to analyze the entire network. This allows the application of our approach in the area of large-scale networks. We present several experiments using small networks as well as large-scale artificial and real world networks. The results of the experiments show high effectiveness due to the locality of our approach and also high quality node ranking comparable to PageRank.

  9. A network security monitor

    Energy Technology Data Exchange (ETDEWEB)

    Heberlein, L.T.; Dias, G.V.; Levitt, K.N.; Mukherjee, B.; Wood, J.; Wolber, D. (California Univ., Davis, CA (USA). Dept. of Electrical Engineering and Computer Science)

    1989-11-01

    The study of security in computer networks is a rapidly growing area of interest because of the proliferation of networks and the paucity of security measures in most current networks. Since most networks consist of a collection of inter-connected local area networks (LANs), this paper concentrates on the security-related issues in a single broadcast LAN such as Ethernet. Specifically, we formalize various possible network attacks and outline methods of detecting them. Our basic strategy is to develop profiles of usage of network resources and then compare current usage patterns with the historical profile to determine possible security violations. Thus, our work is similar to the host-based intrusion-detection systems such as SRI's IDES. Different from such systems, however, is our use of a hierarchical model to refine the focus of the intrusion-detection mechanism. We also report on the development of our experimental LAN monitor currently under implementation. Several network attacks have been simulated and results on how the monitor has been able to detect these attacks are also analyzed. Initial results demonstrate that many network attacks are detectable with our monitor, although it can surely be defeated. Current work is focusing on the integration of network monitoring with host-based techniques. 20 refs., 2 figs.

  10. Multilayer Brain Networks

    Science.gov (United States)

    Vaiana, Michael; Muldoon, Sarah Feldt

    2018-01-01

    The field of neuroscience is facing an unprecedented expanse in the volume and diversity of available data. Traditionally, network models have provided key insights into the structure and function of the brain. With the advent of big data in neuroscience, both more sophisticated models capable of characterizing the increasing complexity of the data and novel methods of quantitative analysis are needed. Recently, multilayer networks, a mathematical extension of traditional networks, have gained increasing popularity in neuroscience due to their ability to capture the full information of multi-model, multi-scale, spatiotemporal data sets. Here, we review multilayer networks and their applications in neuroscience, showing how incorporating the multilayer framework into network neuroscience analysis has uncovered previously hidden features of brain networks. We specifically highlight the use of multilayer networks to model disease, structure-function relationships, network evolution, and link multi-scale data. Finally, we close with a discussion of promising new directions of multilayer network neuroscience research and propose a modified definition of multilayer networks designed to unite and clarify the use of the multilayer formalism in describing real-world systems.

  11. Energy Efficient Wireless Sensor Network Modelling Based on Complex Networks

    OpenAIRE

    Xiao, Lin; Wu, Fahui; Yang, Dingcheng; Zhang, Tiankui; Zhu, Xiaoya

    2016-01-01

    The power consumption and energy efficiency of wireless sensor network are the significant problems in Internet of Things network. In this paper, we consider the network topology optimization based on complex network theory to solve the energy efficiency problem of WSN. We propose the energy efficient model of WSN according to the basic principle of small world from complex networks. Small world network has clustering features that are similar to that of the rules of the network but also has ...

  12. Software Defined Networking: an emerging paradigm to computer networking

    OpenAIRE

    Oladunjoye, Olanrewaju

    2017-01-01

    Software Defined Networking (SDN) is an emerging paradigm in networking technology that enables innovation on how network systems are managed and designed. SDN plays a huge role in the effort to make computer networks programmable. This thesis discusses the history and efforts to programmable and active networks, the early practicesm towards separating the control plane and data plane. Highlighting the architectural concepts in networking that software defined networks emanated as well...

  13. Recurrence of random walks with long-range steps generated by fractional Laplacian matrices on regular networks and simple cubic lattices

    Science.gov (United States)

    Michelitsch, T. M.; Collet, B. A.; Riascos, A. P.; Nowakowski, A. F.; Nicolleau, F. C. G. A.

    2017-12-01

    We analyze a Markovian random walk strategy on undirected regular networks involving power matrix functions of the type L\\frac{α{2}} where L indicates a ‘simple’ Laplacian matrix. We refer to such walks as ‘fractional random walks’ with admissible interval 0random walk. From these analytical results we establish a generalization of Polya’s recurrence theorem for fractional random walks on d-dimensional infinite lattices: The fractional random walk is transient for dimensions d > α (recurrent for d≤slantα ) of the lattice. As a consequence, for 0random walk is transient for all lattice dimensions d=1, 2, .. and in the range 1≤slantα walk is transient only for lattice dimensions d≥slant 3 . The generalization of Polya’s recurrence theorem remains valid for the class of random walks with Lévy flight asymptotics for long-range steps. We also analyze the mean first passage probabilities, mean residence times, mean first passage times and global mean first passage times (Kemeny constant) for the fractional random walk. For an infinite 1D lattice (infinite ring) we obtain for the transient regime 0random walk is generated by the non-diagonality of the fractional Laplacian matrix with Lévy-type heavy tailed inverse power law decay for the probability of long-range moves. This non-local and asymptotic behavior of the fractional random walk introduces small-world properties with the emergence of Lévy flights on large (infinite) lattices.

  14. Shifting Niches for Community Structure Detection

    DEFF Research Database (Denmark)

    Grappiolo, Corrado; Togelius, Julian; Yannakakis, Georgios N.

    2013-01-01

    We present a new evolutionary algorithm for com- munity structure detection in both undirected and unweighted (sparse) graphs and fully connected weighted digraphs (complete networks). Previous investigations have found that, although evolutionary computation can identify community structure...

  15. NASA Communications Augmentation network

    Science.gov (United States)

    Omidyar, Guy C.; Butler, Thomas E.; Laios, Straton C.

    1990-09-01

    The NASA Communications (Nascom) Division of the Mission Operations and Data Systems Directorate (MO&DSD) is to undertake a major initiative to develop the Nascom Augmentation (NAUG) network to achieve its long-range service objectives for operational data transport to support the Space Station Freedom Program, the Earth Observing System (EOS), and other projects. The NAUG is the Nascom ground communications network being developed to accommodate the operational traffic of the mid-1990s and beyond. The NAUG network development will be based on the Open Systems Interconnection Reference Model (OSI-RM). This paper describes the NAUG network architecture, subsystems, topology, and services; addresses issues of internetworking the Nascom network with other elements of the Space Station Information System (SSIS); discusses the operations environment. This paper also notes the areas of related research and presents the current conception of how the network will provide broadband services in 1998.

  16. Bridges in complex networks.

    Science.gov (United States)

    Wu, Ang-Kun; Tian, Liang; Liu, Yang-Yu

    2018-01-01

    A bridge in a graph is an edge whose removal disconnects the graph and increases the number of connected components. We calculate the fraction of bridges in a wide range of real-world networks and their randomized counterparts. We find that real networks typically have more bridges than their completely randomized counterparts, but they have a fraction of bridges that is very similar to their degree-preserving randomizations. We define an edge centrality measure, called bridgeness, to quantify the importance of a bridge in damaging a network. We find that certain real networks have a very large average and variance of bridgeness compared to their degree-preserving randomizations and other real networks. Finally, we offer an analytical framework to calculate the bridge fraction and the average and variance of bridgeness for uncorrelated random networks with arbitrary degree distributions.

  17. Professional social networking.

    Science.gov (United States)

    Rowley, Robert D

    2014-12-01

    We review the current state of social communication between healthcare professionals, the role of consumer social networking, and some emerging technologies to address the gaps. In particular, the review covers (1) the current state of loose social networking for continuing medical education (CME) and other broadcast information dissemination; (2) social networking for business promotion; (3) social networking for peer collaboration, including simple communication as well as more robust data-centered collaboration around patient care; and (4) engaging patients on social platforms, including integrating consumer-originated data into the mix of healthcare data. We will see how, as the nature of healthcare delivery moves from the institution-centric way of tradition to a more social and networked ambulatory pattern that we see emerging today, the nature of health IT has also moved from enterprise-centric systems to more socially networked, cloud-based options.

  18. Social cognitive radio networks

    CERN Document Server

    Chen, Xu

    2015-01-01

    This brief presents research results on social cognitive radio networks, a transformational and innovative networking paradigm that promotes the nexus between social interactions and cognitive radio networks. Along with a review of the research literature, the text examines the key motivation and challenges of social cognitive radio network design. Three socially inspired distributed spectrum sharing mechanisms are introduced: adaptive channel recommendation mechanism, imitation-based social spectrum sharing mechanism, and evolutionarily stable spectrum access mechanism. The brief concludes with a discussion of future research directions which ascertains that exploiting social interactions for distributed spectrum sharing will advance the state-of-the-art of cognitive radio network design, spur a new line of thinking for future wireless networks, and enable novel wireless service and applications.

  19. NASA Communications Augmentation network

    Science.gov (United States)

    Omidyar, Guy C.; Butler, Thomas E.; Laios, Straton C.

    1990-01-01

    The NASA Communications (Nascom) Division of the Mission Operations and Data Systems Directorate (MO&DSD) is to undertake a major initiative to develop the Nascom Augmentation (NAUG) network to achieve its long-range service objectives for operational data transport to support the Space Station Freedom Program, the Earth Observing System (EOS), and other projects. The NAUG is the Nascom ground communications network being developed to accommodate the operational traffic of the mid-1990s and beyond. The NAUG network development will be based on the Open Systems Interconnection Reference Model (OSI-RM). This paper describes the NAUG network architecture, subsystems, topology, and services; addresses issues of internetworking the Nascom network with other elements of the Space Station Information System (SSIS); discusses the operations environment. This paper also notes the areas of related research and presents the current conception of how the network will provide broadband services in 1998.

  20. Macroecology of pollination networks

    DEFF Research Database (Denmark)

    Nielsen, Kristian Trøjelsgaard; Olesen, Jens Mogens

    2013-01-01

    towards the tropics, and that network topology would be affected by current climate. Location Global. Methods Each network was organized as a presence/absence matrix, consisting of P plant species, A pollinator species and their links. From these matrices, network parameters were estimated. Additionally...... peaked at mid-latitude whereas modularity decreased linearly. Both patterns are suggestive of a more specialized interaction structure towards the tropics. In particular, mean annual precipitation appeared influential on network topology as both nestedness and modularity varied significantly. Importantly......Aim Interacting communities of species are organized into complex networks, and network analysis is reckoned to be a strong tool for describing their architecture. Many species assemblies show strong macroecological patterns, e.g. increasing species richness with decreasing latitude, but whether...

  1. Bio-inspired networking

    CERN Document Server

    Câmara, Daniel

    2015-01-01

    Bio-inspired techniques are based on principles, or models, of biological systems. In general, natural systems present remarkable capabilities of resilience and adaptability. In this book, we explore how bio-inspired methods can solve different problems linked to computer networks. Future networks are expected to be autonomous, scalable and adaptive. During millions of years of evolution, nature has developed a number of different systems that present these and other characteristics required for the next generation networks. Indeed, a series of bio-inspired methods have been successfully used to solve the most diverse problems linked to computer networks. This book presents some of these techniques from a theoretical and practical point of view. Discusses the key concepts of bio-inspired networking to aid you in finding efficient networking solutions Delivers examples of techniques both in theoretical concepts and practical applications Helps you apply nature's dynamic resource and task management to your co...

  2. Managing Interorganizational Networks

    DEFF Research Database (Denmark)

    Gustafsson, Jeppe

    bold enough to predict that networks will become the dominant organisation form in future. Several authors maintain that the shift from traditional hierarchical structures to networks involves dramatic changes for managers and employees (Champy 2002, Rohlin 1994, Kanter 2002). This article seeks...... to isolate some of the forthcoming changes and outlines a map for network management. We will try to avoid summarising the increasingly extensive literature about organisations which are characterised by networks and restrict our focus to management in inter-organisational networks. Inter......Management literature’s many descriptions of the current and future challenges and new trends within organisation and management forms depict a motley and kaleidoscopic picture of the future. However, one idea reoccurs throughout most of the literature – the organisational network. Some are even...

  3. Software Defined Networking

    DEFF Research Database (Denmark)

    Caba, Cosmin Marius

    resources are limited. Hence, to counteract this trend, current QoS mechanisms must become simpler to deploy and operate, in order to motivate NSPs to employ QoS techniques instead of overprovisioning. Software Defined Networking (SDN) represents a paradigm shift in the way telecommunication and data...... networks are designed and managed. This thesis argues that SDN can greatly simplify QoS provisioning in communication networks, and even improve QoS in various ways. To this end, the impact of SDN on QoS is assessed from both a network performance perspective (e.g. bandwidth, delay), and also from a more...... generic perspective (e.g. service provisioning speed, resources availability). As a result, new mechanisms for providing QoS are proposed, solutions for SDN-specific QoS challenges are designed and tested, and new network management concepts are prototyped, all aiming to improve QoS for network services...

  4. Green heterogeneous wireless networks

    CERN Document Server

    Ismail, Muhammad; Nee, Hans-Peter; Qaraqe, Khalid A; Serpedin, Erchin

    2016-01-01

    This book focuses on the emerging research topic "green (energy efficient) wireless networks" which has drawn huge attention recently from both academia and industry. This topic is highly motivated due to important environmental, financial, and quality-of-experience (QoE) considerations. Specifically, the high energy consumption of the wireless networks manifests in approximately 2% of all CO2 emissions worldwide. This book presents the authors’ visions and solutions for deployment of energy efficient (green) heterogeneous wireless communication networks. The book consists of three major parts. The first part provides an introduction to the "green networks" concept, the second part targets the green multi-homing resource allocation problem, and the third chapter presents a novel deployment of device-to-device (D2D) communications and its successful integration in Heterogeneous Networks (HetNets). The book is novel in that it specifically targets green networking in a heterogeneous wireless medium, which re...

  5. The Bastion Network Project

    OpenAIRE

    Fulp, J.D.

    2004-01-01

    Workshop on Education in Computer Security (WECS) 6 The Naval Postgraduate School’s Center for Information Systems Security Studies and Research (CISR) has developed a small, but realistic network lab—the Bastion Network—that is dedicated to educating students in the myriad elements involved in the secure operation of a computer network. This paper describes the rationale for this network lab, and offers an overview of a simple framework that could accommodate educational netwo...

  6. Network Atached Storage

    OpenAIRE

    Griffee, Bill

    2013-01-01

    Digital distribution of media has grown increasingly important as an additional requirement is to have this media available to multiple users. Traditionally, servers have filled this role in companies by providing storage that can be accessed by other devices on a network, typically through file sharing or serving or via a storage area network, while providing other services as well. Network attached storage (NAS) systems expand upon traditional servers in that they are built specifically wit...

  7. Random acyclic networks

    OpenAIRE

    Karrer, Brian; Newman, M. E. J.

    2009-01-01

    Directed acyclic graphs are a fundamental class of networks that includes citation networks, food webs, and family trees, among others. Here we define a random graph model for directed acyclic graphs and give solutions for a number of the model's properties, including connection probabilities and component sizes, as well as a fast algorithm for simulating the model on a computer. We compare the predictions of the model to a real-world network of citations between physics papers and find surpr...

  8. GRANCONF: GRAphical Network CONFiguratione

    OpenAIRE

    Olstad, Thomas Sørgård; Torgersen, Magnus Omland

    2016-01-01

    GRANCONF is a framework for mass configuration of network equipment and related systems in a lab environment. The framework is built for complex networking scenarios with equipment from different vendors. The framework has modular support for configuring and resetting devices from various vendors and may be extended with additional functionality in modules. This project is part of automating practical assessments and labs for use in the networking courses at NTNU in Gjøvik. Our contributi...

  9. Personal Network (PN) Applications

    DEFF Research Database (Denmark)

    Prasad, Ramjee; Skouby, K.

    2005-01-01

    The applications of PN will be realised under many scenarios where users can have access to their personal network all the time. This network will enable the user to share critical information, play games, control their home remotely, etc. All this will be achieved with seamless interworking...... and handover between networks and user devices. This paper presents an array of use case scenarios that validates the ubiquitous usage of PN....

  10. Personal network (PN) applications

    DEFF Research Database (Denmark)

    Prasad, R.; Skouby, Knud Erik

    2005-01-01

    The applications of PN will be realised under many scenarios where users can have access to their personal network all the time. This network will enable the user to share critical information, play games, control their home remotely, etc. All this will be achieved with seamless interworking...... and handover between networks and user devices. This paper presents an array of use case scenarios that validates the ubiquitous usage of PN....

  11. Affinity driven social networks

    Science.gov (United States)

    Ruyú, B.; Kuperman, M. N.

    2007-04-01

    In this work we present a model for evolving networks, where the driven force is related to the social affinity between individuals of a population. In the model, a set of individuals initially arranged on a regular ordered network and thus linked with their closest neighbors are allowed to rearrange their connections according to a dynamics closely related to that of the stable marriage problem. We show that the behavior of some topological properties of the resulting networks follows a non trivial pattern.

  12. Network operating system

    Science.gov (United States)

    1985-01-01

    Long-term and short-term objectives for the development of a network operating system for the Space Station are stated. The short-term objective is to develop a prototype network operating system for a 100 megabit/second fiber optic data bus. The long-term objective is to establish guidelines for writing a detailed specification for a Space Station network operating system. Major milestones are noted. Information is given in outline form.

  13. Network Science Experimentation Vision

    Science.gov (United States)

    2015-09-01

    stages of intrusion, such as phishing, SQL injection , Botnets, network scanning, propagation, etc.) employing a variety of countermeasures, including...shim layers, network topology, and the load that is placed on the network • ELICIT capability to inject data at various nodes at various times...capability to inject data at various nodes at various times • ELICIT capability to vary the quality and quality of this data • ELICIT agent stand-ins

  14. Handbook of networking & connectivity

    CERN Document Server

    McClain, Gary R

    1994-01-01

    Handbook of Networking & Connectivity focuses on connectivity standards in use, including hardware and software options. The book serves as a guide for solving specific problems that arise in designing and maintaining organizational networks.The selection first tackles open systems interconnection, guide to digital communications, and implementing TCP/IP in an SNA environment. Discussions focus on elimination of the SNA backbone, routing SNA over internets, connectionless versus connection-oriented networks, internet concepts, application program interfaces, basic principles of layering, proto

  15. Networks in ATLAS

    Science.gov (United States)

    McKee, Shawn; ATLAS Collaboration

    2017-10-01

    Networks have played a critical role in high-energy physics (HEP), enabling us to access and effectively utilize globally distributed resources to meet the needs of our physicists. Because of their importance in enabling our grid computing infrastructure many physicists have taken leading roles in research and education (R&E) networking, participating in, and even convening, network related meetings and research programs with the broader networking community worldwide. This has led to HEP benefiting from excellent global networking capabilities for little to no direct cost. However, as other science domains ramp-up their need for similar networking it becomes less clear that this situation will continue unchanged. What this means for ATLAS in particular needs to be understood. ATLAS has evolved its computing model since the LHC started based upon its experience with using globally distributed resources. The most significant theme of those changes has been increased reliance upon, and use of, its networks. We will report on a number of networking initiatives in ATLAS including participation in the global perfSONAR network monitoring and measuring efforts of WLCG and OSG, the collaboration with the LHCOPN/LHCONE effort, the integration of network awareness into PanDA, the use of the evolving ATLAS analytics framework to better understand our networks and the changes in our DDM system to allow remote access to data. We will also discuss new efforts underway that are exploring the inclusion and use of software defined networks (SDN) and how ATLAS might benefit from: • Orchestration and optimization of distributed data access and data movement. • Better control of workflows, end to end. • Enabling prioritization of time-critical vs normal tasks • Improvements in the efficiency of resource usage

  16. Security for multihop wireless networks

    CERN Document Server

    Khan, Shafiullah

    2014-01-01

    Security for Multihop Wireless Networks provides broad coverage of the security issues facing multihop wireless networks. Presenting the work of a different group of expert contributors in each chapter, it explores security in mobile ad hoc networks, wireless sensor networks, wireless mesh networks, and personal area networks.Detailing technologies and processes that can help you secure your wireless networks, the book covers cryptographic coprocessors, encryption, authentication, key management, attacks and countermeasures, secure routing, secure medium access control, intrusion detection, ep

  17. Chaotic diagonal recurrent neural network

    International Nuclear Information System (INIS)

    Wang Xing-Yuan; Zhang Yi

    2012-01-01

    We propose a novel neural network based on a diagonal recurrent neural network and chaos, and its structure and learning algorithm are designed. The multilayer feedforward neural network, diagonal recurrent neural network, and chaotic diagonal recurrent neural network are used to approach the cubic symmetry map. The simulation results show that the approximation capability of the chaotic diagonal recurrent neural network is better than the other two neural networks. (interdisciplinary physics and related areas of science and technology)

  18. Social network visualization in epidemiology

    OpenAIRE

    James H. Fowler; Nicholas A. Christakis

    2009-01-01

    Epidemiological investigations and interventions are increasingly focusing on social networks. Two aspects of social networks are relevant in this regard: the structure of networks and the function of networks. A better understanding of the processes that determine how networks form and how they operate with respect to the spread of behavior holds promise for improving public health. Visualizing social networks is a key to both research and interventions. Network images supplement statistical...

  19. Friendly network robotics; Friendly network robotics

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-03-01

    This paper summarizes the research results on the friendly network robotics in fiscal 1996. This research assumes an android robot as an ultimate robot and the future robot system utilizing computer network technology. The robot aiming at human daily work activities in factories or under extreme environments is required to work under usual human work environments. The human robot with similar size, shape and functions to human being is desirable. Such robot having a head with two eyes, two ears and mouth can hold a conversation with human being, can walk with two legs by autonomous adaptive control, and has a behavior intelligence. Remote operation of such robot is also possible through high-speed computer network. As a key technology to use this robot under coexistence with human being, establishment of human coexistent robotics was studied. As network based robotics, use of robots connected with computer networks was also studied. In addition, the R-cube (R{sup 3}) plan (realtime remote control robot technology) was proposed. 82 refs., 86 figs., 12 tabs.

  20. Physical Layer Network Coding

    OpenAIRE

    Shengli, Zhang; Liew, Soung-Chang; Lam, Patrick P. K.

    2007-01-01

    A main distinguishing feature of a wireless network compared with a wired network is its broadcast nature, in which the signal transmitted by a node may reach several other nodes, and a node may receive signals from several other nodes simultaneously. Rather than a blessing, this feature is treated more as an interference-inducing nuisance in most wireless networks today (e.g., IEEE 802.11). This paper shows that the concept of network coding can be applied at the physical layer to turn the b...

  1. Celestial data routing network

    Science.gov (United States)

    Bordetsky, Alex

    2000-11-01

    Imagine that information processing human-machine network is threatened in a particular part of the world. Suppose that an anticipated threat of physical attacks could lead to disruption of telecommunications network management infrastructure and access capabilities for small geographically distributed groups engaged in collaborative operations. Suppose that small group of astronauts are exploring the solar planet and need to quickly configure orbital information network to support their collaborative work and local communications. The critical need in both scenarios would be a set of low-cost means of small team celestial networking. To the geographically distributed mobile collaborating groups such means would allow to maintain collaborative multipoint work, set up orbital local area network, and provide orbital intranet communications. This would be accomplished by dynamically assembling the network enabling infrastructure of the small satellite based router, satellite based Codec, and set of satellite based intelligent management agents. Cooperating single function pico satellites, acting as agents and personal switching devices together would represent self-organizing intelligent orbital network of cooperating mobile management nodes. Cooperative behavior of the pico satellite based agents would be achieved by comprising a small orbital artificial neural network capable of learning and restructing the networking resources in response to the anticipated threat.

  2. Networks and Interactivity

    DEFF Research Database (Denmark)

    Considine, Mark; Lewis, Jenny

    2012-01-01

    The systemic reform of employment services in OECD countries was driven by New Public Management (NPM) and then post-NPM reforms, when first-phase changes such as privatization were amended with `joined up' processes to help manage fragmentation. This article examines the networking strategies...... of `street-level' employment services staff for the impacts of this. Contrary to expectations, networking has generally declined over the last decade. There are signs of path dependence in networking patterns within each country, but also a convergence of patterns for the UK and Australia......, but not The Netherlands. Networking appears to be mediated by policy and regulatory imperatives....

  3. Effective professional networking.

    Science.gov (United States)

    Goolsby, Mary Jo; Knestrick, Joyce M

    2017-08-01

    The reasons for nurse practitioners to develop a professional network are boundless and are likely to change over time. Networking opens doors and creates relationships that support new opportunities, personal development, collaborative research, policy activism, evidence-based practice, and more. Successful professional networking involves shared, mutually beneficial interactions between individuals and/or individuals and groups, regardless of whether it occurs face to face or electronically. This article combines nuggets from the literature with guidance based on the authors' combined experience in networking activities at the local, national, and international levels. ©2017 American Association of Nurse Practitioners.

  4. Introduction to neural networks

    International Nuclear Information System (INIS)

    Pavlopoulos, P.

    1996-01-01

    This lecture is a presentation of today's research in neural computation. Neural computation is inspired by knowledge from neuro-science. It draws its methods in large degree from statistical physics and its potential applications lie mainly in computer science and engineering. Neural networks models are algorithms for cognitive tasks, such as learning and optimization, which are based on concepts derived from research into the nature of the brain. The lecture first gives an historical presentation of neural networks development and interest in performing complex tasks. Then, an exhaustive overview of data management and networks computation methods is given: the supervised learning and the associative memory problem, the capacity of networks, the Perceptron networks, the functional link networks, the Madaline (Multiple Adalines) networks, the back-propagation networks, the reduced coulomb energy (RCE) networks, the unsupervised learning and the competitive learning and vector quantization. An example of application in high energy physics is given with the trigger systems and track recognition system (track parametrization, event selection and particle identification) developed for the CPLEAR experiment detectors from the LEAR at CERN. (J.S.). 56 refs., 20 figs., 1 tab., 1 appendix

  5. Mobile Virtual Private Networking

    Science.gov (United States)

    Pulkkis, Göran; Grahn, Kaj; Mårtens, Mathias; Mattsson, Jonny

    Mobile Virtual Private Networking (VPN) solutions based on the Internet Security Protocol (IPSec), Transport Layer Security/Secure Socket Layer (SSL/TLS), Secure Shell (SSH), 3G/GPRS cellular networks, Mobile IP, and the presently experimental Host Identity Protocol (HIP) are described, compared and evaluated. Mobile VPN solutions based on HIP are recommended for future networking because of superior processing efficiency and network capacity demand features. Mobile VPN implementation issues associated with the IP protocol versions IPv4 and IPv6 are also evaluated. Mobile VPN implementation experiences are presented and discussed.

  6. International Rehabilitation Network

    National Research Council Canada - National Science Library

    Smith, William

    2001-01-01

    The International Rehabilitation Network's goal is to improve the quality of services for land mine survivors and other amputee's through the dissemination of educational programs to rehabilitation professionals...

  7. Networked Instrumentation Element

    Data.gov (United States)

    National Aeronautics and Space Administration — Armstrong researchers have developed a networked instrumentation system that connects modern experimental payloads to existing analog and digital communications...

  8. Dynamic Sensor Networks

    National Research Council Canada - National Science Library

    Schott, Brian

    2004-01-01

    ...: Declarative Languages and Execution Environment includes topographical soldier interface and a sensor network simulation environment for algorithm development, deployment planning, and operational support. Finally, Task 3...

  9. Mobile networks architecture

    CERN Document Server

    Perez, Andre

    2013-01-01

    This book explains the evolutions of architecture for mobiles and summarizes the different technologies:- 2G: the GSM (Global System for Mobile) network, the GPRS (General Packet Radio Service) network and the EDGE (Enhanced Data for Global Evolution) evolution;- 3G: the UMTS (Universal Mobile Telecommunications System) network and the HSPA (High Speed Packet Access) evolutions:- HSDPA (High Speed Downlink Packet Access),- HSUPA (High Speed Uplink Packet Access),- HSPA+;- 4G: the EPS (Evolved Packet System) network.The telephone service and data transmission are the

  10. Heterogeneous cellular networks

    CERN Document Server

    Hu, Rose Qingyang

    2013-01-01

    A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses,  covering the related topics including scenarios of heterogeneous network deployment, interference management i

  11. Mobile ad hoc networking

    CERN Document Server

    John Wiley & Sons

    2004-01-01

    "Assimilating the most up-to-date information on research and development activities in this rapidly growing area, Mobile Ad Hoc Networking covers physical, data link, network, and transport layers, as well as application, security, simulation, and power management issues in sensor, local area, personal, and mobile ad hoc networks. Each of the book's sixteen chapters has been written by a top expert and discusses in-depth the most important topics in the field. Mobile Ad Hoc Networking is an excellent reference and guide for professionals seeking an in-depth examination of topics that also provides a comprehensive overview of the current state-of-the-art."--Jacket.

  12. Heterogeneous broadband network

    Science.gov (United States)

    Dittmann, Lars

    1995-11-01

    Although the vision for the future Integrated Broadband Communication Network (IBCN) is an all optical network, it is certain that for a long period to come, the network will remain very heterogeneous, with a mixture of different physical media (fiber, coax and twisted pair), transmission systems (PDH, SDH, ADSL) and transport protocols (TCP/IP, AAL/ATM, frame relay). In the current work towards the IBCN, the ATM concept is considered the generic network protocol for both public and private network, with the ability to use different underlying transmission protocols and, through adaptation protocols, provide the appropriate services (old as well as new) to the customer. One of the major difficulties of heterogeneous network is the restriction that is usually given by the lowest common denominator, e.g. in terms of single channel capacity. A possible way to overcome these limitations is by extending the ATM concept with a multilink capability, that allows us to use separate resources as one common. The improved flexibility obtained by this protocol extension further allows a real time optimization of network and call configuration, without any impact on the quality of service seen from the user. This paper describes an example of an ATM based multilink protocol that has been experimentally implemented within the RACE project 'STRATOSPHERIC'. The paper outlines the complexity of introducing an extra network functionality compared with the added value, such as an improved ability to recover an error due to a malfunctioning network component.

  13. Sharing network resources

    CERN Document Server

    Parekh, Abhay

    2014-01-01

    Resource Allocation lies at the heart of network control. In the early days of the Internet the scarcest resource was bandwidth, but as the network has evolved to become an essential utility in the lives of billions, the nature of the resource allocation problem has changed. This book attempts to describe the facets of resource allocation that are most relevant to modern networks. It is targeted at graduate students and researchers who have an introductory background in networking and who desire to internalize core concepts before designing new protocols and applications. We start from the fun

  14. Network Monitoring with Nagios

    CERN Document Server

    Dondich, Taylor

    2006-01-01

    Network monitoring can be a complex task to implement and maintain in your IT infrastructure. Nagios, an open-source host, service and network monitoring program can help you streamline your network monitoring tasks and reduce the cost of operation.With this shortcut guide, we'll go over how Nagios fits in the overall network monitoring puzzle. We'll also cover installation and basic usage. Finally, we'll show you how to extend Nagios with other tools to extend functionality.

  15. Optical network democratization.

    Science.gov (United States)

    Nejabati, Reza; Peng, Shuping; Simeonidou, Dimitra

    2016-03-06

    The current Internet infrastructure is not able to support independent evolution and innovation at physical and network layer functionalities, protocols and services, while at same time supporting the increasing bandwidth demands of evolving and heterogeneous applications. This paper addresses this problem by proposing a completely democratized optical network infrastructure. It introduces the novel concepts of the optical white box and bare metal optical switch as key technology enablers for democratizing optical networks. These are programmable optical switches whose hardware is loosely connected internally and is completely separated from their control software. To alleviate their complexity, a multi-dimensional abstraction mechanism using software-defined network technology is proposed. It creates a universal model of the proposed switches without exposing their technological details. It also enables a conventional network programmer to develop network applications for control of the optical network without specific technical knowledge of the physical layer. Furthermore, a novel optical network virtualization mechanism is proposed, enabling the composition and operation of multiple coexisting and application-specific virtual optical networks sharing the same physical infrastructure. Finally, the optical white box and the abstraction mechanism are experimentally evaluated, while the virtualization mechanism is evaluated with simulation. © 2016 The Author(s).

  16. Modelling dendritic ecological networks in space: An integrated network perspective

    Science.gov (United States)

    Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

  17. Entangled Networks, Synchronization, and Optimal Network Topology

    Science.gov (United States)

    Donetti, Luca; Hurtado, Pablo I.; Muñoz, Miguel A.

    2005-10-01

    A new family of graphs, entangled networks, with optimal properties in many respects, is introduced. By definition, their topology is such that it optimizes synchronizability for many dynamical processes. These networks are shown to have an extremely homogeneous structure: degree, node distance, betweenness, and loop distributions are all very narrow. Also, they are characterized by a very interwoven (entangled) structure with short average distances, large loops, and no well-defined community structure. This family of nets exhibits an excellent performance with respect to other flow properties such as robustness against errors and attacks, minimal first-passage time of random walks, efficient communication, etc. These remarkable features convert entangled networks in a useful concept, optimal or almost optimal in many senses, and with plenty of potential applications in computer science or neuroscience.

  18. The Benefits of Grid Networks

    Science.gov (United States)

    Tennant, Roy

    2005-01-01

    In the article, the author talks about the benefits of grid networks. In speaking of grid networks the author is referring to both networks of computers and networks of humans connected together in a grid topology. Examples are provided of how grid networks are beneficial today and the ways in which they have been used.

  19. Convergence of Networks

    DEFF Research Database (Denmark)

    Prasad, Ramjee; Ruggieri, Marina

    2008-01-01

    The paper focuses on the revolutionary changes that could characterise the future of networks. Those changes involve many aspects in the conceivement and exploitation of networks: architecture, services, technologies and modeling. The convergence of wired and wireless technologies along with the ...

  20. Nestedness in mutualistic networks

    OpenAIRE

    Rohr, Rudolf P.; Fortuna, Miguel A.; Luque, Bartolo; Bascompte, Jordi

    2013-01-01

    James et al. (2012) presented simulations that apparently falsify the analytical result by Bastolla et al. (2009), who showed that nested mutualistic interactions decrease interspecific competition and increase biodiversity in model ecosystems. This contradiction, however, mainly stems from the incorrect application of formulas derived for fully connected networks to empirical, sparse networks.

  1. Joint Hub Network Development

    NARCIS (Netherlands)

    Cruijssen, F.C.A.M.; Borm, P.E.M.; Dullaert, W.; Hamers, H.J.M.

    2007-01-01

    This paper introduces a framework for joint hub network development. Building a joint physical hub for transhipment of goods is expensive and therefore involves considerable risks for the cooperating companies. In a practical setting, it is unlikely that an entire network will be built at once.

  2. On Heterogeneous Covert Networks

    Science.gov (United States)

    Lindelauf, Roy; Borm, Peter; Hamers, Herbert

    Covert organizations are constantly faced with a tradeoff between secrecy and operational efficiency. Lindelauf, Borm and Hamers [13] developed a theoretical framework to determine optimal homogeneous networks taking the above mentioned considerations explicitly into account. In this paper this framework is put to the test by applying it to the 2002 Jemaah Islamiyah Bali bombing. It is found that most aspects of this covert network can be explained by the theoretical framework. Some interactions however provide a higher risk to the network than others. The theoretical framework on covert networks is extended to accommodate for such heterogeneous interactions. Given a network structure the optimal location of one risky interaction is established. It is shown that the pair of individuals in the organization that should conduct the interaction that presents the highest risk to the organization, is the pair that is the least connected to the remainder of the network. Furthermore, optimal networks given a single risky interaction are approximated and compared. When choosing among a path, star and ring graph it is found that for low order graphs the path graph is best. When increasing the order of graphs under consideration a transition occurs such that the star graph becomes best. It is found that the higher the risk a single interaction presents to the covert network the later this transition from path to star graph occurs.

  3. Beyond the networks

    DEFF Research Database (Denmark)

    Andreasen, Manja Hoppe; Møller-Jensen, Lasse

    2016-01-01

    through applications, co-financing of network extensions as well as lobbying efforts towards urban authorities and service providers. The formal service providers primarily take a reactive role, responding to demand, requests and political pressure from residents. Post-settlement network extensions...

  4. Clustering of correlated networks

    OpenAIRE

    Dorogovtsev, S. N.

    2003-01-01

    We obtain the clustering coefficient, the degree-dependent local clustering, and the mean clustering of networks with arbitrary correlations between the degrees of the nearest-neighbor vertices. The resulting formulas allow one to determine the nature of the clustering of a network.

  5. Network-Oblivious Algorithms

    DEFF Research Database (Denmark)

    Bilardi, Gianfranco; Pietracaprina, Andrea; Pucci, Geppino

    2016-01-01

    A framework is proposed for the design and analysis of network-oblivious algorithms, namely algorithms that can run unchanged, yet efficiently, on a variety of machines characterized by different degrees of parallelism and communication capabilities. The framework prescribes that a network-oblivi...

  6. Home Network Security

    NARCIS (Netherlands)

    Scholten, Hans; van Dijk, Hylke

    2008-01-01

    Service discovery and secure and safe service usage are essential elements in the deployment of home and personal networks. Because no system administrator is present, setup and daily operation of such a network has to be automated as much as possible with a high degree of user friendliness. To

  7. CRCHD Integrated Networks

    Science.gov (United States)

    INB supports two network-based programs—the National Outreach Network (NON) and the Geographic Management of Cancer Health Disparities Program (GMaP)—as well as advising on women’s health and sexual and gender minority opportunities within and across the NCI.

  8. KNOWLEDGE TRANSFER THROUGH NETWORKS

    Directory of Open Access Journals (Sweden)

    GYÖRGY ATTILA

    2012-06-01

    Full Text Available Knowledge is a vital intangible asset for any organization and cannot be valued exactly due its special form of materialization. Although we have this drawback, a scientifically established value should be used in order to measure the performance of knowledge holders. A correct valuation helps to know the worth of assets offered in exploitation. Exploitation of this resource could be done in several different ways, but integration in knowledge networks seems to generate best efficiency ratio. Networks offer the possibility to change information, to obtain new information, to build further ideas arose from network partners or to develop together new ideas. Thus, networks assure conditions to optimize the members’ knowledge portfolios. Optimization of knowledge usage creates benefits for network members. These benefits could be profits (if members are private companies or social welfare (if members are looking after collective purposes. Taxonomy of knowledge networks is diverse, permitting an adaptation to the needs of members. Networks permit a large scale of heterogeneity. Since an important part of new knowledge creating costs is covered from public budgetary resources, a special development is recorded at those networks which are exclusively or partly organized in the public sector or benefit by participation from the public sector.

  9. Networking wireless sensors

    National Research Council Canada - National Science Library

    Krishnamachari, Bhaskar

    2005-01-01

    ... by networking techniques across multiple layers. The topics covered include network deployment, localization, time synchronization, wireless radio characteristics, medium-access, topology control, routing, data-centric techniques, and transport protocols. Ideal for researchers and designers seeking to create new algorithms and protocols and enginee...

  10. Networking: OFFLU example

    Science.gov (United States)

    World Organization for Animal Health (OIE) and Food and Agriculture Organization (FAO) for the United Nations Influenza Network (OFFLU) is the joint OIE-FAO global network of expertise on animal influenzas: equine, swine, poultry and wild birds. OFFLU aims to reduce negative impacts of animal influ...

  11. Triangulation positioning system network

    Directory of Open Access Journals (Sweden)

    Sfendourakis Marios

    2017-01-01

    Full Text Available This paper presents ongoing work on localization and positioning through triangulation procedure for a Fixed Sensors Network - FSN.The FSN has to work as a system.As the triangulation problem becomes high complicated in a case with large numbers of sensors and transmitters, an adequate grid topology is needed in order to tackle the detection complexity.For that reason a Network grid topology is presented and areas that are problematic and need further analysis are analyzed.The Network System in order to deal with problems of saturation and False Triangulations - FTRNs will have to find adequate methods in every sub-area of the Area Of Interest - AOI.Also, concepts like Sensor blindness and overall Network blindness, are presented. All these concepts affect the Network detection rate and its performance and ought to be considered in a way that the network overall performance won’t be degraded.Network performance should be monitored contentiously, with right algorithms and methods.It is also shown that as the number of TRNs and FTRNs is increased Detection Complexity - DC is increased.It is hoped that with further research all the characteristics of a triangulation system network for positioning will be gained and the system will be able to perform autonomously with a high detection rate.

  12. Network cities and externalities

    Directory of Open Access Journals (Sweden)

    Rafael Boix Domènech

    2004-01-01

    Full Text Available The concept of «agglomeration economies» explains the existence of advantages derived from the concentration of population and activity. However, it does not explain the existence of spatially dynamic external economies. Network economies generated in networks of cities correspond to this last type, since they are generated from the interaction between urban units, linked by a network relationship. The objective of this research is to advance in the study of the relationship between the networks of cities and the generation of external economies. The research is divided in four parts: first we expose the link between networks of cities and external economies. The second part outlines a model for the combined measuring of the concentration and network economies. The third part explains the results of applying the model to a case of study: the network of cities of Catalonia. The results suggest that there is a causal relationship between the organization of the urban units forming networks of cities and the generation of external economies that affect growth and economic development. Finally, conclusions and policy implications are drawn up.

  13. FTS2000 network architecture

    Science.gov (United States)

    Klenart, John

    1991-01-01

    The network architecture of FTS2000 is graphically depicted. A map of network A topology is provided, with interservice nodes. Next, the four basic element of the architecture is laid out. Then, the FTS2000 time line is reproduced. A list of equipment supporting FTS2000 dedicated transmissions is given. Finally, access alternatives are shown.

  14. Local Area Networks.

    Science.gov (United States)

    Marks, Kenneth E.; Nielsen, Steven

    1991-01-01

    Discusses cabling that is needed in local area networks (LANs). Types of cables that may be selected are described, including twisted pair, coaxial cables (or ethernet), and fiber optics; network topologies, the manner in which the cables are laid out, are considered; and cable installation issues are discussed. (LRW)

  15. Deep Spiking Networks

    NARCIS (Netherlands)

    O'Connor, P.; Welling, M.

    2016-01-01

    We introduce an algorithm to do backpropagation on a spiking network. Our network is "spiking" in the sense that our neurons accumulate their activation into a potential over time, and only send out a signal (a "spike") when this potential crosses a threshold and the neuron is reset. Neurons only

  16. Innovation in Virtual Networks

    DEFF Research Database (Denmark)

    Hu, Yimei; Sørensen, Olav Jull

    2011-01-01

    The purpose of this article is to explore and highlight the particular innovation characteristics and modes of the chinese game industry from a networking perspective......The purpose of this article is to explore and highlight the particular innovation characteristics and modes of the chinese game industry from a networking perspective...

  17. Classroom Computer Network.

    Science.gov (United States)

    Lent, John

    1984-01-01

    This article describes a computer network system that connects several microcomputers to a single disk drive and one copy of software. Many schools are switching to networks as a cheaper and more efficient means of computer instruction. Teachers may be faced with copywriting problems when reproducing programs. (DF)

  18. Network SCADA System

    International Nuclear Information System (INIS)

    Milivojevic, Dragan R.; Tasic, Visa; Karabasevic, Dejan

    2003-01-01

    Copper Institute, Industrial Informatics department, is developing and applying network real time process monitoring and control systems. Some of these systems are already in use. The paper presents some hardware and software general remarks and performances, with special regard to communication sub-systems and network possibilities. (Author)

  19. Online Social Network Interactions:

    Directory of Open Access Journals (Sweden)

    Hui-Jung Chang

    2018-01-01

    Full Text Available A cross-cultural comparison of social networking structure on McDonald’s Facebook fan sites between Taiwan and the USA was conducted utilizing the individualism/collectivism dimension proposed by Hofstede. Four network indicators are used to describe the network structure of McDonald’s Facebook fan sites: size, density, clique and centralization. Individuals who post on both Facebook sites for the year of 2012 were considered as network participants for the purpose of the study. Due to the huge amount of data, only one thread of postings was sampled from each month of the year of 2012. The final data consists of 1002 postings written by 896 individuals and 5962 postings written by 5532 individuals from Taiwan and the USA respectively. The results indicated that the USA McDonald’s Facebook fan network has more fans, while Taiwan’s McDonald’s Facebook fan network is more densely connected. Cliques did form among the overall multiplex and within the individual uniplex networks in two countries, yet no significant differences were found between them. All the fan networks in both countries are relatively centralized, mostly on the site operators.

  20. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... to evaluate multiple epidemic scenarios in various network types....

  1. Personalized Home-Networks

    DEFF Research Database (Denmark)

    Soler, José; Gandy, Michael

    2007-01-01

    The paper provides details of a home-networking architecture based on an enhanced residential gateway. Initially the need for mechanisms allowing user-dependent network behavior is described and afterwards details of an initial implementation are provided in terms of architectural description...

  2. Untangle network security

    CERN Document Server

    El-Bawab, Abd El-Monem A

    2014-01-01

    If you are a security engineer or a system administrator and want to secure your server infrastructure with the feature-rich Untangle, this book is for you. For individuals who want to start their career in the network security field, this book would serve as a perfect companion to learn the basics of network security and how to implement it using Untangle NGFW.

  3. Trends in Optical Networks

    Indian Academy of Sciences (India)

    Integrated TDM/IP Service Network: Built using next-generation SDH · Case 2: ISP Backbone over SONET/SDH · Solution for the PoPs · Solution for the Gateway site · Case 3: Ethernet Leased Line Services over Existing Infrastructure · Transport for Mobile Voice/Data Networks · Functions needed for mapping Ethernet to ...

  4. Weaponizing Wireless Networks

    DEFF Research Database (Denmark)

    Giannetsos, Athanasios; Tassos, Dimitriou; Prasad, Neeli R.

    2010-01-01

    of a sensor network. Results show that our tool can be flexibly applied to different sensor network operating systems and protocol stacks giving an adversary privileges to which she is not entitled to. We hope that our tool will be used proactively, to study the weaknesses of new security protocols, and......, hopefully, to enhance the level of security provided by these solutions even further....

  5. Physical Layer Network Coding

    DEFF Research Database (Denmark)

    Fukui, Hironori; Yomo, Hironori; Popovski, Petar

    2013-01-01

    /receive interference. The way to deal with this problem in distributed wireless networks is usage of MAC-layer mechanisms that make a spatial reservation of the shared wireless medium, similar to the well-known RTS/CTS in IEEE 802.11 wireless networks. In this paper, we investigate two-way relaying in presence...

  6. Wireless networked music performance

    CERN Document Server

    Gabrielli, Leonardo

    2016-01-01

    This book presents a comprehensive overview of the state of the art in Networked Music Performance (NMP) and a historical survey of computer music networking. It introduces current technical trends in NMP and technical issues yet to be addressed. It also lists wireless communication protocols and compares these to the requirements of NMP. Practical use cases and advancements are also discussed.

  7. CAISSON: Interconnect Network Simulator

    Science.gov (United States)

    Springer, Paul L.

    2006-01-01

    Cray response to HPCS initiative. Model future petaflop computer interconnect. Parallel discrete event simulation techniques for large scale network simulation. Built on WarpIV engine. Run on laptop and Altix 3000. Can be sized up to 1000 simulated nodes per host node. Good parallel scaling characteristics. Flexible: multiple injectors, arbitration strategies, queue iterators, network topologies.

  8. Understanding telecommunications networks

    CERN Document Server

    Valdar, Andy

    2017-01-01

    A telecommunications network is an electronic system of links, nodes and the controls that govern their operations to allow voice and data transfer among users and devices. This fully revised, updated and expanded second edition covers all aspects of today's networks, including how they are planned, formed and operated.

  9. Integrating networks with Mathematica

    NARCIS (Netherlands)

    Strijkers, R.J.; Meijer, R.J.

    2008-01-01

    We have developed a concept that considers network behavior as a collection of software objects, which can be used or modified in computer programs. The interfaces of these software objects are exposed as web services and enable applications to analyze and manipulate networks, e.g. to find

  10. Trends in Optical Networks

    Indian Academy of Sciences (India)

    Traditional Solution: Building an overlay network with SDH and IP elements · Integrated TDM/IP Service Network: Built using next-generation SDH · Case 2: ISP Backbone over SONET/SDH · Solution for the PoPs ... Bandwidth Allocation Link Capacity Adjustment Scheme (LCAS) · Cost-Reducing EoS: Partial Protection.

  11. Knowledge in Communication Networks

    OpenAIRE

    Naumov, Pavel; Tao, Jia

    2015-01-01

    The paper investigates epistemic properties of information flow under communication protocols with a given topological structure of the communication network. The main result is a sound and complete logical system that describes all such properties. The system consists of a variation of the multi-agent epistemic logic S5 extended by a new network-specific Gateway axiom.

  12. Online social support networks.

    Science.gov (United States)

    Mehta, Neil; Atreja, Ashish

    2015-04-01

    Peer support groups have a long history and have been shown to improve health outcomes. With the increasing familiarity with online social networks like Facebook and ubiquitous access to the Internet, online social support networks are becoming popular. While studies have shown the benefit of these networks in providing emotional support or meeting informational needs, robust data on improving outcomes such as a decrease in health services utilization or reduction in adverse outcomes is lacking. These networks also pose unique challenges in the areas of patient privacy, funding models, quality of content, and research agendas. Addressing these concerns while creating patient-centred, patient-powered online support networks will help leverage these platforms to complement traditional healthcare delivery models in the current environment of value-based care.

  13. Managing Cisco network security

    CERN Document Server

    Knipp, Eric

    2002-01-01

    An in-depth knowledge of how to configure Cisco IP network security is a MUST for anyone working in today''s internetworked world"There''s no question that attacks on enterprise networks are increasing in frequency and sophistication..."-Mike Fuhrman, Cisco Systems Manager, Security ConsultingManaging Cisco Network Security, Second Edition offers updated and revised information covering many of Cisco''s security products that provide protection from threats, detection of network security incidents, measurement of vulnerability and policy compliance and management of security policy across an extended organization. These are the tools that network administrators have to mount defenses against threats. Chapters also cover the improved functionality and ease of the Cisco Secure Policy Manger software used by thousands of small-to-midsized businesses and a special section on the Cisco Aironet Wireless Security Solutions.Security from a real-world perspectiveKey coverage of the new technologies offered by the Cisc...

  14. High-Performance Networking

    CERN Multimedia

    CERN. Geneva

    2003-01-01

    The series will start with an historical introduction about what people saw as high performance message communication in their time and how that developed to the now to day known "standard computer network communication". It will be followed by a far more technical part that uses the High Performance Computer Network standards of the 90's, with 1 Gbit/sec systems as introduction for an in depth explanation of the three new 10 Gbit/s network and interconnect technology standards that exist already or emerge. If necessary for a good understanding some sidesteps will be included to explain important protocols as well as some necessary details of concerned Wide Area Network (WAN) standards details including some basics of wavelength multiplexing (DWDM). Some remarks will be made concerning the rapid expanding applications of networked storage.

  15. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  16. Organization Virtual or Networked?

    Directory of Open Access Journals (Sweden)

    Rūta Tamošiūnaitė

    2013-08-01

    Full Text Available Purpose—to present distinction between “virtual organization” and “networked organization”; giving their definitions.Design/methodology/approach—review of previous researches, systemic analyses of their findings and synthesis of distinctive characteristics of ”virtual organization” and “networked organization.”Findings—the main result of the research is key diverse features separating ”virtual organization” and ”networked organization.” Definitions of “virtual organization” and “networked organization” are presented.Originality/Value—distinction between “virtual organization” and “networked organization” creates possibilities to use all advantages of those types of organizations and gives foundation for deeper researches in this field.Research type: general review.

  17. Sensor Network Motes:

    DEFF Research Database (Denmark)

    Leopold, Martin

    This dissertation describes our efforts to improve sensor network performance evaluation and portability, within the context of the sensor network project Hogthrob. In Hogthrob, we faced the challenge of building an sensor network architecture for sow monitoring. This application has hard...... requirements on price and performance, and shows great potential for using sensor networks. Throughout the project we let the application requirements guide our design choices, leading us to push the technologies further to meet the specific goal of the application. In this dissertation, we attack two key...... to investigate these challenges and apart from developing the methodologies, we also present the results of our experiments. In particular, we present a new vector based methodology for performance evaluation of sensor network devices (motes) and applications, based on application specific benchmarking...

  18. Complex Networks IX

    CERN Document Server

    Coronges, Kate; Gonçalves, Bruno; Sinatra, Roberta; Vespignani, Alessandro; Proceedings of the 9th Conference on Complex Networks; CompleNet 2018

    2018-01-01

    This book aims to bring together researchers and practitioners working across domains and research disciplines to measure, model, and visualize complex networks. It collects the works presented at the 9th International Conference on Complex Networks (CompleNet) 2018 in Boston, MA in March, 2018. With roots in physical, information and social science, the study of complex networks provides a formal set of mathematical methods, computational tools and theories to describe prescribe and predict dynamics and behaviors of complex systems. Despite their diversity, whether the systems are made up of physical, technological, informational, or social networks, they share many common organizing principles and thus can be studied with similar approaches. This book provides a view of the state-of-the-art in this dynamic field and covers topics such as group decision-making, brain and cellular connectivity, network controllability and resiliency, online activism, recommendation systems, and cyber security.

  19. Concordant Chemical Reaction Networks

    Science.gov (United States)

    Shinar, Guy; Feinberg, Martin

    2015-01-01

    We describe a large class of chemical reaction networks, those endowed with a subtle structural property called concordance. We show that the class of concordant networks coincides precisely with the class of networks which, when taken with any weakly monotonic kinetics, invariably give rise to kinetic systems that are injective — a quality that, among other things, precludes the possibility of switch-like transitions between distinct positive steady states. We also provide persistence characteristics of concordant networks, instability implications of discordance, and consequences of stronger variants of concordance. Some of our results are in the spirit of recent ones by Banaji and Craciun, but here we do not require that every species suffer a degradation reaction. This is especially important in studying biochemical networks, for which it is rare to have all species degrade. PMID:22659063

  20. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    In the present paper we consider the allocation of cost in connection networks. Agents have connection demands in form of pairs of locations they want to be connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection demands....... We use three axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well as all...... connection costs; and, (3) the central planner selects a cost minimizing network satisfying reported connection demands based on estimated connection costs and allocates true connection costs of the selected network....

  1. Minimum cost connection networks

    DEFF Research Database (Denmark)

    Hougaard, Jens Leth; Tvede, Mich

    2015-01-01

    In the present paper we consider the allocation of costs in connection networks. Agents have connection demands in form of pairs of locations they want to have connected. Connections between locations are costly to build. The problem is to allocate costs of networks satisfying all connection...... demands. We use a few axioms to characterize allocation rules that truthfully implement cost minimizing networks satisfying all connection demands in a game where: (1) a central planner announces an allocation rule and a cost estimation rule; (2) every agent reports her own connection demand as well...... as all connection costs; (3) the central planner selects a cost minimizing network satisfying reported connection demands based on the estimated costs; and, (4) the planner allocates the true costs of the selected network. It turns out that an allocation rule satisfies the axioms if and only if relative...

  2. Collective network routing

    Science.gov (United States)

    Hoenicke, Dirk

    2014-12-02

    Disclosed are a unified method and apparatus to classify, route, and process injected data packets into a network so as to belong to a plurality of logical networks, each implementing a specific flow of data on top of a common physical network. The method allows to locally identify collectives of packets for local processing, such as the computation of the sum, difference, maximum, minimum, or other logical operations among the identified packet collective. Packets are injected together with a class-attribute and an opcode attribute. Network routers, employing the described method, use the packet attributes to look-up the class-specific route information from a local route table, which contains the local incoming and outgoing directions as part of the specifically implemented global data flow of the particular virtual network.

  3. Decentralized Online Social Networks

    Science.gov (United States)

    Datta, Anwitaman; Buchegger, Sonja; Vu, Le-Hung; Strufe, Thorsten; Rzadca, Krzysztof

    Current Online social networks (OSN) are web services run on logically centralized infrastructure. Large OSN sites use content distribution networks and thus distribute some of the load by caching for performance reasons, nevertheless there is a central repository for user and application data. This centralized nature of OSNs has several drawbacks including scalability, privacy, dependence on a provider, need for being online for every transaction, and a lack of locality. There have thus been several efforts toward decentralizing OSNs while retaining the functionalities offered by centralized OSNs. A decentralized online social network (DOSN) is a distributed system for social networking with no or limited dependency on any dedicated central infrastructure. In this chapter we explore the various motivations of a decentralized approach to online social networking, discuss several concrete proposals and types of DOSN as well as challenges and opportunities associated with decentralization.

  4. Consulting in the Library Network Environment.

    Science.gov (United States)

    Markuson, Barbara Evans

    1980-01-01

    Describes four elements of consulting in library networks: network client groups, potential sources of consultants, categories of network consulting, and difficulties in network-related consulting. (FM)

  5. Tinnitus: Network pathophysiology-network pharmacology

    Directory of Open Access Journals (Sweden)

    Ana Belen eElgoyhen

    2012-01-01

    Full Text Available Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for 1 in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single FDA-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in central nervous system pathologies is changing from that of magic bullets that target individual chemoreceptors or disease-causing genes into that of magic shotguns, promiscuous or dirty drugs that target disease-causing networks, also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy.

  6. Tinnitus: network pathophysiology-network pharmacology.

    Science.gov (United States)

    Elgoyhen, Ana B; Langguth, Berthold; Vanneste, Sven; De Ridder, Dirk

    2012-01-01

    Tinnitus, the phantom perception of sound, is a prevalent disorder. One in 10 adults has clinically significant subjective tinnitus, and for one in 100, tinnitus severely affects their quality of life. Despite the significant unmet clinical need for a safe and effective drug targeting tinnitus relief, there is currently not a single Food and Drug Administration (FDA)-approved drug on the market. The search for drugs that target tinnitus is hampered by the lack of a deep knowledge of the underlying neural substrates of this pathology. Recent studies are increasingly demonstrating that, as described for other central nervous system (CNS) disorders, tinnitus is a pathology of brain networks. The application of graph theoretical analysis to brain networks has recently provided new information concerning their topology, their robustness and their vulnerability to attacks. Moreover, the philosophy behind drug design and pharmacotherapy in CNS pathologies is changing from that of "magic bullets" that target individual chemoreceptors or "disease-causing genes" into that of "magic shotguns," "promiscuous" or "dirty drugs" that target "disease-causing networks," also known as network pharmacology. In the present work we provide some insight into how this knowledge could be applied to tinnitus pathophysiology and pharmacotherapy.

  7. Networked Leadership in Educational Collaborative Networks

    Science.gov (United States)

    Díaz-Gibson, Jordi; Zaragoza, Mireia Civís; Daly, Alan J.; Mayayo, Jordi Longás; Romaní, Jordi Riera

    2017-01-01

    Educational Collaborative Networks (ECNs) aim to achieve educational goals at the community level and base their actions on collaborative partnering between schools and community organizations. These approaches are an emergent and innovative leadership and policy strategy being used increasingly across the globe, given the interconnected and…

  8. Network topology descriptions in hybrid networks

    NARCIS (Netherlands)

    Grosso, P.; Brown, A.; Cedeyn, A.; Dijkstra, F.; van der Ham, J.; Patil, A.; Primet, P.; Swany, M.; Zurawski, J.

    2010-01-01

    The NML-WG goal is to define a schema for describing topologies of hybrid networks. This schema is in first instance intended for: • lightpath provisioning applications to exchange topology information intra and inter domain; • reporting performance metrics. This document constitutes Deliverable 1

  9. Mobility Network and Safety

    Directory of Open Access Journals (Sweden)

    Adriana Galderisi

    2010-04-01

    Full Text Available Mobility network is crucial for ensuring territorial safety with respect to natural and technological hazards. They represent a basic support to community’s everyday life although being exposed elements often characterized by high vulnerability to different hazards and, in the meanwhile, strategic equipments for emergency management. Physical damages or the lack in functioning of those networks may greatly increase the loss of human lives caused by hazardous events as well as produce relevant economic damages at medium and long term. Although the relevance of the mobility networks in assuring territorial safety is at present largely recognized, risk analyses have been long focused on buildings’ vulnerability or, even where they have paid attention to mobility network, they have been mainly focused on the physical damages that a given hazard could may induce on individual elements of such network. It is recent the awareness that mobility network represents a system, characterized by relevant interdependences both among its elements and among network infrastructures and urban systems. Based on these assumptions, this paper points out the heterogeneous aspects of the mobility network vulnerability and their relevance in increasing the overall territorial or urban vulnerability to hazardous events. Therefore, an in-depth investigation of the concept of mobility network vulnerability is provided, in order to highlight the aspects mostly investigated and more recent research perspectives. Finally, a case study in the Campania Region is presented in order to point out how traditional risk analyses, generally referred to individual hazards, can sometimes led to invest in the mobility network improvement or development which, targeted to increase the security of a territory result, on the opposite, in an increase of the territorial vulnerability.

  10. Network class superposition analyses.

    Directory of Open Access Journals (Sweden)

    Carl A B Pearson

    Full Text Available Networks are often used to understand a whole system by modeling the interactions among its pieces. Examples include biomolecules in a cell interacting to provide some primary function, or species in an environment forming a stable community. However, these interactions are often unknown; instead, the pieces' dynamic states are known, and network structure must be inferred. Because observed function may be explained by many different networks (e.g., ≈ 10(30 for the yeast cell cycle process, considering dynamics beyond this primary function means picking a single network or suitable sample: measuring over all networks exhibiting the primary function is computationally infeasible. We circumvent that obstacle by calculating the network class ensemble. We represent the ensemble by a stochastic matrix T, which is a transition-by-transition superposition of the system dynamics for each member of the class. We present concrete results for T derived from boolean time series dynamics on networks obeying the Strong Inhibition rule, by applying T to several traditional questions about network dynamics. We show that the distribution of the number of point attractors can be accurately estimated with T. We show how to generate Derrida plots based on T. We show that T-based Shannon entropy outperforms other methods at selecting experiments to further narrow the network structure. We also outline an experimental test of predictions based on T. We motivate all of these results in terms of a popular molecular biology boolean network model for the yeast cell cycle, but the methods and analyses we introduce are general. We conclude with open questions for T, for example, application to other models, computational considerations when scaling up to larger systems, and other potential analyses.

  11. A Network Traffic Control Enhancement Approach over Bluetooth Networks

    DEFF Research Database (Denmark)

    Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

    2003-01-01

    This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well...

  12. Decomposition of Network Communication Games

    NARCIS (Netherlands)

    Dietzenbacher, Bas; Borm, Peter; Hendrickx, Ruud

    2015-01-01

    Using network control structures this paper introduces network communication games as a generalization of vertex games and edge games corresponding to communication situations and studies their decomposition into unanimity games. We obtain a relation between the dividends of the network

  13. Neural Networks: Implementations and Applications

    NARCIS (Netherlands)

    Vonk, E.; Veelenturf, L.P.J.; Jain, L.C.

    1996-01-01

    Artificial neural networks, also called neural networks, have been used successfully in many fields including engineering, science and business. This paper presents the implementation of several neural network simulators and their applications in character recognition and other engineering areas

  14. Models of educational institutions' networking

    OpenAIRE

    Shilova Olga Nikolaevna

    2015-01-01

    The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.

  15. Extracting information from multiplex networks

    Science.gov (United States)

    Iacovacci, Jacopo; Bianconi, Ginestra

    2016-06-01

    Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

  16. Flow whitelisting in SCADA networks

    NARCIS (Netherlands)

    Barbosa, Rafael Ramos Regis; Sadre, Ramin; Pras, Aiko

    2013-01-01

    Supervisory control and data acquisition (SCADA) networks are commonly deployed in large industrial facilities. Modern SCADA networks are becoming more vulnerable to cyber attacks due to the common use of standard communications protocols and increased interconnections with corporate networks and

  17. Control of odour emission in wastewater treatment plants by direct and undirected measurement of odour emission capacity.

    Science.gov (United States)

    Zarra, T; Giuliani, S; Naddeo, V; Belgiorno, V

    2012-01-01

    Odour emissions from wastewater treatment plants (WWTPs) are considered to be the main causes of disturbance noticed by the exposed population and have relevant impacts on both tourism economy and land costs. Odour impact from WWTPs is generated by primary and secondary odour emissions. Primary odour emissions are related especially to the wastewater type and variability discharged into the sewer and directed to the WWTP, and to the wastewater collection and sewage system. Secondary odours are related to the treatment units of the plant. Several studies describe the key role of primary odour emissions and how they are strongly related to odour impacts of WWTPs. In this way, a opportune characterization of the emission capacity of primary odour could be an effective way to control odour emission in the WWTPs. In this study the odour emission capacity (OEC) of different domestic sewers was described and investigated; a correlation between the OEC and the main physical-chemical parameters of wastewater quality was also carried out. Results of this study identify the optimum conditions for sampling and measuring OEC in wastewaters and define its dependence by wastewater quality. These results can contribute to setting the standards for the maximum odourant content of wastewater that are discharged into the publicly owned sewage system.

  18. A Design of Computer Aided Instructions (CAI) for Undirected Graphs in the Discrete Math Tutorial (DMT). Part 1.

    Science.gov (United States)

    1990-06-01

    void); static void cont2 (void); static void cont3 (void); static void cont4 (void); static void confimn__graph-exit(void); static void nornial-exit...attach [Pagedowni to the cont3 function * setonkey(0x I 00,cont3,0); LILNE WIDTH = 3; cls(1); drawRect(-309,210,310,-200,1 1); drawLine(- 100,-80...34,28); write-horz str(- 1 80,-98 ,Ŕ(-)" ,28); cont3 (); static void cont3 (void) /* attach [Pageup] to the cont2 function * setonkey(0x4900,cont2,0

  19. Undirected health IT implementation in ambulatory care favors paper-based workarounds and limits health data exchange.

    Science.gov (United States)

    Djalali, Sima; Ursprung, Nadine; Rosemann, Thomas; Senn, Oliver; Tandjung, Ryan

    2015-11-01

    The adoption and use of health information technology (IT) continues to grow around the globe. In Switzerland, the government nor professional associations have to this day provided incentives for health IT adoption. We aim to assess the proportion of physicians who are routinely working with electronic health data and describe to what extent physicians exchange electronic health data with peers and other health care providers. Additionally, we aim to estimate the effect of physicians' attitude towards health IT on the adoption of electronic workflows. Between May and July 2013, we conducted a cross-sectional survey of 1200 practice based physicians in Switzerland. Respondents were asked to report on their technical means and where applicable their paper-based workarounds to process laboratory data, examination results, referral letters and physician's letters. Physicians' view of barriers and facilitators towards health IT use was determined by a composite score. A response rate of 57.1% (n=685) was reached. The sample was considered to be representative for physicians in Swiss ambulatory care. 35.2% of the respondents documented patients' health status with the help of a longitudinal semi-structured electronic text record generated by one or more encounters in the practice. Depending on the task within a workflow, around 11-46% of the respondents stated to rely on electronic workflow practices to process laboratory and examination data and dispatch referral notes and physician's letters. The permanent use of electronic workflow processes was infrequent. Instead, respondents reported paper-based workarounds affecting specific tasks within a workflow. Physicians' attitude towards health IT was significantly associated with the adoption of electronic workflows (OR 1.04-1.31, p<0.05), but the effect sizes of factors related to the working environment (e.g., regional factors, medical specialty, type of practice) were larger. At present, only a few physicians in Swiss ambulatory care routinely work with electronic health data. Until more of their peers participate in electronic exchange of structured clinical information, most physicians will continue to stay in paper-based systems and workarounds. The survey found that physicians with a positive attitude towards health IT were more likely to adopt electronic workflows, but the impact is minor. It will likely be necessary to introduce financial incentives and develop national standards in order to promote the adoption by a critical mass of practicing clinicians. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  20. Leadership Networking Connect, Collaborate, Create

    CERN Document Server

    (CCL), Center for Creative Leadership; Baldwin, David

    2011-01-01

    Networking is essential to effective leadership in today's organizations. Leaders who are skilled networkers have access to people, information, and resources to help solve problems and create opportunities. Leaders who neglect their networks are missing out on a critical component of their role as leaders. This book will help leaders take a new view of networking and provide insight into how to enhance their networks and become effective at leadership networking.

  1. Neural networks for aircraft control

    Science.gov (United States)

    Linse, Dennis

    1990-01-01

    Current research in Artificial Neural Networks indicates that networks offer some potential advantages in adaptation and fault tolerance. This research is directed at determining the possible applicability of neural networks to aircraft control. The first application will be to aircraft trim. Neural network node characteristics, network topology and operation, neural network learning and example histories using neighboring optimal control with a neural net are discussed.

  2. Strategic Networking for Online Success

    OpenAIRE

    Heitmann, M; Bremer, L; Stahl, F; Ansari, A

    2010-01-01

    The growth of online social networks and the decreasing effectiveness of traditional marketing have lead to a large interest in social networks. For an appropriate application of new marketing approaches marketers have to understand the impact of interactions and relationships among network members on their individual outcome and network popularity in order to use online social networks effectively in marketing. In this study we analyze networking behavior of music artists for promoting their...

  3. Network coding at different layers in wireless networks

    CERN Document Server

    2016-01-01

    This book focuses on how to apply network coding at different layers in wireless networks – including MAC, routing, and TCP – with special focus on cognitive radio networks. It discusses how to select parameters in network coding (e.g., coding field, number of packets involved, and redundant information ration) in order to be suitable for the varying wireless environments. The book explores how to deploy network coding in MAC to improve network performance and examines joint network coding with opportunistic routing to improve the successful rate of routing. In regards to TCP and network coding, the text considers transport layer protocol working with network coding to overcome the transmission error rate, particularly with how to use the ACK feedback of TCP to enhance the efficiency of network coding. The book pertains to researchers and postgraduate students, especially whose interests are in opportunistic routing and TCP in cognitive radio networks.

  4. Optical Network Testbeds Workshop

    Energy Technology Data Exchange (ETDEWEB)

    Joe Mambretti

    2007-06-01

    This is the summary report of the third annual Optical Networking Testbed Workshop (ONT3), which brought together leading members of the international advanced research community to address major challenges in creating next generation communication services and technologies. Networking research and development (R&D) communities throughout the world continue to discover new methods and technologies that are enabling breakthroughs in advanced communications. These discoveries are keystones for building the foundation of the future economy, which requires the sophisticated management of extremely large qualities of digital information through high performance communications. This innovation is made possible by basic research and experiments within laboratories and on specialized testbeds. Initial network research and development initiatives are driven by diverse motives, including attempts to solve existing complex problems, the desire to create powerful new technologies that do not exist using traditional methods, and the need to create tools to address specific challenges, including those mandated by large scale science or government agency mission agendas. Many new discoveries related to communications technologies transition to wide-spread deployment through standards organizations and commercialization. These transition paths allow for new communications capabilities that drive many sectors of the digital economy. In the last few years, networking R&D has increasingly focused on advancing multiple new capabilities enabled by next generation optical networking. Both US Federal networking R&D and other national R&D initiatives, such as those organized by the National Institute of Information and Communications Technology (NICT) of Japan are creating optical networking technologies that allow for new, powerful communication services. Among the most promising services are those based on new types of multi-service or hybrid networks, which use new optical networking

  5. Launch Control Network Engineer

    Science.gov (United States)

    Medeiros, Samantha

    2017-01-01

    The Spaceport Command and Control System (SCCS) is being built at the Kennedy Space Center in order to successfully launch NASA’s revolutionary vehicle that allows humans to explore further into space than ever before. During my internship, I worked with the Network, Firewall, and Hardware teams that are all contributing to the huge SCCS network project effort. I learned the SCCS network design and the several concepts that are running in the background. I also updated and designed documentation for physical networks that are part of SCCS. This includes being able to assist and build physical installations as well as configurations. I worked with the network design for vehicle telemetry interfaces to the Launch Control System (LCS); this allows the interface to interact with other systems at other NASA locations. This network design includes the Space Launch System (SLS), Interim Cryogenic Propulsion Stage (ICPS), and the Orion Multipurpose Crew Vehicle (MPCV). I worked on the network design and implementation in the Customer Avionics Interface Development and Analysis (CAIDA) lab.

  6. Optical storage networking

    Science.gov (United States)

    Mohr, Ulrich

    2001-11-01

    For efficient business continuance and backup of mission- critical data an inter-site storage network is required. Where traditional telecommunications costs are prohibitive for all but the largest organizations, there is an opportunity for regional carries to deliver an innovative storage service. This session reveals how a combination of optical networking and protocol-aware SAN gateways can provide an extended storage networking platform with the lowest cost of ownership and the highest possible degree of reliability, security and availability. Companies of every size, with mainframe and open-systems environments, can afford to use this integrated service. Three mayor applications are explained; channel extension, Network Attached Storage (NAS), Storage Area Networks (SAN) and how optical networks address the specific requirements. One advantage of DWDM is the ability for protocols such as ESCON, Fibre Channel, ATM and Gigabit Ethernet, to be transported natively and simultaneously across a single fiber pair, and the ability to multiplex many individual fiber pairs over a single pair, thereby reducing fiber cost and recovering fiber pairs already in use. An optical storage network enables a new class of service providers, Storage Service Providers (SSP) aiming to deliver value to the enterprise by managing storage, backup, replication and restoration as an outsourced service.

  7. Toward Optimal Transport Networks

    Science.gov (United States)

    Alexandrov, Natalia; Kincaid, Rex K.; Vargo, Erik P.

    2008-01-01

    Strictly evolutionary approaches to improving the air transport system a highly complex network of interacting systems no longer suffice in the face of demand that is projected to double or triple in the near future. Thus evolutionary approaches should be augmented with active design methods. The ability to actively design, optimize and control a system presupposes the existence of predictive modeling and reasonably well-defined functional dependences between the controllable variables of the system and objective and constraint functions for optimization. Following recent advances in the studies of the effects of network topology structure on dynamics, we investigate the performance of dynamic processes on transport networks as a function of the first nontrivial eigenvalue of the network's Laplacian, which, in turn, is a function of the network s connectivity and modularity. The last two characteristics can be controlled and tuned via optimization. We consider design optimization problem formulations. We have developed a flexible simulation of network topology coupled with flows on the network for use as a platform for computational experiments.

  8. Simulated Associating Polymer Networks

    Science.gov (United States)

    Billen, Joris

    Telechelic associating polymer networks consist of polymer chains terminated by endgroups that have a different chemical composition than the polymer backbone. When dissolved in a solution, the endgroups cluster together to form aggregates. At low temperature, a strongly connected reversible network is formed and the system behaves like a gel. Telechelic networks are of interest since they are representative for biopolymer networks (e.g. F-actin) and are widely used in medical applications (e.g. hydrogels for tissue engineering, wound dressings) and consumer products (e.g. contact lenses, paint thickeners). In this thesis such systems are studied by means of a molecular dynamics/Monte Carlo simulation. At first, the system in rest is studied by means of graph theory. The changes in network topology upon cooling to the gel state, are characterized. Hereto an extensive study of the eigenvalue spectrum of the gel network is performed. As a result, an in-depth investigation of the eigenvalue spectra for spatial ER, scale-free, and small-world networks is carried out. Next, the gel under the application of a constant shear is studied, with a focus on shear banding and the changes in topology under shear. Finally, the relation between the gel transition and percolation is discussed.

  9. Networked Microgrids Scoping Study

    Energy Technology Data Exchange (ETDEWEB)

    Backhaus, Scott N. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Dobriansky, Larisa [General MicroGrids, San Diego, CA (United States); Glover, Steve [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Liu, Chen-Ching [Washington State Univ., Pullman, WA (United States); Looney, Patrick [Brookhaven National Lab. (BNL), Upton, NY (United States); Mashayekh, Salman [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Pratt, Annabelle [National Renewable Energy Lab. (NREL), Golden, CO (United States); Schneider, Kevin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Stadler, Michael [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Starke, Michael [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Wang, Jianhui [Argonne National Lab. (ANL), Argonne, IL (United States); Yue, Meng [Brookhaven National Lab. (BNL), Upton, NY (United States)

    2016-12-05

    Much like individual microgrids, the range of opportunities and potential architectures of networked microgrids is very diverse. The goals of this scoping study are to provide an early assessment of research and development needs by examining the benefits of, risks created by, and risks to networked microgrids. At this time there are very few, if any, examples of deployed microgrid networks. In addition, there are very few tools to simulate or otherwise analyze the behavior of networked microgrids. In this setting, it is very difficult to evaluate networked microgrids systematically or quantitatively. At this early stage, this study is relying on inputs, estimations, and literature reviews by subject matter experts who are engaged in individual microgrid research and development projects, i.e., the authors of this study The initial step of the study gathered input about the potential opportunities provided by networked microgrids from these subject matter experts. These opportunities were divided between the subject matter experts for further review. Part 2 of this study is comprised of these reviews. Part 1 of this study is a summary of the benefits and risks identified in the reviews in Part 2 and synthesis of the research needs required to enable networked microgrids.

  10. Towards Optimal Transport Networks

    Directory of Open Access Journals (Sweden)

    Erik P. Vargo

    2010-08-01

    Full Text Available Our ultimate goal is to design transportation net- works whose dynamic performance metrics (e.g. pas- senger throughput, passenger delay, and insensitivity to weather disturbances are optimized. Here the fo- cus is on optimizing static features of the network that are known to directly affect the network dynamics. First, we present simulation results which support a connection between maximizing the first non-trivial eigenvalue of a network's Laplacian and superior air- port network performance. Then, we explore the ef- fectiveness of a tabu search heuristic for optimizing this metric by comparing experimental results to the- oretical upper bounds. We also consider generating upper bounds on a network's algebraic connectivity via the solution of semidefinite programming (SDP relaxations. A modification of an existing subgraph extraction algorithm is implemented to explore the underlying regional structures in the U.S. airport net- work, with the hope that the resulting localized struc- tures can be optimized independently and reconnected via a "backbone" network to achieve superior network performance.

  11. SBA Network Components & Software Inventory

    Data.gov (United States)

    Small Business Administration — SBA’s Network Components & Software Inventory contains a complete inventory of all devices connected to SBA’s network including workstations, servers, routers,...

  12. Optimal Network-Topology Design

    Science.gov (United States)

    Li, Victor O. K.; Yuen, Joseph H.; Hou, Ting-Chao; Lam, Yuen Fung

    1987-01-01

    Candidate network designs tested for acceptability and cost. Optimal Network Topology Design computer program developed as part of study on topology design and analysis of performance of Space Station Information System (SSIS) network. Uses efficient algorithm to generate candidate network designs consisting of subsets of set of all network components, in increasing order of total costs and checks each design to see whether it forms acceptable network. Technique gives true cost-optimal network and particularly useful when network has many constraints and not too many components. Program written in PASCAL.

  13. Robustness of airline route networks

    Science.gov (United States)

    Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

    2016-03-01

    Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

  14. COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks

    NARCIS (Netherlands)

    Sie, Rory

    2012-01-01

    Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.

  15. Data Exchange Network

    DEFF Research Database (Denmark)

    Grau Larsen, Anton; Ellersgaard, Christoph

    2015-01-01

    This article presents the extensive Danish elite network. Collected during 2012 and 2013, the data comprises 56,536 positions within 5,079 affiliations, and connects 37,750 individuals. The network consists of the largest Danish corporations, state institutions, NGO’s, and other integrative...... networks such as social clubs or royal events. Data were gathered through an inclusion principle, adding all potentially interesting affiliations. Procedures of name-matching and quality control are presented. Finally, the data are introduced: made available through a package for R, which enables...

  16. Wireless rechargeable sensor networks

    CERN Document Server

    Yang, Yuanyuan

    2015-01-01

    This SpringerBrief provides a concise guide to applying wireless energy transfer techniques in traditional battery-powered sensor networks. It examines the benefits and challenges of wireless power including efficiency and reliability. The authors build a wireless rechargeable sensor networks from scratch and aim to provide perpetual network operation. Chapters cover a wide range of topics from the collection of energy information and recharge scheduling to joint design with typical sensing applications such as data gathering. Problems are approached using a natural combination of probability

  17. Global Alumni Networks

    DEFF Research Database (Denmark)

    Hansen, Annette Skovsted

    2015-01-01

    One significant and often overlooked outcome of technical assistance and overseas capacity development programmes is the inclusion of experts from developing countries in epistemic communities. The main argument of this article is that the formal network structure offered to alumni of Japanese...... technical assistance and capacity development programmes have provided experts from developing countries access to epistemic communities since the early 1960s. This exploration of an alternative way of understanding capacity development programmes shows how alumni have made the networks global by using...... the Japanese network structure responding to the multilateral UNEPTA framework, which enables South-South and South-North connections....

  18. BES Science Network Requirements

    Energy Technology Data Exchange (ETDEWEB)

    Biocca, Alan; Carlson, Rich; Chen, Jackie; Cotter, Steve; Tierney, Brian; Dattoria, Vince; Davenport, Jim; Gaenko, Alexander; Kent, Paul; Lamm, Monica; Miller, Stephen; Mundy, Chris; Ndousse, Thomas; Pederson, Mark; Perazzo, Amedeo; Popescu, Razvan; Rouson, Damian; Sekine, Yukiko; Sumpter, Bobby; Dart, Eli; Wang, Cai-Zhuang -Z; Whitelam, Steve; Zurawski, Jason

    2011-02-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivityfor the US Department of Energy Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of the Office ofScience programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years.

  19. BES Science Network Requirements

    International Nuclear Information System (INIS)

    Dart, Eli; Tierney, Brian; Biocca, A.; Carlson, R.; Chen, J.; Cotter, S.; Dattoria, V.; Davenport, J.; Gaenko, A.; Kent, P.; Lamm, M.; Miller, S.; Mundy, C.; Ndousse, T.; Pederson, M.; Perazzo, A.; Popescu, R.; Rouson, D.; Sekine, Y.; Sumpter, B.; Wang, C.-Z.; Whitelam, S.; Zurawski, J.

    2011-01-01

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the US Department of Energy Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of the Office of Science programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 20 years.

  20. Wireless network pricing

    CERN Document Server

    Huang, Jianwei

    2013-01-01

    Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing