WorldWideScience

Sample records for network analysis tool

  1. Method and tool for network vulnerability analysis

    Science.gov (United States)

    Swiler, Laura Painton [Albuquerque, NM; Phillips, Cynthia A [Albuquerque, NM

    2006-03-14

    A computer system analysis tool and method that will allow for qualitative and quantitative assessment of security attributes and vulnerabilities in systems including computer networks. The invention is based on generation of attack graphs wherein each node represents a possible attack state and each edge represents a change in state caused by a single action taken by an attacker or unwitting assistant. Edges are weighted using metrics such as attacker effort, likelihood of attack success, or time to succeed. Generation of an attack graph is accomplished by matching information about attack requirements (specified in "attack templates") to information about computer system configuration (contained in a configuration file that can be updated to reflect system changes occurring during the course of an attack) and assumed attacker capabilities (reflected in "attacker profiles"). High risk attack paths, which correspond to those considered suited to application of attack countermeasures given limited resources for applying countermeasures, are identified by finding "epsilon optimal paths."

  2. Models as Tools of Analysis of a Network Organisation

    Directory of Open Access Journals (Sweden)

    Wojciech Pająk

    2013-06-01

    Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.

  3. Integrated Network Analysis and Effective Tools in Plant Systems Biology

    Directory of Open Access Journals (Sweden)

    Atsushi eFukushima

    2014-11-01

    Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

  4. ATHENA: the analysis tool for heritable and environmental network associations.

    Science.gov (United States)

    Holzinger, Emily R; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

    2014-03-01

    Advancements in high-throughput technology have allowed researchers to examine the genetic etiology of complex human traits in a robust fashion. Although genome-wide association studies have identified many novel variants associated with hundreds of traits, a large proportion of the estimated trait heritability remains unexplained. One hypothesis is that the commonly used statistical techniques and study designs are not robust to the complex etiology that may underlie these human traits. This etiology could include non-linear gene × gene or gene × environment interactions. Additionally, other levels of biological regulation may play a large role in trait variability. To address the need for computational tools that can explore enormous datasets to detect complex susceptibility models, we have developed a software package called the Analysis Tool for Heritable and Environmental Network Associations (ATHENA). ATHENA combines various variable filtering methods with machine learning techniques to analyze high-throughput categorical (i.e. single nucleotide polymorphisms) and quantitative (i.e. gene expression levels) predictor variables to generate multivariable models that predict either a categorical (i.e. disease status) or quantitative (i.e. cholesterol levels) outcomes. The goal of this article is to demonstrate the utility of ATHENA using simulated and biological datasets that consist of both single nucleotide polymorphisms and gene expression variables to identify complex prediction models. Importantly, this method is flexible and can be expanded to include other types of high-throughput data (i.e. RNA-seq data and biomarker measurements). ATHENA is freely available for download. The software, user manual and tutorial can be downloaded from http://ritchielab.psu.edu/ritchielab/software.

  5. Diffusion of Latent Semantic Analysis as a Research Tool: A Social Network Analysis Approach

    OpenAIRE

    Tonta, Yaşar; DARVISH, HAMID

    2010-01-01

    Latent semantic analysis (LSA) is a relatively new research tool with a wide range of applications in different fields ranging from discourse analysis to cognitive science, from information retrieval to machine learning and so on. In this paper, we chart the develop- ment and diffusion of LSA as a research tool using social network analysis (SNA) approach that reveals the social structure of a discipline in terms of collaboration among scientists. Using Thomson Reuters’ Web of Science (WoS), ...

  6. statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data

    Directory of Open Access Journals (Sweden)

    Mark S. Handcock

    2007-12-01

    Full Text Available statnet is a suite of software packages for statistical network analysis. The packages implement recent advances in network modeling based on exponential-family random graph models (ERGM. The components of the package provide a comprehensive framework for ERGM-based network modeling, including tools for model estimation, model evaluation, model-based network simulation, and network visualization. This broad functionality is powered by a central Markov chain Monte Carlo (MCMC algorithm. The coding is optimized for speed and robustness.

  7. Computational tools for large-scale biological network analysis

    OpenAIRE

    Pinto, José Pedro Basto Gouveia Pereira

    2012-01-01

    Tese de doutoramento em Informática The surge of the field of Bioinformatics, among other contributions, provided biological researchers with powerful computational methods for processing and analysing the large amount of data coming from recent biological experimental techniques such as genome sequencing and other omics. Naturally, this led to the opening of new avenues of biological research among which is included the analysis of large-scale biological networks. The an...

  8. Discerning molecular interactions: A comprehensive review on biomolecular interaction databases and network analysis tools.

    Science.gov (United States)

    Miryala, Sravan Kumar; Anbarasu, Anand; Ramaiah, Sudha

    2017-11-09

    Computational analysis of biomolecular interaction networks is now gaining a lot of importance to understand the functions of novel genes/proteins. Gene interaction (GI) network analysis and protein-protein interaction (PPI) network analysis play a major role in predicting the functionality of interacting genes or proteins and gives an insight into the functional relationships and evolutionary conservation of interactions among the genes. An interaction network is a graphical representation of gene/protein interactome, where each gene/protein is a node, and interaction between gene/protein is an edge. In this review, we discuss the popular open source databases that serve as data repositories to search and collect protein/gene interaction data, and also tools available for the generation of interaction network, visualization and network analysis. Also, various network analysis approaches like topological approach and clustering approach to study the network properties and functional enrichment server which illustrates the functions and pathway of the genes and proteins has been discussed. Hence the distinctive attribute mentioned in this review is not only to provide an overview of tools and web servers for gene and protein-protein interaction (PPI) network analysis but also to extract useful and meaningful information from the interaction networks. Copyright © 2017. Published by Elsevier B.V.

  9. Topological and Geometric Tools for the Analysis fo Complex Networks

    Science.gov (United States)

    2013-10-01

    faster than the current subgradient techniques for network optimization. Below, we will highlight some of the major advances. Some highlights are...Maximization Most existing work uses dual decomposition and subgradient methods to solve network optimization problems in a distributed manner, which...neighborhood. Simulation results illustrate the significant multiple order of magnitude performance gains of this method relative to subgradient methods

  10. Kiwi: a tool for integration and visualization of network topology and gene-set analysis.

    Science.gov (United States)

    Väremo, Leif; Gatto, Francesco; Nielsen, Jens

    2014-12-11

    The analysis of high-throughput data in biology is aided by integrative approaches such as gene-set analysis. Gene-sets can represent well-defined biological entities (e.g. metabolites) that interact in networks (e.g. metabolic networks), to exert their function within the cell. Data interpretation can benefit from incorporating the underlying network, but there are currently no optimal methods that link gene-set analysis and network structures. Here we present Kiwi, a new tool that processes output data from gene-set analysis and integrates them with a network structure such that the inherent connectivity between gene-sets, i.e. not simply the gene overlap, becomes apparent. In two case studies, we demonstrate that standard gene-set analysis points at metabolites regulated in the interrogated condition. Nevertheless, only the integration of the interactions between these metabolites provides an extra layer of information that highlights how they are tightly connected in the metabolic network. Kiwi is a tool that enhances interpretability of high-throughput data. It allows the users not only to discover a list of significant entities or processes as in gene-set analysis, but also to visualize whether these entities or processes are isolated or connected by means of their biological interaction. Kiwi is available as a Python package at http://www.sysbio.se/kiwi and an online tool in the BioMet Toolbox at http://www.biomet-toolbox.org.

  11. Constructing Social Networks From Secondary Storage With Bulk Analysis Tools

    Science.gov (United States)

    2016-06-01

    but we also have various amounts of file formats, encryption, and lack of training on programs that assist with analyzing data. Garfinkel’s paper...last issue addressed by Garfinkel is that there is not enough on-the-job training of digital forensic tools. This thesis has taken these issues into...wanted to provide an aesthetically pleasing and useful format for analysts. Furthermore, we wanted a method that was intuitive and consistent so analyst

  12. RADYBAN: A tool for reliability analysis of dynamic fault trees through conversion into dynamic Bayesian networks

    Energy Technology Data Exchange (ETDEWEB)

    Montani, S. [Dipartimento di Informatica, Universita del Piemonte Orientale, Via Bellini 25g, 15100 Alessandria (Italy)], E-mail: stefania@mfn.unipmn.it; Portinale, L. [Dipartimento di Informatica, Universita del Piemonte Orientale, Via Bellini 25g, 15100 Alessandria (Italy)], E-mail: portinal@mfn.unipmn.it; Bobbio, A. [Dipartimento di Informatica, Universita del Piemonte Orientale, Via Bellini 25g, 15100 Alessandria (Italy)], E-mail: bobbio@mfn.unipmn.it; Codetta-Raiteri, D. [Dipartimento di Informatica, Universita del Piemonte Orientale, Via Bellini 25g, 15100 Alessandria (Italy)], E-mail: raiteri@mfn.unipmn.it

    2008-07-15

    In this paper, we present RADYBAN (Reliability Analysis with DYnamic BAyesian Networks), a software tool which allows to analyze a dynamic fault tree relying on its conversion into a dynamic Bayesian network. The tool implements a modular algorithm for automatically translating a dynamic fault tree into the corresponding dynamic Bayesian network and exploits classical algorithms for the inference on dynamic Bayesian networks, in order to compute reliability measures. After having described the basic features of the tool, we show how it operates on a real world example and we compare the unreliability results it generates with those returned by other methodologies, in order to verify the correctness and the consistency of the results obtained.

  13. xMWAS: a data-driven integration and differential network analysis tool.

    Science.gov (United States)

    Uppal, Karan; Ma, Chunyu; Go, Young-Mi; Jones, Dean P; Wren, Jonathan

    2018-02-15

    Integrative omics is a central component of most systems biology studies. Computational methods are required for extracting meaningful relationships across different omics layers. Various tools have been developed to facilitate integration of paired heterogenous omics data; however most existing tools allow integration of only two omics datasets. Furthermore, existing data integration tools do not incorporate additional steps of identifying sub-networks or communities of highly connected entities and evaluating the topology of the integrative network under different conditions. Here we present xMWAS, a software for data integration, network visualization, clustering, and differential network analysis of data from biochemical and phenotypic assays, and two or more omics platforms. https://kuppal.shinyapps.io/xmwas (Online) and https://github.com/kuppal2/xMWAS/ (R). kuppal2@emory.edu. Supplementary data are available at Bioinformatics online.

  14. MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

    Science.gov (United States)

    Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

    2016-03-18

    Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

  15. Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

    Directory of Open Access Journals (Sweden)

    Fikret Emre eKapucu

    2012-06-01

    Full Text Available In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC, exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI histograms. Moreover, the algorithm calculates interspike interval thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

  16. Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics.

    Science.gov (United States)

    Kapucu, Fikret E; Tanskanen, Jarno M A; Mikkonen, Jarno E; Ylä-Outinen, Laura; Narkilahti, Susanna; Hyttinen, Jari A K

    2012-01-01

    In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESCs), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI) histograms. Moreover, the algorithm calculates ISI thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average (CMA) and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA) data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

  17. Recognition of Protozoa and Metazoa using image analysis tools, discriminant analysis, neural networks and decision trees.

    Science.gov (United States)

    Ginoris, Y P; Amaral, A L; Nicolau, A; Coelho, M A Z; Ferreira, E C

    2007-07-09

    Protozoa and metazoa are considered good indicators of the treatment quality in activated sludge systems due to the fact that these organisms are fairly sensitive to physical, chemical and operational processes. Therefore, it is possible to establish close relationships between the predominance of certain species or groups of species and several operational parameters of the plant, such as the biotic indices, namely the Sludge Biotic Index (SBI). This procedure requires the identification, classification and enumeration of the different species, which is usually achieved manually implying both time and expertise availability. Digital image analysis combined with multivariate statistical techniques has proved to be a useful tool to classify and quantify organisms in an automatic and not subjective way. This work presents a semi-automatic image analysis procedure for protozoa and metazoa recognition developed in Matlab language. The obtained morphological descriptors were analyzed using discriminant analysis, neural network and decision trees multivariable statistical techniques to identify and classify each protozoan or metazoan. The obtained procedure was quite adequate for distinguishing between the non-sessile protozoa classes and also for the metazoa classes, with high values for the overall species recognition with the exception of sessile protozoa. In terms of the wastewater conditions assessment the obtained results were found to be suitable for the prediction of these conditions. Finally, the discriminant analysis and neural networks results were found to be quite similar whereas the decision trees technique was less appropriate.

  18. BisoGenet: a new tool for gene network building, visualization and analysis.

    Science.gov (United States)

    Martin, Alexander; Ochagavia, Maria E; Rabasa, Laya C; Miranda, Jamilet; Fernandez-de-Cossio, Jorge; Bringas, Ricardo

    2010-02-17

    The increasing availability and diversity of omics data in the post-genomic era offers new perspectives in most areas of biomedical research. Graph-based biological networks models capture the topology of the functional relationships between molecular entities such as gene, protein and small compounds and provide a suitable framework for integrating and analyzing omics-data. The development of software tools capable of integrating data from different sources and to provide flexible methods to reconstruct, represent and analyze topological networks is an active field of research in bioinformatics. BisoGenet is a multi-tier application for visualization and analysis of biomolecular relationships. The system consists of three tiers. In the data tier, an in-house database stores genomics information, protein-protein interactions, protein-DNA interactions, gene ontology and metabolic pathways. In the middle tier, a global network is created at server startup, representing the whole data on bioentities and their relationships retrieved from the database. The client tier is a Cytoscape plugin, which manages user input, communication with the Web Service, visualization and analysis of the resulting network. BisoGenet is able to build and visualize biological networks in a fast and user-friendly manner. A feature of Bisogenet is the possibility to include coding relations to distinguish between genes and their products. This feature could be instrumental to achieve a finer grain representation of the bioentities and their relationships. The client application includes network analysis tools and interactive network expansion capabilities. In addition, an option is provided to allow other networks to be converted to BisoGenet. This feature facilitates the integration of our software with other tools available in the Cytoscape platform. BisoGenet is available at http://bio.cigb.edu.cu/bisogenet-cytoscape/.

  19. Using the Contextual Hub Analysis Tool (CHAT) in Cytoscape to Identify Contextually Relevant Network Hubs.

    Science.gov (United States)

    Muetze, Tanja; Lynn, David J

    2017-09-13

    Highly connected nodes in biological networks are called network hubs. Hubs are topologically important to the structure of the network and have been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we provide a step-by-step protocol for using the Contextual Hub Analysis Tool (CHAT), an application within Cytoscape 3, which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene or protein expression data, and identify hub nodes that are more highly connected to contextual nodes than expected by chance. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

  20. Network Connectance Analysis as a Tool to Understand Homeostasis of Plants under Environmental Changes

    Directory of Open Access Journals (Sweden)

    Suzana C. Bertolli

    2013-07-01

    Full Text Available The homeostasis of plants under environmental constraints may be maintained by alterations in the organization of their physiological networks. The ability to control a network depends on the strength of the connections between network elements, which is called network connectance. Herein, we intend to provide more evidence on the existence of a modulation pattern of photosynthetic networks, in response to adverse environmental conditions. Two species (Glycine max-C3 metabolism, and Brachiaria brizantha-C4 metabolism were submitted to two environmental constraints (water availability, and high and low temperatures, and from the physiological parameters measured, the global connectance (Cgtotal and the modules connectance (gas exchange-Cgge and photochemical-Cgpho were analyzed. Both types of environmental constraints impaired the photosynthetic capacity and the growth of the plants, indicating loss of their homeostasis, but in different ways. The results showed that in general the Cgtotal of both species increased with temperature increment and water deficit, indicating a higher modulation of photosynthetic networks. However, the Cg variation in both species did not influence the total dry biomass that was reduced by environmental adversities. This outcome is probably associated with a loss of system homeostasis. The connectance network analyses indicated a possible lack of correspondence between the photosynthetic networks modulation patterns and the homeostasis loss. However, this kind of analysis can be a powerful tool to access the degree of stability of a biological system, as well as to allow greater understanding of the dynamics underlying the photosynthetic processes that maintain the identity of the systems under environmental adversities.

  1. User-friendly Tool for Power Flow Analysis and Distributed Generation Optimisation in Radial Distribution Networks

    Directory of Open Access Journals (Sweden)

    M. F. Akorede

    2017-06-01

    Full Text Available The intent of power distribution companies (DISCOs is to deliver electric power to their customers in an efficient and reliable manner – with minimal energy loss cost. One major way to minimise power loss on a given power system is to install distributed generation (DG units on the distribution networks. However, to maximise benefits, it is highly crucial for a DISCO to ensure that these DG units are of optimal size and sited in the best locations on the network. This paper gives an overview of a software package developed in this study, called Power System Analysis and DG Optimisation Tool (PFADOT. The main purpose of the graphical user interface-based package is to guide a DISCO in finding the optimal size and location for DG placement in radial distribution networks. The package, which is also suitable for load flow analysis, employs the GUI feature of MATLAB. Three objective functions are formulated into a single optimisation problem and solved with fuzzy genetic algorithm to simultaneously obtain DG optimal size and location. The accuracy and reliability of the developed tool was validated using several radial test systems, and the results obtained are evaluated against the existing similar package cited in the literature, which are impressive and computationally efficient.

  2. Social network analysis shows direct evidence for social transmission of tool use in wild chimpanzees.

    Directory of Open Access Journals (Sweden)

    Catherine Hobaiter

    2014-09-01

    Full Text Available Social network analysis methods have made it possible to test whether novel behaviors in animals spread through individual or social learning. To date, however, social network analysis of wild populations has been limited to static models that cannot precisely reflect the dynamics of learning, for instance, the impact of multiple observations across time. Here, we present a novel dynamic version of network analysis that is capable of capturing temporal aspects of acquisition--that is, how successive observations by an individual influence its acquisition of the novel behavior. We apply this model to studying the spread of two novel tool-use variants, "moss-sponging" and "leaf-sponge re-use," in the Sonso chimpanzee community of Budongo Forest, Uganda. Chimpanzees are widely considered the most "cultural" of all animal species, with 39 behaviors suspected as socially acquired, most of them in the domain of tool-use. The cultural hypothesis is supported by experimental data from captive chimpanzees and a range of observational data. However, for wild groups, there is still no direct experimental evidence for social learning, nor has there been any direct observation of social diffusion of behavioral innovations. Here, we tested both a static and a dynamic network model and found strong evidence that diffusion patterns of moss-sponging, but not leaf-sponge re-use, were significantly better explained by social than individual learning. The most conservative estimate of social transmission accounted for 85% of observed events, with an estimated 15-fold increase in learning rate for each time a novice observed an informed individual moss-sponging. We conclude that group-specific behavioral variants in wild chimpanzees can be socially learned, adding to the evidence that this prerequisite for culture originated in a common ancestor of great apes and humans, long before the advent of modern humans.

  3. An overview of existing modeling tools making use of model checking in the analysis of biochemical networks.

    Science.gov (United States)

    Carrillo, Miguel; Góngora, Pedro A; Rosenblueth, David A

    2012-01-01

    Model checking is a well-established technique for automatically verifying complex systems. Recently, model checkers have appeared in computer tools for the analysis of biochemical (and gene regulatory) networks. We survey several such tools to assess the potential of model checking in computational biology. Next, our overview focuses on direct applications of existing model checkers, as well as on algorithms for biochemical network analysis influenced by model checking, such as those using binary decision diagrams (BDDs) or Boolean-satisfiability solvers. We conclude with advantages and drawbacks of model checking for the analysis of biochemical networks.

  4. Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

    Science.gov (United States)

    Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

    2016-01-01

    Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

  5. Data Visualization and Analysis Tools for the Global Precipitation Measurement (GPM) Validation Network

    Science.gov (United States)

    Morris, Kenneth R.; Schwaller, Mathew

    2010-01-01

    The Validation Network (VN) prototype for the Global Precipitation Measurement (GPM) Mission compares data from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR) to similar measurements from U.S. and international operational weather radars. This prototype is a major component of the GPM Ground Validation System (GVS). The VN provides a means for the precipitation measurement community to identify and resolve significant discrepancies between the ground radar (GR) observations and similar satellite observations. The VN prototype is based on research results and computer code described by Anagnostou et al. (2001), Bolen and Chandrasekar (2000), and Liao et al. (2001), and has previously been described by Morris, et al. (2007). Morris and Schwaller (2009) describe the PR-GR volume-matching algorithm used to create the VN match-up data set used for the comparisons. This paper describes software tools that have been developed for visualization and statistical analysis of the original and volume matched PR and GR data.

  6. A Design Tool Utilizing Stoichiometric Structure for the Analysis of Biochemical Reaction Networks

    Science.gov (United States)

    1990-05-20

    for the Analysis of Biochemical Reaction Networks 12.PERSONAL AUTHOR(S) Captain Stephen E. Kelly 13a.TYPE OF REPORT I 13b.TIME COVERED I14.DATE OF...necessary’apd identify by bldck numbe&)"War A method is proposed for the analysis of possible distributions of pro’ cts in biochemical reaction networks using...consistency and closure in fermentation material balanc-. -iSeveral biochemical reaction networks were examined. A proposed pathway for the biosynthetic

  7. Generating community-built tools for data sharing and analysis in environmental networks

    Science.gov (United States)

    Read, Jordan S.; Gries, Corinna; Read, Emily K.; Klug, Jennifer; Hanson, Paul C.; Hipsey, Matthew R.; Jennings, Eleanor; O'Reilley, Catherine; Winslow, Luke A.; Pierson, Don; McBride, Christopher G.; Hamilton, David

    2016-01-01

    Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

  8. Modelling the Steady State of Sewage Networks as a Support Tool for Their Planning and Analysis

    Directory of Open Access Journals (Sweden)

    Grażyna Petriczek

    2015-01-01

    Full Text Available Fundamental questions connected with the modelling of communal sewage networks have been considered and formulas used to model the functioning of the basic network have been analyzed. The problem described concerns gravitational sewage networks divided by nodes into branches and sectors. Simulation of the steady state functioning of sewage networks is commonly carried out on the basis of nomograms in the form of charts, in which the relations between network parameters like channel diameters, flow rates, hydraulic slopes and flow velocities are described. In traditional design, the values of such parameters are simply read from such nomogram chart tables. Another way of simulating the functioning of a network is the use of professional software, like SWMM, that models sewage flows along the channels by means of differential equations de-scribing the movement of fluids. In both approaches, the user is a mechanical operator of a "black box" procedure. In this paper, another way of simulating the functioning of sewage net-works has been presented. Numerical solutions of nonlinear equations describing the physical phenomena of sewage flows are applied and explained. The presented algorithms were developed to model the steady state of a sewage network enabling a quick analysis of the network parameters and the possibility of fast, simple and comprehensible network modeling and design. (original abstract

  9. USING ARTIFICIAL NEURAL NETWORKS AS STATISTICAL TOOLS FOR ANALYSIS OF MEDICAL DATA

    Directory of Open Access Journals (Sweden)

    ANOUSHIRAVAN KAZEMNEZHAD

    2003-06-01

    Full Text Available Introduction: Artificial neural networks mimic brains behavior. They are able to predict and feature recognition and classification. Therefore, neural networks seem to serious rivals for statistical models like regression and discriminant analysis. Methods: We have introduced biological neuron and generalized their function for artificial neurons and described back propagation error algoritm for training of networks in details. Result: Based on two simulated data and one real data we built neural networks by using back propagation and compared them by regression models. Discussion: Neural networks can be considered as a non parametric method for data modeling and seem that they are potentially. more powerful than regression for modeling, but more ambiguous in notation.

  10. Systematic analysis of natural hazards along infrastructure networks using a GIS-tool for risk assessment

    Science.gov (United States)

    Baruffini, Mirko

    2010-05-01

    GIS-based system can be for effective and efficient disaster response management. In the coming years our GIS application will be a data base containing all information needed for the evaluation of risk sites along the Gotthard line. Our GIS application can help the technical management to decide about protection measures because of, in addition to the visualisation, tools for spatial data analysis will be available. REFERENCES Bründl M. (Ed.) 2009 : Risikokonzept für Naturgefahren - Leitfaden. Nationale Plattform für Naturgefahren PLANAT, Bern. 416 S. BUWAL 1999: Risikoanalyse bei gravitativen Naturgefahren - Methode, Fallbeispiele und Daten (Risk analyses for gravitational natural hazards). Bundesamt für Umwelt, Wald und Landschaft (BUWAL). Umwelt-Materialen Nr. 107, 1-244. Loat, R. & Zimmermann, M. 2004: La gestion des risques en Suisse (Risk Management in Switzerland). In: Veyret, Y., Garry, G., Meschinet de Richemont, N. & Armand Colin (eds) 2002: Colloque Arche de la Défense 22-24 octobre 2002, dans Risques naturels et aménagement en Europe, 108-120. Maggi R. et al, 2009: Evaluation of the optimal resilience for vulnerable infrastructure networks. An interdisciplinary pilot study on the transalpine transportation corridors, NRP 54 "Sustainable Development of the Built Environment", Projekt Nr. 405 440, Final Scientific Report, Lugano

  11. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis

    OpenAIRE

    Giulia Berlusconi; Francesco Calderoni; Nicola Parolini; Marco Verani; Carlo Piccardi

    2017-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies s...

  12. Social Network Analysis: A Simple but Powerful Tool for Identifying Teacher Leaders

    Science.gov (United States)

    Smith, P. Sean; Trygstad, Peggy J.; Hayes, Meredith L.

    2018-01-01

    Instructional teacher leadership is central to a vision of distributed leadership. However, identifying instructional teacher leaders can be a daunting task, particularly for administrators who find themselves either newly appointed or faced with high staff turnover. This article describes the use of social network analysis (SNA), a simple but…

  13. Qualitative Network Analysis Tools for the Configurative Articulation of Cultural Value and Impact from Research

    Science.gov (United States)

    Oancea, Alis; Florez Petour, Teresa; Atkinson, Jeanette

    2017-01-01

    This article introduces a methodological approach for articulating and communicating the impact and value of research: qualitative network analysis using collaborative configuration tracing and visualization. The approach was proposed initially in Oancea ("Interpretations and Practices of Research Impact across the Range of Disciplines…

  14. Integration of Systems Network (SysNet) tools for regional land use scenario analysis in Asia

    NARCIS (Netherlands)

    Roetter, R.P.; Hoanh, C.T.; Laborte, A.G.; Keulen, van H.; Ittersum, van M.K.; Dreiser, C.; Diepen, van C.A.; Ridder, de N.; Laar, van H.H.

    2005-01-01

    This paper introduces the approach of the Systems research Network (SysNet) for land use planning in tropical Asia with a focus on its main scientific-technical output: the development of the land use planning and analysis system (LUPAS) and its component models. These include crop simulation

  15. anNET: a tool for network-embedded thermodynamic analysis of quantitative metabolome data

    Directory of Open Access Journals (Sweden)

    Zamboni Nicola

    2008-04-01

    Full Text Available Abstract Background Compared to other omics techniques, quantitative metabolomics is still at its infancy. Complex sample preparation and analytical procedures render exact quantification extremely difficult. Furthermore, not only the actual measurement but also the subsequent interpretation of quantitative metabolome data to obtain mechanistic insights is still lacking behind the current expectations. Recently, the method of network-embedded thermodynamic (NET analysis was introduced to address some of these open issues. Building upon principles of thermodynamics, this method allows for a quality check of measured metabolite concentrations and enables to spot metabolic reactions where active regulation potentially controls metabolic flux. So far, however, widespread application of NET analysis in metabolomics labs was hindered by the absence of suitable software. Results We have developed in Matlab a generalized software called 'anNET' that affords a user-friendly implementation of the NET analysis algorithm. anNET supports the analysis of any metabolic network for which a stoichiometric model can be compiled. The model size can span from a single reaction to a complete genome-wide network reconstruction including compartments. anNET can (i test quantitative data sets for thermodynamic consistency, (ii predict metabolite concentrations beyond the actually measured data, (iii identify putative sites of active regulation in the metabolic reaction network, and (iv help in localizing errors in data sets that were found to be thermodynamically infeasible. We demonstrate the application of anNET with three published Escherichia coli metabolome data sets. Conclusion Our user-friendly and generalized implementation of the NET analysis method in the software anNET allows users to rapidly integrate quantitative metabolome data obtained from virtually any organism. We envision that use of anNET in labs working on quantitative metabolomics will provide the

  16. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    Directory of Open Access Journals (Sweden)

    Giulia Berlusconi

    Full Text Available The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

  17. Link Prediction in Criminal Networks: A Tool for Criminal Intelligence Analysis.

    Science.gov (United States)

    Berlusconi, Giulia; Calderoni, Francesco; Parolini, Nicola; Verani, Marco; Piccardi, Carlo

    2016-01-01

    The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities.

  18. SentiHealth-Cancer: A sentiment analysis tool to help detecting mood of patients in online social networks.

    Science.gov (United States)

    Rodrigues, Ramon Gouveia; das Dores, Rafael Marques; Camilo-Junior, Celso G; Rosa, Thierson Couto

    2016-01-01

    Cancer is a critical disease that affects millions of people and families around the world. In 2012 about 14.1 million new cases of cancer occurred globally. Because of many reasons like the severity of some cases, the side effects of some treatments and death of other patients, cancer patients tend to be affected by serious emotional disorders, like depression, for instance. Thus, monitoring the mood of the patients is an important part of their treatment. Many cancer patients are users of online social networks and many of them take part in cancer virtual communities where they exchange messages commenting about their treatment or giving support to other patients in the community. Most of these communities are of public access and thus are useful sources of information about the mood of patients. Based on that, Sentiment Analysis methods can be useful to automatically detect positive or negative mood of cancer patients by analyzing their messages in these online communities. The objective of this work is to present a Sentiment Analysis tool, named SentiHealth-Cancer (SHC-pt), that improves the detection of emotional state of patients in Brazilian online cancer communities, by inspecting their posts written in Portuguese language. The SHC-pt is a sentiment analysis tool which is tailored specifically to detect positive, negative or neutral messages of patients in online communities of cancer patients. We conducted a comparative study of the proposed method with a set of general-purpose sentiment analysis tools adapted to this context. Different collections of posts were obtained from two cancer communities in Facebook. Additionally, the posts were analyzed by sentiment analysis tools that support the Portuguese language (Semantria and SentiStrength) and by the tool SHC-pt, developed based on the method proposed in this paper called SentiHealth. Moreover, as a second alternative to analyze the texts in Portuguese, the collected texts were automatically translated

  19. Design Tools for Large Networks

    CERN Document Server

    Panikashvili, E; 15th IEEE Real Time Conference 2007

    2007-01-01

    The Atlas TDAQ network consists of four separate networks which together total over 4000 ports at 1Gb/s, 40 ports at 10Gbps, 200 Ethernet switches at the edge of the network, 6 multiblade chassis switches at the core and over 20 km of copper and fiber cabling. The NetDesign suite was developed to provide a comprehensive set of design tools that permits the generation of a navigable circuit design, automates a number of routine tasks and provides the user with a powerful and flexible reporting system. Netdesign is an addon extension to the basic functionality of the Microsoft Visio CAD tool. It features: automatic labeling of cables, media / port connection validation, navigation along a cable, schematic hierarchical, cross-page and vertical navigation, overall verification of network diagram and hyperlinks to other equipment databases. The internal network structure can be exported to a 3rd party database from which a user-friendly meta-language is used to process a large variety of reports on the network des...

  20. Weighted Implementation of Suboptimal Paths (WISP): An Optimized Algorithm and Tool for Dynamical Network Analysis.

    Science.gov (United States)

    Van Wart, Adam T; Durrant, Jacob; Votapka, Lane; Amaro, Rommie E

    2014-02-11

    Allostery can occur by way of subtle cooperation among protein residues (e.g., amino acids) even in the absence of large conformational shifts. Dynamical network analysis has been used to model this cooperation, helping to computationally explain how binding to an allosteric site can impact the behavior of a primary site many ångstroms away. Traditionally, computational efforts have focused on the most optimal path of correlated motions leading from the allosteric to the primary active site. We present a program called Weighted Implementation of Suboptimal Paths (WISP) capable of rapidly identifying additional suboptimal pathways that may also play important roles in the transmission of allosteric signals. Aside from providing signal redundancy, suboptimal paths traverse residues that, if disrupted through pharmacological or mutational means, could modulate the allosteric regulation of important drug targets. To demonstrate the utility of our program, we present a case study describing the allostery of HisH-HisF, an amidotransferase from T. maritima thermotiga. WISP and its VMD-based graphical user interface (GUI) can be downloaded from http://nbcr.ucsd.edu/wisp.

  1. Latent Semantic Analysis As a Tool for Learner Positioning in Learning Networks for Lifelong Learning

    Science.gov (United States)

    van Bruggen, Jan; Sloep, Peter; van Rosmalen, Peter; Brouns, Francis; Vogten, Hubert; Koper, Rob; Tattersall, Colin

    2004-01-01

    As we move towards distributed, self-organised learning networks for lifelong learning to which multiple providers contribute content, there is a need to develop new techniques to determine where learners can be positioned in these networks. Positioning requires us to map characteristics of the learner onto characteristics of learning materials…

  2. Trace saver: A tool for network service improvement and personalised analysis of user centric statistics

    Science.gov (United States)

    Bilal, Muhammad; Asfand-e-Yar, Mockford, Steve; Khan, Wasiq; Awan, Irfan

    2012-11-01

    Mobile technology is among the fastest growing technologies in today's world with low cost and highly effective benefits. Most important and entertaining areas in mobile technology development and usage are location based services, user friendly networked applications and gaming applications. However, concern towards network operator service provision and improvement has been very low. The portable applications available for a range of mobile operating systems which help improve the network operator services are desirable by the mobile operators. This paper proposes a state of the art mobile application Tracesaver, which provides a great achievement over the barriers in gathering device and network related information, for network operators to improve their network service provision. Tracesaver is available for a broad range of mobile devices with different mobile operating systems and computational capabilities. The availability of Tracesaver in market has proliferated over the last year since it was published. The survey and results show that Tracesaver is being used by millions of mobile users and provides novel ways of network service improvement with its highly user friendly interface.

  3. Social Network Analysis: Applied Tool to Enhance Effective Collaboration between Child Protection Organisations by Revealing and Strengthening Work Relationships

    National Research Council Canada - National Science Library

    Beáta Dávid

    2013-01-01

    .... The qualitative approach was complemented by social network analysis. Revealing the mechanism based on the actors' perception on how the child protection network operates, we identifi ed and named the strengths and weaknesses of its structure...

  4. Enhancement of the FDOT's project level and network level bridge management analysis tools

    Science.gov (United States)

    2011-02-01

    Over several years, the Florida Department of Transportation (FDOT) has been implementing the AASHTO Pontis Bridge Management System to support network-level and project-level decision making in the headquarters and district offices. Pontis is an int...

  5. Social Network Analysis as a tool to analyze interaction of Batsmen and Bowlers in Cricket

    CERN Document Server

    Mukherjee, Satyam

    2012-01-01

    This paper describes the far reaching applications of network methods for understanding interaction within members of sport teams. Although a popular sport in the erstwhile English colonies, cricket has not received much attention from scientific community even though there is no dearth of statistics. This paper presents a network based approach to analyze the interaction of batsmen and bowlers in International cricket matches. First we consider the network of interaction between bowlers and batsmen. If two batsmen faced the same bowler they are connected by an unweighted link. Similarly if two bowlers bowled to the same batsman, they are connected. In this way a network of batsmen and bowlers is generated. We determine the exact values of clustering coefficient, average degree, average shortest path length of the networks and compare them with the Erd\\text{\\"{o}}s-R\\text{\\'{e}}nyi model and the configuration model. We also study an alternate version of the network in which two batsmen are connected if they a...

  6. VCAT: Visual Crosswalk Analysis Tool

    Energy Technology Data Exchange (ETDEWEB)

    Cleland, Timothy J. [Los Alamos National Laboratory; Forslund, David W. [Los Alamos National Laboratory; Cleland, Catherine A. [Los Alamos National Laboratory

    2012-08-31

    VCAT is a knowledge modeling and analysis tool. It was synthesized from ideas in functional analysis, business process modeling, and complex network science. VCAT discovers synergies by analyzing natural language descriptions. Specifically, it creates visual analytic perspectives that capture intended organization structures, then overlays the serendipitous relationships that point to potential synergies within an organization or across multiple organizations.

  7. Experimental and computational tools for analysis of signaling networks in primary cells

    DEFF Research Database (Denmark)

    Schoof, Erwin M; Linding, Rune

    2014-01-01

    , or differentiation. Protein phosphorylation events play a major role in this process and are often involved in fundamental biological and cellular processes such as protein-protein interactions, enzyme activity, and immune responses. Determining which kinases phosphorylate specific phospho sites poses a challenge......; this information is critical when trying to elucidate key proteins involved in specific cellular responses. Here, methods to generate high-quality quantitative phosphorylation data from cell lysates originating from primary cells, and how to analyze the generated data to construct quantitative signaling network...

  8. A critical analysis of the implementation of social networking as an e-recruitment tool within a security enterprise

    Directory of Open Access Journals (Sweden)

    Anthony Lewis

    2015-12-01

    Full Text Available Many enterprises are operating in complex and competitive environments, and changes in the internal and external environment have prompted them to engage in better ways of doing business. In order to respond to these changes, and survive in today’s volatile business environment, enterprises need to change their strategies. Human Resource departments are under pressure to keep operating costs low whilst also ensuring they are attracting, recruiting, and retaining talent within the enterprise. To achieve this, an increasing number of enterprises have adopted social networking into their recruitment strategy. This research aims to critically analyze the implementation of social networking as an e-recruitment tool within a Security Enterprise. The research key objective is to examine the importance of attracting Generation Y through the use of social networking sites and also to develop an understanding of the advantages and disadvantages of using social networking as an e-recruitment tool. The research also looks at contemporary examples of enterprises that have implemented social networking into their recruitment strategy. A further objective of the research is to gain an understanding of the attitudes and perceptions of the use of social networking as an e-recruitment tool. To achieve this, the research has taken a mixed-methods approach whilst focusing on an interpretivist stance. Data was gathered through an interview with the HR Manager at the Security Enterprise and a questionnaire was distributed to 22 employees within the enterprise and 84 respondents on social networking sites. The overall attitudes and perceptions of respondents showed that social networking can be effectively used as an e-recruitment tool as long as a traditional recruitment method is also used.

  9. A Software Tool of Technical and Financial-Economic Analysis for Acquistion of Broadband Radio PPDR Networks

    Directory of Open Access Journals (Sweden)

    Gierszal Henryk

    2016-12-01

    Full Text Available In this paper, we present a software tool that allows preparing econometric analyses aiming at selection of optimal business models for acquisition of broadband mobile networks by PPDR organizations. Such agencies often and often need broadband services to improve operational activities in order to increase the safety, security, and their effectiveness in day-to-day and crisis situations. Upgrade or migration to broadband networks needs careful decisions so as to find a justified trade-off between CAPEX and OPEX. The network evolution can be based on different business models but any approach cannot degrade the reliability, security, and resilience required by PSC.

  10. Network performance analysis

    CERN Document Server

    Bonald, Thomas

    2013-01-01

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

  11. Performance Analysis using CPN Tools

    DEFF Research Database (Denmark)

    Wells, Lisa Marie

    2006-01-01

    This paper provides an overview of new facilities for performance analysis using Coloured Petri Nets and the tool CPN Tools. Coloured Petri Nets is a formal modeling language that is well suited for modeling and analyzing large and complex systems. The new facilities include support for collecting...... data during simulations, for generating different kinds of performance-related output, and for running multiple simulation replications. A simple example of a network protocol is used to illustrate the flexibility of the new facilities....

  12. A software tool for network intrusion detection

    CSIR Research Space (South Africa)

    Van der Walt, C

    2012-10-01

    Full Text Available This presentation illustrates how a recently developed software tool enables operators to easily monitor a network and detect intrusions without requiring expert knowledge of network intrusion detections....

  13. Flow Analysis Tool White Paper

    Science.gov (United States)

    Boscia, Nichole K.

    2012-01-01

    Faster networks are continually being built to accommodate larger data transfers. While it is intuitive to think that implementing faster networks will result in higher throughput rates, this is often not the case. There are many elements involved in data transfer, many of which are beyond the scope of the network itself. Although networks may get bigger and support faster technologies, the presence of other legacy components, such as older application software or kernel parameters, can often cause bottlenecks. Engineers must be able to identify when data flows are reaching a bottleneck that is not imposed by the network and then troubleshoot it using the tools available to them. The current best practice is to collect as much information as possible on the network traffic flows so that analysis is quick and easy. Unfortunately, no single method of collecting this information can sufficiently capture the whole endto- end picture. This becomes even more of a hurdle when large, multi-user systems are involved. In order to capture all the necessary information, multiple data sources are required. This paper presents a method for developing a flow analysis tool to effectively collect network flow data from multiple sources and provide that information to engineers in a clear, concise way for analysis. The purpose of this method is to collect enough information to quickly (and automatically) identify poorly performing flows along with the cause of the problem. The method involves the development of a set of database tables that can be populated with flow data from multiple sources, along with an easyto- use, web-based front-end interface to help network engineers access, organize, analyze, and manage all the information.

  14. Trace Replay and Network Simulation Tool

    Energy Technology Data Exchange (ETDEWEB)

    2017-09-22

    TraceR Is a trace replay tool built upon the ROSS-based CODES simulation framework. TraceR can be used for predicting network performance and understanding network behavior by simulating messaging In High Performance Computing applications on interconnection networks.

  15. Network analysis as a tool for assessing environmental sustainability: applying the ecosystem perspective to a Danish water management system

    DEFF Research Database (Denmark)

    Pizzol, Massimo; Scotti, Marco; Thomsen, Marianne

    2013-01-01

    patterns of growth and development. We applied Network Analysis (NA) for assessing the sustainability of a Danish municipal Water Management System (WMS). We identified water users within the WMS and represented their interactions as a network of water flows. We computed intensive and extensive indices......New insights into the sustainable use of natural resources in human systems can be gained through comparison with ecosystems via common indices. In both kinds of system, resources are processed by a number of users within a network, but we consider ecosystems as the only ones displaying sustainable......: it is highly efficient at processing the water resource, but the rigid and almost linear structure makes it vulnerable in situations of stress such as heavy rain events. The analysis of future scenarios showed a trend towards increased sustainability, but differences between past and expected future...

  16. Social Network Analysis as an Analytic Tool for Task Group Research: A Case Study of an Interdisciplinary Community of Practice

    Science.gov (United States)

    Lockhart, Naorah C.

    2017-01-01

    Group counselors commonly collaborate in interdisciplinary settings in health care, substance abuse, and juvenile justice. Social network analysis is a methodology rarely used in counseling research yet has potential to examine task group dynamics in new ways. This case study explores the scholarly relationships among 36 members of an…

  17. Co-authorship Network Analysis: A Powerful Tool for Strategic Planning of Research, Development and Capacity Building Programs on Neglected Diseases

    Science.gov (United States)

    Morel, Carlos Medicis; Serruya, Suzanne Jacob; Penna, Gerson Oliveira; Guimarães, Reinaldo

    2009-01-01

    Background New approaches and tools were needed to support the strategic planning, implementation and management of a Program launched by the Brazilian Government to fund research, development and capacity building on neglected tropical diseases with strong focus on the North, Northeast and Center-West regions of the country where these diseases are prevalent. Methodology/Principal Findings Based on demographic, epidemiological and burden of disease data, seven diseases were selected by the Ministry of Health as targets of the initiative. Publications on these diseases by Brazilian researchers were retrieved from international databases, analyzed and processed with text-mining tools in order to standardize author- and institution's names and addresses. Co-authorship networks based on these publications were assembled, visualized and analyzed with social network analysis software packages. Network visualization and analysis generated new information, allowing better design and strategic planning of the Program, enabling decision makers to characterize network components by area of work, identify institutions as well as authors playing major roles as central hubs or located at critical network cut-points and readily detect authors or institutions participating in large international scientific collaborating networks. Conclusions/Significance Traditional criteria used to monitor and evaluate research proposals or R&D Programs, such as researchers' productivity and impact factor of scientific publications, are of limited value when addressing research areas of low productivity or involving institutions from endemic regions where human resources are limited. Network analysis was found to generate new and valuable information relevant to the strategic planning, implementation and monitoring of the Program. It afforded a more proactive role of the funding agencies in relation to public health and equity goals, to scientific capacity building objectives and a more

  18. Co-authorship network analysis: a powerful tool for strategic planning of research, development and capacity building programs on neglected diseases.

    Science.gov (United States)

    Morel, Carlos Medicis; Serruya, Suzanne Jacob; Penna, Gerson Oliveira; Guimarães, Reinaldo

    2009-08-18

    New approaches and tools were needed to support the strategic planning, implementation and management of a Program launched by the Brazilian Government to fund research, development and capacity building on neglected tropical diseases with strong focus on the North, Northeast and Center-West regions of the country where these diseases are prevalent. Based on demographic, epidemiological and burden of disease data, seven diseases were selected by the Ministry of Health as targets of the initiative. Publications on these diseases by Brazilian researchers were retrieved from international databases, analyzed and processed with text-mining tools in order to standardize author- and institution's names and addresses. Co-authorship networks based on these publications were assembled, visualized and analyzed with social network analysis software packages. Network visualization and analysis generated new information, allowing better design and strategic planning of the Program, enabling decision makers to characterize network components by area of work, identify institutions as well as authors playing major roles as central hubs or located at critical network cut-points and readily detect authors or institutions participating in large international scientific collaborating networks. Traditional criteria used to monitor and evaluate research proposals or R&D Programs, such as researchers' productivity and impact factor of scientific publications, are of limited value when addressing research areas of low productivity or involving institutions from endemic regions where human resources are limited. Network analysis was found to generate new and valuable information relevant to the strategic planning, implementation and monitoring of the Program. It afforded a more proactive role of the funding agencies in relation to public health and equity goals, to scientific capacity building objectives and a more consistent engagement of institutions and authors from endemic regions

  19. Co-authorship network analysis: a powerful tool for strategic planning of research, development and capacity building programs on neglected diseases.

    Directory of Open Access Journals (Sweden)

    Carlos Medicis Morel

    Full Text Available BACKGROUND: New approaches and tools were needed to support the strategic planning, implementation and management of a Program launched by the Brazilian Government to fund research, development and capacity building on neglected tropical diseases with strong focus on the North, Northeast and Center-West regions of the country where these diseases are prevalent. METHODOLOGY/PRINCIPAL FINDINGS: Based on demographic, epidemiological and burden of disease data, seven diseases were selected by the Ministry of Health as targets of the initiative. Publications on these diseases by Brazilian researchers were retrieved from international databases, analyzed and processed with text-mining tools in order to standardize author- and institution's names and addresses. Co-authorship networks based on these publications were assembled, visualized and analyzed with social network analysis software packages. Network visualization and analysis generated new information, allowing better design and strategic planning of the Program, enabling decision makers to characterize network components by area of work, identify institutions as well as authors playing major roles as central hubs or located at critical network cut-points and readily detect authors or institutions participating in large international scientific collaborating networks. CONCLUSIONS/SIGNIFICANCE: Traditional criteria used to monitor and evaluate research proposals or R&D Programs, such as researchers' productivity and impact factor of scientific publications, are of limited value when addressing research areas of low productivity or involving institutions from endemic regions where human resources are limited. Network analysis was found to generate new and valuable information relevant to the strategic planning, implementation and monitoring of the Program. It afforded a more proactive role of the funding agencies in relation to public health and equity goals, to scientific capacity building

  20. CRADA Final Report: Thermal Design and Analysis Tools for Dense-Wavelength-Division-Multiplexed (DWDM) Optical Networks

    Energy Technology Data Exchange (ETDEWEB)

    Hopkins, Deborah

    2005-01-31

    The current project originated from discussions with designers and engineers in the opto-electronics industry who sought help from LBNL in identifying effective thermal-management strategies for optical-network components and systems. Miniaturization of opto-electronic components exacerbates the thermal management problem because it allows a greater number of temperature-sensitive components to be fit into less space. Measurement techniques are required to evaluate emerging technologies, test prototype designs, and provide data that can be used to calibrate and validate models. To address these needs, LBNL and project partners developed a test station that allows experiments to be performed under tightly controlled conditions. The central component of the testing device is a "guarded" hot plate that enables high-precision temperature measurements, allowing forced-convection cooling devices to be evaluated. The device is so named because guard plates are used to eliminate heat flow and ensure that heat is not dissipated through the cooling device under investigation. This tool not only allows characterization of emerging technologies and materials, but also allows collection of high-resolution data that can be used to validate and improve simulation tools used to develop next-generation cooling devices for telecommunication systems. The ability to measure and analyze thermal performance benefits the photonics and optical-network industry by reducing development costs and time to market.

  1. Animal movement network analysis as a tool to map farms serving as contamination source in cattle cysticercosis

    Directory of Open Access Journals (Sweden)

    Samuel C. Aragão

    Full Text Available ABSTRACT: Bovine cysticercosis is a problem distributed worldwide that result in economic losses mainly due to the condemnation of infected carcasses. One of the difficulties in applying control measures is the identification of the source of infection, especially because cattle are typically acquired from multiple farms. Here, we tested the utility of an animal movement network constructed with data from a farm that acquires cattle from several other different farms to map the major contributors of cysticercosis propagation. Additionally, based on the results of the network analysis, we deployed a sanitary management and drug treatment scheme to decrease cysticercosis’ occurrence in the farm. Six farms that had commercial trades were identified by the animal movement network and characterized as the main contributors to the occurrence of cysticercosis in the studied farm. The identification of farms with a putative risk of Taenia saginata infection using the animal movement network along with the proper sanitary management and drug treatment resulted in a gradual decrease in cysticercosis prevalence, from 25% in 2010 to 3.7% in 2011 and 1.8% in 2012. These results suggest that the animal movement network can contribute towards controlling bovine cysticercosis, thus minimizing economic losses and preventing human taeniasis.

  2. Geographical Network Analysis and Spatial Econometrics as Tools to Enhance Our Understanding of Student Migration Patterns and Benefits in the U.S. Higher Education Network

    Science.gov (United States)

    González Canché, Manuel S.

    2018-01-01

    This study measures the extent to which student outmigration outside the 4-year sector takes place and posits that the benefits from attracting non-resident students exist regardless of sector of enrollment. The study also provides empirical evidence about the relevance of employing geographical network analysis (GNA) and spatial econometrics in…

  3. Networks as Tools for Sustainable Urban Development

    DEFF Research Database (Denmark)

    Jensen, Jesper Ole; Tollin, Nicola

    Due to the increasing number of networks related to sustainable development (SUD) the paper focuses on understanding in which way networks can be considered useful tools for sustainable urban development, taking particularly into consideration the networks potential of spreading innovative policies......, strategies and actions. There has been little theoretically development on the subject. In practice networks for sustainable development can be seen as combining different theoretical approaches to networks, including governance, urban competition and innovation. To give a picture of the variety...... of sustainable networks, we present different examples of networks, operating at different geographical scales, from global to local, with different missions (organizational, political, technical), fields (lobbying, learning, branding) and its size. The potentials and challenges related to sustainable networks...

  4. Networks as Tools for Urban Sustainability

    DEFF Research Database (Denmark)

    Jensen, Jesper Ole; Tollin, Nicola

    2004-01-01

    Due to the increasing number of networks related to sustainable development (SUD) the paper focuses on understanding in which way networks can be considered useful tools for sustainable urban development, taking particularly into consideration the networks potential of spreading innovative policies......, strategies and actions. There has been little theoretically development on the subject. In practice networks for sustainable development can be seen as combining different theoretical approaches to networks, including governance, urban competition and innovation. To give a picture of the variety...... of sustainable networks, we present different examples of networks, operating at different geographical scales, from global to local, with different missions (organizational, political, technical), fields (lobbying, learning, branding) and its size. The potentials and challenges related to sustainable networks...

  5. Enhancing Classroom Effectiveness through Social Networking Tools

    Science.gov (United States)

    Kurthakoti, Raghu; Boostrom, Robert E., Jr.; Summey, John H.; Campbell, David A.

    2013-01-01

    To determine the usefulness of social networking Web sites such as Ning.com as a communication tool in marketing courses, a study was designed with special concern for social network use in comparison to Blackboard. Students from multiple marketing courses were surveyed. Assessments of Ning.com and Blackboard were performed both to understand how…

  6. Multidimensional Analysis of Linguistic Networks

    Science.gov (United States)

    Araújo, Tanya; Banisch, Sven

    Network-based approaches play an increasingly important role in the analysis of data even in systems in which a network representation is not immediately apparent. This is particularly true for linguistic networks, which use to be induced from a linguistic data set for which a network perspective is only one out of several options for representation. Here we introduce a multidimensional framework for network construction and analysis with special focus on linguistic networks. Such a framework is used to show that the higher is the abstraction level of network induction, the harder is the interpretation of the topological indicators used in network analysis. Several examples are provided allowing for the comparison of different linguistic networks as well as to networks in other fields of application of network theory. The computation and the intelligibility of some statistical indicators frequently used in linguistic networks are discussed. It suggests that the field of linguistic networks, by applying statistical tools inspired by network studies in other domains, may, in its current state, have only a limited contribution to the development of linguistic theory.

  7. Social Networking Tools for Academic Libraries

    Science.gov (United States)

    Chu, Samuel Kai-Wah; Du, Helen S.

    2013-01-01

    This is an exploratory study investigating the use of social networking tools in academic libraries, examining the extent of their use, library staff's perceptions of their usefulness and challenges, and factors influencing decisions to use or not to use such tools. Invitations to participate in a web-based survey were sent to 140 university…

  8. Physics Analysis Tools Workshop 2007

    CERN Multimedia

    Elizabeth Gallas,

    The ATLAS PAT (Physics Analysis Tools) group evaluates, develops and tests software tools for the analysis of physics data, consistent with the ATLAS analysis and event data models. Following on from earlier PAT workshops in London (2004), Tucson (2005) and Tokyo (2006), this year's workshop was hosted by the University of Bergen in Norway on April 23-28 with more than 60 participants. The workshop brought together PAT developers and users to discuss the available tools with an emphasis on preparing for data taking. At the start of the week, workshop participants, laptops and power converters in-hand, jumped headfirst into tutorials, learning how to become trigger-aware and how to use grid computing resources via the distributed analysis tools Panda and Ganga. The well organised tutorials were well attended and soon the network was humming, providing rapid results to the users and ample feedback to the developers. A mid-week break was provided by a relaxing and enjoyable cruise through the majestic Norwegia...

  9. Network management tools for a GPS datalink network

    Science.gov (United States)

    Smyth, Padhraic; Chauvin, Todd; Oliver, Gordon; Statman, Joseph

    1991-01-01

    The availability of GPS (Global Position Satellite) information in real-time via a datalink system is shown to significantly increase the capacity of flight test and training ranges in terms of missions supported. This increase in mission activity. imposes demands on mission planning in the range-operations environment. In this context, network management tools which can improve the capability of range personnel to plan, monitor, and control network resources, are of significant interest. The application of both simulation and artificial intelligence techniques is described to develop such network managements tools.

  10. Contamination Analysis Tools

    Science.gov (United States)

    Brieda, Lubos

    2015-01-01

    This talk presents 3 different tools developed recently for contamination analysis:HTML QCM analyzer: runs in a web browser, and allows for data analysis of QCM log filesJava RGA extractor: can load in multiple SRS.ana files and extract pressure vs. time dataC++ Contamination Simulation code: 3D particle tracing code for modeling transport of dust particulates and molecules. Uses residence time to determine if molecules stick. Particulates can be sampled from IEST-STD-1246 and be accelerated by aerodynamic forces.

  11. Dynamic Contingency Analysis Tool

    Energy Technology Data Exchange (ETDEWEB)

    2016-01-14

    The Dynamic Contingency Analysis Tool (DCAT) is an open-platform and publicly available methodology to help develop applications that aim to improve the capabilities of power system planning engineers to assess the impact and likelihood of extreme contingencies and potential cascading events across their systems and interconnections. Outputs from the DCAT will help find mitigation solutions to reduce the risk of cascading outages in technically sound and effective ways. The current prototype DCAT implementation has been developed as a Python code that accesses the simulation functions of the Siemens PSS/E planning tool (PSS/E). It has the following features: It uses a hybrid dynamic and steady-state approach to simulating the cascading outage sequences that includes fast dynamic and slower steady-state events. It integrates dynamic models with protection scheme models for generation, transmission, and load. It models special protection systems (SPSs)/remedial action schemes (RASs) and automatic and manual corrective actions. Overall, the DCAT attempts to bridge multiple gaps in cascading-outage analysis in a single, unique prototype tool capable of automatically simulating and analyzing cascading sequences in real systems using multiprocessor computers.While the DCAT has been implemented using PSS/E in Phase I of the study, other commercial software packages with similar capabilities can be used within the DCAT framework.

  12. Regional Use of Social Networking Tools

    Science.gov (United States)

    2014-12-01

    4 2.1.7 Tumblr 4 2.1.8 Instagram 4 2.2 Local Social Networking Services 5 3 Regional Preferences for Social Networking Tools 6 4 African Region...YouTube 280 million Twitter 255 million LinkedIn n/a Pinterest n/a Tumblr 300 million Instagram 200 million The active-user base numbers...so this percentage may decline in the future. 2.1.8 Instagram Instagram , acquired by Facebook in 2012, is a mobile social networking service that

  13. A System Analysis Tool

    Energy Technology Data Exchange (ETDEWEB)

    CAMPBELL,PHILIP L.; ESPINOZA,JUAN

    2000-06-01

    In this paper we describe a tool for analyzing systems. The analysis is based on program slicing. It answers the following question for the software: if the value of a particular variable changes, what other variable values also change, and what is the path in between? program slicing was developed based on intra-procedure control and data flow. It has been expanded commercially to inter-procedure flow. However, we extend slicing to collections of programs and non-program entities, which we term multi-domain systems. The value of our tool is that an analyst can model the entirety of a system, not just the software, and we believe that this makes for a significant increase in power. We are building a prototype system.

  14. Social network diagnostics: a tool for monitoring group interventions.

    Science.gov (United States)

    Gesell, Sabina B; Barkin, Shari L; Valente, Thomas W

    2013-10-01

    Many behavioral interventions designed to improve health outcomes are delivered in group settings. To date, however, group interventions have not been evaluated to determine if the groups generate interaction among members and how changes in group interaction may affect program outcomes at the individual or group level. This article presents a model and practical tool for monitoring how social ties and social structure are changing within the group during program implementation. The approach is based on social network analysis and has two phases: collecting network measurements at strategic intervention points to determine if group dynamics are evolving in ways anticipated by the intervention, and providing the results back to the group leader to guide implementation next steps. This process aims to initially increase network connectivity and ultimately accelerate the diffusion of desirable behaviors through the new network. This article presents the Social Network Diagnostic Tool and, as proof of concept, pilot data collected during the formative phase of a childhood obesity intervention. The number of reported advice partners and discussion partners increased during program implementation. Density, the number of ties among people in the network expressed as a percentage of all possible ties, increased from 0.082 to 0.182 (p 0.05) in the discussion network. The observed two-fold increase in network density represents a significant shift in advice partners over the intervention period. Using the Social Network Tool to empirically guide program activities of an obesity intervention was feasible.

  15. Contextual Hub Analysis Tool (CHAT: A Cytoscape app for identifying contextually relevant hubs in biological networks [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Tanja Muetze

    2016-08-01

    Full Text Available Highly connected nodes (hubs in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT, which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest.   Availability: CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store (http://apps.cytoscape.org/apps/chat.

  16. Frequency Response Analysis Tool

    Energy Technology Data Exchange (ETDEWEB)

    Etingov, Pavel V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Kosterev, Dmitry [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Dai, T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-12-01

    Frequency response has received a lot of attention in recent years at the national level, which culminated in the development and approval of North American Electricity Reliability Corporation (NERC) BAL-003-1 Frequency Response and Frequency Bias Setting Reliability Standard. This report is prepared to describe the details of the work conducted by Pacific Northwest National Laboratory (PNNL) in collaboration with the Bonneville Power Administration and Western Electricity Coordinating Council (WECC) Joint Synchronized Information Subcommittee (JSIS) to develop a frequency response analysis tool (FRAT). The document provides the details on the methodology and main features of the FRAT. The tool manages the database of under-frequency events and calculates the frequency response baseline. Frequency response calculations are consistent with frequency response measure (FRM) in NERC BAL-003-1 for an interconnection and balancing authority. The FRAT can use both phasor measurement unit (PMU) data, where available, and supervisory control and data acquisition (SCADA) data. The tool is also capable of automatically generating NERC Frequency Response Survey (FRS) forms required by BAL-003-1 Standard.

  17. Social Networking Sites as a Learning Tool

    Science.gov (United States)

    Sanchez-Casado, Noelia; Cegarra Navarro, Juan Gabriel; Wensley, Anthony; Tomaseti-Solano, Eva

    2016-01-01

    Purpose: Over the past few years, social networking sites (SNSs) have become very useful for firms, allowing companies to manage the customer-brand relationships. In this context, SNSs can be considered as a learning tool because of the brand knowledge that customers develop from these relationships. Because of the fact that knowledge in…

  18. Draper Station Analysis Tool

    Science.gov (United States)

    Bedrossian, Nazareth; Jang, Jiann-Woei; McCants, Edward; Omohundro, Zachary; Ring, Tom; Templeton, Jeremy; Zoss, Jeremy; Wallace, Jonathan; Ziegler, Philip

    2011-01-01

    Draper Station Analysis Tool (DSAT) is a computer program, built on commercially available software, for simulating and analyzing complex dynamic systems. Heretofore used in designing and verifying guidance, navigation, and control systems of the International Space Station, DSAT has a modular architecture that lends itself to modification for application to spacecraft or terrestrial systems. DSAT consists of user-interface, data-structures, simulation-generation, analysis, plotting, documentation, and help components. DSAT automates the construction of simulations and the process of analysis. DSAT provides a graphical user interface (GUI), plus a Web-enabled interface, similar to the GUI, that enables a remotely located user to gain access to the full capabilities of DSAT via the Internet and Webbrowser software. Data structures are used to define the GUI, the Web-enabled interface, simulations, and analyses. Three data structures define the type of analysis to be performed: closed-loop simulation, frequency response, and/or stability margins. DSAT can be executed on almost any workstation, desktop, or laptop computer. DSAT provides better than an order of magnitude improvement in cost, schedule, and risk assessment for simulation based design and verification of complex dynamic systems.

  19. Network analysis applications in hydrology

    Science.gov (United States)

    Price, Katie

    2017-04-01

    Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

  20. Importance of simulation tools for the planning of optical network

    Science.gov (United States)

    Martins, Indayara B.; Martins, Yara; Rudge, Felipe; Moschimı, Edson

    2015-10-01

    The main proposal of this work is to show the importance of using simulation tools to project optical networks. The simulation method supports the investigation of several system and network parameters, such as bit error rate, blocking probability as well as physical layer issues, such as attenuation, dispersion, and nonlinearities, as these are all important to evaluate and validate the operability of optical networks. The work was divided into two parts: firstly, physical layer preplanning was proposed for the distribution of amplifiers and compensating for the attenuation and dispersion effects in span transmission; in this part, we also analyzed the quality of the transmitted signal. In the second part, an analysis of the transport layer was completed, proposing wavelength distribution planning, according to the total utilization of each link. The main network parameters used to evaluate the transport and physical layer design were delay (latency), blocking probability, and bit error rate (BER). This work was carried out with commercially available simulation tools.

  1. Development and psychometric testing of the clinical networks engagement tool.

    Directory of Open Access Journals (Sweden)

    Jill M Norris

    Full Text Available Clinical networks are being used widely to facilitate large system transformation in healthcare, by engagement of stakeholders throughout the health system. However, there are no available instruments that measure engagement in these networks.The study purpose was to develop and assess the measurement properties of a multiprofessional tool to measure engagement in clinical network initiatives. Based on components of the International Association of Public Participation Spectrum and expert panel review, we developed 40 items for testing. The draft instrument was distributed to 1,668 network stakeholders across different governance levels (leaders, members, support, frontline stakeholders in 9 strategic clinical networks in Alberta (January to July 2014. With data from 424 completed surveys (25.4% response rate, descriptive statistics, exploratory and confirmatory factor analysis, Pearson correlations, linear regression, multivariate analysis, and Cronbach alpha were conducted to assess reliability and validity of the scores.Sixteen items were retained in the instrument. Exploratory factor analysis indicated a four-factor solution and accounted for 85.7% of the total variance in engagement with clinical network initiatives: global engagement, inform (provided with information, involve (worked together to address concerns, and empower (given final decision-making authority. All subscales demonstrated acceptable reliability (Cronbach alpha 0.87 to 0.99. Both the confirmatory factor analysis and regression analysis confirmed that inform, involve, and empower were all significant predictors of global engagement, with involve as the strongest predictor. Leaders had higher mean scores than frontline stakeholders, while members and support staff did not differ in mean scores.This study provided foundational evidence for the use of this tool for assessing engagement in clinical networks. Further work is necessary to evaluate engagement in broader network

  2. Hurricane Data Analysis Tool

    Science.gov (United States)

    Liu, Zhong; Ostrenga, Dana; Leptoukh, Gregory

    2011-01-01

    In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of

  3. Java Radar Analysis Tool

    Science.gov (United States)

    Zaczek, Mariusz P.

    2005-01-01

    Java Radar Analysis Tool (JRAT) is a computer program for analyzing two-dimensional (2D) scatter plots derived from radar returns showing pieces of the disintegrating Space Shuttle Columbia. JRAT can also be applied to similar plots representing radar returns showing aviation accidents, and to scatter plots in general. The 2D scatter plots include overhead map views and side altitude views. The superposition of points in these views makes searching difficult. JRAT enables three-dimensional (3D) viewing: by use of a mouse and keyboard, the user can rotate to any desired viewing angle. The 3D view can include overlaid trajectories and search footprints to enhance situational awareness in searching for pieces. JRAT also enables playback: time-tagged radar-return data can be displayed in time order and an animated 3D model can be moved through the scene to show the locations of the Columbia (or other vehicle) at the times of the corresponding radar events. The combination of overlays and playback enables the user to correlate a radar return with a position of the vehicle to determine whether the return is valid. JRAT can optionally filter single radar returns, enabling the user to selectively hide or highlight a desired radar return.

  4. Social network sites: Indispensable or optional social tools?

    DEFF Research Database (Denmark)

    Shklovski, Irina

    2012-01-01

    Much research has enumerated potential benefits of online social network sites. Given the pervasiveness of these sites and the numbers of people that use them daily, both re-search and media tend to make the assumption that social network sites have become indispensible to their users. Based...... on the analysis of qualitative data from users of social network sites in Russia and Kazakhstan, this paper consid-ers under what conditions social network sites can become indispensable to their users and when these technologies remain on the periphery of life despite fulfilling useful func-tions. For some...... respondents, these sites had become indis-pensable tools as they were integrated into everyday rou-tines of communicating with emotionally important and proximal contacts and were often used for coordination of offline activities. For others social network sites remained spaces where they occasionally visited...

  5. Tools and Models for Integrating Multiple Cellular Networks

    Energy Technology Data Exchange (ETDEWEB)

    Gerstein, Mark [Yale Univ., New Haven, CT (United States). Gerstein Lab.

    2015-11-06

    In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novel algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed

  6. PANET: a GPU-based tool for fast parallel analysis of robustness dynamics and feed-forward/feedback loop structures in large-scale biological networks.

    Science.gov (United States)

    Trinh, Hung-Cuong; Le, Duc-Hau; Kwon, Yung-Keun

    2014-01-01

    It has been a challenge in systems biology to unravel relationships between structural properties and dynamic behaviors of biological networks. A Cytoscape plugin named NetDS was recently proposed to analyze the robustness-related dynamics and feed-forward/feedback loop structures of biological networks. Despite such a useful function, limitations on the network size that can be analyzed exist due to high computational costs. In addition, the plugin cannot verify an intrinsic property which can be induced by an observed result because it has no function to simulate the observation on a large number of random networks. To overcome these limitations, we have developed a novel software tool, PANET. First, the time-consuming parts of NetDS were redesigned to be processed in parallel using the OpenCL library. This approach utilizes the full computing power of multi-core central processing units and graphics processing units. Eventually, this made it possible to investigate a large-scale network such as a human signaling network with 1,609 nodes and 5,063 links. We also developed a new function to perform a batch-mode simulation where it generates a lot of random networks and conducts robustness calculations and feed-forward/feedback loop examinations of them. This helps us to determine if the findings in real biological networks are valid in arbitrary random networks or not. We tested our plugin in two case studies based on two large-scale signaling networks and found interesting results regarding relationships between coherently coupled feed-forward/feedback loops and robustness. In addition, we verified whether or not those findings are consistently conserved in random networks through batch-mode simulations. Taken together, our plugin is expected to effectively investigate various relationships between dynamics and structural properties in large-scale networks. Our software tool, user manual and example datasets are freely available at http://panet-csc.sourceforge.net/.

  7. A fast tool for minimum hybridization networks.

    Science.gov (United States)

    Chen, Zhi-Zhong; Wang, Lusheng; Yamanaka, Satoshi

    2012-07-02

    Due to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang's HybridNet and Albrecht et al.'s Dendroscope 3) run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need. We develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from the given trees by cutting some edges) such that

  8. A fast tool for minimum hybridization networks

    Directory of Open Access Journals (Sweden)

    Chen Zhi-Zhong

    2012-07-01

    Full Text Available Abstract Background Due to hybridization events in evolution, studying two different genes of a set of species may yield two related but different phylogenetic trees for the set of species. In this case, we want to combine the two phylogenetic trees into a hybridization network with the fewest hybridization events. This leads to three computational problems, namely, the problem of computing the minimum size of a hybridization network, the problem of constructing one minimum hybridization network, and the problem of enumerating a representative set of minimum hybridization networks. The previously best software tools for these problems (namely, Chen and Wang’s HybridNet and Albrecht et al.’s Dendroscope 3 run very slowly for large instances that cannot be reduced to relatively small instances. Indeed, when the minimum size of a hybridization network of two given trees is larger than 23 and the problem for the trees cannot be reduced to relatively smaller independent subproblems, then HybridNet almost always takes longer than 1 day and Dendroscope 3 often fails to complete. Thus, a faster software tool for the problems is in need. Results We develop a software tool in ANSI C, named FastHN, for the following problems: Computing the minimum size of a hybridization network, constructing one minimum hybridization network, and enumerating a representative set of minimum hybridization networks. We obtain FastHN by refining HybridNet with three ideas. The first idea is to preprocess the input trees so that the trees become smaller or the problem becomes to solve two or more relatively smaller independent subproblems. The second idea is to use a fast algorithm for computing the rSPR distance of two given phylognetic trees to cut more branches of the search tree in the exhaustive-search stage of the algorithm. The third idea is that during the exhaustive-search stage of the algorithm, we find two sibling leaves in one of the two forests (obtained from

  9. Real-world comparison of CPU and GPU implementations of SNPrank: a network analysis tool for GWAS.

    Science.gov (United States)

    Davis, Nicholas A; Pandey, Ahwan; McKinney, B A

    2011-01-15

    Bioinformatics researchers have a variety of programming languages and architectures at their disposal, and recent advances in graphics processing unit (GPU) computing have added a promising new option. However, many performance comparisons inflate the actual advantages of GPU technology. In this study, we carry out a realistic performance evaluation of SNPrank, a network centrality algorithm that ranks single nucleotide polymorhisms (SNPs) based on their importance in the context of a phenotype-specific interaction network. Our goal is to identify the best computational engine for the SNPrank web application and to provide a variety of well-tested implementations of SNPrank for Bioinformaticists to integrate into their research. Using SNP data from the Wellcome Trust Case Control Consortium genome-wide association study of Bipolar Disorder, we compare multiple SNPrank implementations, including Python, Matlab and Java as well as CPU versus GPU implementations. When compared with naïve, single-threaded CPU implementations, the GPU yields a large improvement in the execution time. However, with comparable effort, multi-threaded CPU implementations negate the apparent advantage of GPU implementations. The SNPrank code is open source and available at http://insilico.utulsa.edu/snprank.

  10. RMOD: a tool for regulatory motif detection in signaling network.

    Directory of Open Access Journals (Sweden)

    Jinki Kim

    Full Text Available Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  11. RMOD: a tool for regulatory motif detection in signaling network.

    Science.gov (United States)

    Kim, Jinki; Yi, Gwan-Su

    2013-01-01

    Regulatory motifs are patterns of activation and inhibition that appear repeatedly in various signaling networks and that show specific regulatory properties. However, the network structures of regulatory motifs are highly diverse and complex, rendering their identification difficult. Here, we present a RMOD, a web-based system for the identification of regulatory motifs and their properties in signaling networks. RMOD finds various network structures of regulatory motifs by compressing the signaling network and detecting the compressed forms of regulatory motifs. To apply it into a large-scale signaling network, it adopts a new subgraph search algorithm using a novel data structure called path-tree, which is a tree structure composed of isomorphic graphs of query regulatory motifs. This algorithm was evaluated using various sizes of signaling networks generated from the integration of various human signaling pathways and it showed that the speed and scalability of this algorithm outperforms those of other algorithms. RMOD includes interactive analysis and auxiliary tools that make it possible to manipulate the whole processes from building signaling network and query regulatory motifs to analyzing regulatory motifs with graphical illustration and summarized descriptions. As a result, RMOD provides an integrated view of the regulatory motifs and mechanism underlying their regulatory motif activities within the signaling network. RMOD is freely accessible online at the following URL: http://pks.kaist.ac.kr/rmod.

  12. Sight Application Analysis Tool

    Energy Technology Data Exchange (ETDEWEB)

    Bronevetsky, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2014-09-17

    The scale and complexity of scientific applications makes it very difficult to optimize, debug and extend them to support new capabilities. We have developed a tool that supports developers’ efforts to understand the logical flow of their applications and interactions between application components and hardware in a way that scales with application complexity and parallelism.

  13. GraphCrunch: A tool for large network analyses

    Directory of Open Access Journals (Sweden)

    Pržulj Nataša

    2008-01-01

    Full Text Available Abstract Background The recent explosion in biological and other real-world network data has created the need for improved tools for large network analyses. In addition to well established global network properties, several new mathematical techniques for analyzing local structural properties of large networks have been developed. Small over-represented subgraphs, called network motifs, have been introduced to identify simple building blocks of complex networks. Small induced subgraphs, called graphlets, have been used to develop "network signatures" that summarize network topologies. Based on these network signatures, two new highly sensitive measures of network local structural similarities were designed: the relative graphlet frequency distance (RGF-distance and the graphlet degree distribution agreement (GDD-agreement. Finding adequate null-models for biological networks is important in many research domains. Network properties are used to assess the fit of network models to the data. Various network models have been proposed. To date, there does not exist a software tool that measures the above mentioned local network properties. Moreover, none of the existing tools compare real-world networks against a series of network models with respect to these local as well as a multitude of global network properties. Results Thus, we introduce GraphCrunch, a software tool that finds well-fitting network models by comparing large real-world networks against random graph models according to various network structural similarity measures. It has unique capabilities of finding computationally expensive RGF-distance and GDD-agreement measures. In addition, it computes several standard global network measures and thus supports the largest variety of network measures thus far. Also, it is the first software tool that compares real-world networks against a series of network models and that has built-in parallel computing capabilities allowing for a user

  14. GraphCrunch: a tool for large network analyses.

    Science.gov (United States)

    Milenković, Tijana; Lai, Jason; Przulj, Natasa

    2008-01-30

    The recent explosion in biological and other real-world network data has created the need for improved tools for large network analyses. In addition to well established global network properties, several new mathematical techniques for analyzing local structural properties of large networks have been developed. Small over-represented subgraphs, called network motifs, have been introduced to identify simple building blocks of complex networks. Small induced subgraphs, called graphlets, have been used to develop "network signatures" that summarize network topologies. Based on these network signatures, two new highly sensitive measures of network local structural similarities were designed: the relative graphlet frequency distance (RGF-distance) and the graphlet degree distribution agreement (GDD-agreement). Finding adequate null-models for biological networks is important in many research domains. Network properties are used to assess the fit of network models to the data. Various network models have been proposed. To date, there does not exist a software tool that measures the above mentioned local network properties. Moreover, none of the existing tools compare real-world networks against a series of network models with respect to these local as well as a multitude of global network properties. Thus, we introduce GraphCrunch, a software tool that finds well-fitting network models by comparing large real-world networks against random graph models according to various network structural similarity measures. It has unique capabilities of finding computationally expensive RGF-distance and GDD-agreement measures. In addition, it computes several standard global network measures and thus supports the largest variety of network measures thus far. Also, it is the first software tool that compares real-world networks against a series of network models and that has built-in parallel computing capabilities allowing for a user specified list of machines on which to perform

  15. Google matrix analysis of directed networks

    Science.gov (United States)

    Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.

    2015-10-01

    In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.

  16. NOAA's Inundation Analysis Tool

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Coastal storms and other meteorological phenomenon can have a significant impact on how high water levels rise and how often. The inundation analysis program is...

  17. Constructing an Intelligent Patent Network Analysis Method

    OpenAIRE

    Chao-Chan Wu; Ching-Bang Yao

    2012-01-01

    Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks...

  18. Study of Tools for Network Discovery and Network Mapping

    Science.gov (United States)

    2003-11-01

    DISCOVERY OptiView Console supports central and distributed architectures. OptiView Console consists of the Viewer and the Service Manager that...OptiView console. Service Manager is the engine that performs network discovery, data management, data analysis, and provides notification services...The Service Manager gives you status information and configuration control of the services that are part of the OptiView Console application. These

  19. ATLAS Distributed Analysis Tools

    CERN Document Server

    Gonzalez de la Hoz, Santiago; Liko, Dietrich

    2008-01-01

    The ATLAS production system has been successfully used to run production of simulation data at an unprecedented scale. Up to 10000 jobs were processed in one day. The experiences obtained operating the system on several grid flavours was essential to perform a user analysis using grid resources. First tests of the distributed analysis system were then performed. In the preparation phase data was registered in the LHC File Catalog (LFC) and replicated in external sites. For the main test, few resources were used. All these tests are only a first step towards the validation of the computing model. The ATLAS management computing board decided to integrate the collaboration efforts in distributed analysis in only one project, GANGA. The goal is to test the reconstruction and analysis software in a large scale Data production using Grid flavors in several sites. GANGA allows trivial switching between running test jobs on a local batch system and running large-scale analyses on the Grid; it provides job splitting a...

  20. Social Network Analysis and Critical Realism

    DEFF Research Database (Denmark)

    Buch-Hansen, Hubert

    2014-01-01

    Social network analysis ( SNA) is an increasingly popular approach that provides researchers with highly developed tools to map and analyze complexes of social relations. Although a number of network scholars have explicated the assumptions that underpin SNA, the approach has yet to be discussed ...

  1. Criminal Network Investigation: Processes, Tools, and Techniques

    DEFF Research Database (Denmark)

    Petersen, Rasmus Rosenqvist

    intelligence products that can be disseminated to their customers. Investigators deal with an increasing amount of information from a variety of sources, especially the Internet, all of which are important to their analysis and decision making process. But information abundance is far from the only or most...... a target-centric process model (acquisition, synthesis, sense-making, dissemination, cooperation) encouraging and supporting an iterative and incremental evolution of the criminal network across all five investigation processes. The first priority of the process model is to address the problems of linear...

  2. Social network analysis and dual rover communications

    Science.gov (United States)

    Litaker, Harry L.; Howard, Robert L.

    2013-10-01

    Social network analysis (SNA) refers to the collection of techniques, tools, and methods used in sociometry aiming at the analysis of social networks to investigate decision making, group communication, and the distribution of information. Human factors engineers at the National Aeronautics and Space Administration (NASA) conducted a social network analysis on communication data collected during a 14-day field study operating a dual rover exploration mission to better understand the relationships between certain network groups such as ground control, flight teams, and planetary science. The analysis identified two communication network structures for the continuous communication and Twice-a-Day Communication scenarios as a split network and negotiated network respectfully. The major nodes or groups for the networks' architecture, transmittal status, and information were identified using graphical network mapping, quantitative analysis of subjective impressions, and quantified statistical analysis using Sociometric Statue and Centrality. Post-questionnaire analysis along with interviews revealed advantages and disadvantages of each network structure with team members identifying the need for a more stable continuous communication network, improved robustness of voice loops, and better systems training/capabilities for scientific imagery data and operational data during Twice-a-Day Communications.

  3. Reaction network analysis in biochemical signaling pathways

    OpenAIRE

    Martinez-Forero, I. (Iván); Pelaez, A. (Antonio); Villoslada, P. (Pablo)

    2010-01-01

    The aim of this thesis is to improve the understanding of signaling pathways through a theoretical study of chemical reaction networks. The equilibirum solution to the equations derived from chemical networks will be analytically resolved using tools from algebraic geometry. The chapters are organized as follows: 1. An introduction to chemical dynamics in biological systems with a special emphasis on steady state analysis 2. Complete description of the chemical reaction network theor...

  4. Social network analysis

    NARCIS (Netherlands)

    de Nooy, W.; Crothers, C.

    2009-01-01

    Social network analysis (SNA) focuses on the structure of ties within a set of social actors, e.g., persons, groups, organizations, and nations, or the products of human activity or cognition such as web sites, semantic concepts, and so on. It is linked to structuralism in sociology stressing the

  5. Automated Analysis of Security in Networking Systems

    DEFF Research Database (Denmark)

    Buchholtz, Mikael

    2004-01-01

    It has for a long time been a challenge to built secure networking systems. One way to counter this problem is to provide developers of software applications for networking systems with easy-to-use tools that can check security properties before the applications ever reach the marked. These tools...... will both help raise the general level of awareness of the problems and prevent the most basic flaws from occurring. This thesis contributes to the development of such tools. Networking systems typically try to attain secure communication by applying standard cryptographic techniques. In this thesis...... attacks, and attacks launched by insiders. Finally, the perspectives for the application of the analysis techniques are discussed, thereby, coming a small step closer to providing developers with easy- to-use tools for validating the security of networking applications....

  6. "Development Radar": The Co-Configuration of a Tool in a Learning Network

    Science.gov (United States)

    Toiviainen, Hanna; Kerosuo, Hannele; Syrjala, Tuula

    2009-01-01

    Purpose: The paper aims to argue that new tools are needed for operating, developing and learning in work-life networks where academic and practice knowledge are intertwined in multiple levels of and in boundary-crossing across activities. At best, tools for learning are designed in a process of co-configuration, as the analysis of one tool,…

  7. Network systems security analysis

    Science.gov (United States)

    Yilmaz, Ä.°smail

    2015-05-01

    Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.

  8. Network analytical tool for monitoring global food safety highlights China.

    Directory of Open Access Journals (Sweden)

    Tamás Nepusz

    Full Text Available BACKGROUND: The Beijing Declaration on food safety and security was signed by over fifty countries with the aim of developing comprehensive programs for monitoring food safety and security on behalf of their citizens. Currently, comprehensive systems for food safety and security are absent in many countries, and the systems that are in place have been developed on different principles allowing poor opportunities for integration. METHODOLOGY/PRINCIPAL FINDINGS: We have developed a user-friendly analytical tool based on network approaches for instant customized analysis of food alert patterns in the European dataset from the Rapid Alert System for Food and Feed. Data taken from alert logs between January 2003-August 2008 were processed using network analysis to i capture complexity, ii analyze trends, and iii predict possible effects of interventions by identifying patterns of reporting activities between countries. The detector and transgressor relationships are readily identifiable between countries which are ranked using i Google's PageRank algorithm and ii the HITS algorithm of Kleinberg. The program identifies Iran, China and Turkey as the transgressors with the largest number of alerts. However, when characterized by impact, counting the transgressor index and the number of countries involved, China predominates as a transgressor country. CONCLUSIONS/SIGNIFICANCE: This study reports the first development of a network analysis approach to inform countries on their transgressor and detector profiles as a user-friendly aid for the adoption of the Beijing Declaration. The ability to instantly access the country-specific components of the several thousand annual reports will enable each country to identify the major transgressors and detectors within its trading network. Moreover, the tool can be used to monitor trading countries for improved detector/transgressor ratios.

  9. Structural Analysis of Complex Networks

    CERN Document Server

    Dehmer, Matthias

    2011-01-01

    Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,

  10. Analysis of computer networks

    CERN Document Server

    Gebali, Fayez

    2015-01-01

    This textbook presents the mathematical theory and techniques necessary for analyzing and modeling high-performance global networks, such as the Internet. The three main building blocks of high-performance networks are links, switching equipment connecting the links together, and software employed at the end nodes and intermediate switches. This book provides the basic techniques for modeling and analyzing these last two components. Topics covered include, but are not limited to: Markov chains and queuing analysis, traffic modeling, interconnection networks and switch architectures and buffering strategies.   ·         Provides techniques for modeling and analysis of network software and switching equipment; ·         Discusses design options used to build efficient switching equipment; ·         Includes many worked examples of the application of discrete-time Markov chains to communication systems; ·         Covers the mathematical theory and techniques necessary for ana...

  11. Measuring Road Network Vulnerability with Sensitivity Analysis

    Science.gov (United States)

    Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin

    2017-01-01

    This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706

  12. Physics Analysis Tools Workshop Report

    CERN Multimedia

    Assamagan, K A

    A Physics Analysis Tools (PAT) workshop was held at the University of Tokyo in Tokyo Japan on May 15-19, 2006. Unlike the previous ones, this workshop brought together the core PAT developers and ATLAS users. The workshop was attended by 69 people from various institutions: Australia 5 Canada 1 China 6 CERN 4 Europe 7 Japan 32 Taiwan 3 USA 11 The agenda consisted of a 2-day tutorial for users, a 0.5-day user feedback discussion session between users and developers, and a 2-day core PAT workshop devoted to issues in Physics Analysis Tools activities. The tutorial, attended by users and developers, covered the following grounds: Event Selection with the TAG Event Selection Using the Athena-Aware NTuple Event Display Interactive Analysis within ATHENA Distributed Analysis Monte Carlo Truth Tools Trigger-Aware Analysis Event View By many accounts, the tutorial was useful. This workshop was the first time that the ATLAS Asia-Pacific community (Taiwan, Japan, China and Australia) go...

  13. Visualization and Analysis of Complex Covert Networks

    DEFF Research Database (Denmark)

    Memon, Bisharat

    This report discusses and summarize the results of my work so far in relation to my Ph.D. project entitled "Visualization and Analysis of Complex Covert Networks". The focus of my research is primarily on development of methods and supporting tools for visualization and analysis of networked...... systems that are covert and hence inherently complex. My Ph.D. is positioned within the wider framework of CrimeFighter project. The framework envisions a number of key knowledge management processes that are involved in the workflow, and the toolbox provides supporting tools to assist human end...

  14. GKIN: a tool for drawing genetic networks

    Directory of Open Access Journals (Sweden)

    Jonathan Arnold

    2012-03-01

    Full Text Available We present GKIN, a simulator and a comprehensive graphical interface where one can draw the model specification of reactions between hypothesized molecular participants in a gene regulatory and biochemical reaction network (or genetic network for short. The solver is written in C++ in a nearly platform independentmanner to simulate large ensembles of models, which can run on PCs, Macintoshes, and UNIX machines, and its graphical user interface is written in Java which can run as a standalone or WebStart application. The drawing capability for rendering a network significantly enhances the ease of use of other reaction network simulators, such as KINSOLVER (Aleman-Meza et al., 2009 and enforces a correct semantic specification of the network. In a usability study with novice users, drawing the network with GKIN was preferred and faster in comparison with entry with a dialog-box guided interface in COPASI (Hoops, et al., 2006 with no difference in error rates between GKIN and COPASI in specifying the network. GKIN is freely available at http://faculty.cs.wit.edu/~ldeligia/PROJECTS/GKIN/.

  15. BGen: A UML Behavior Network Generator Tool

    Science.gov (United States)

    Huntsberger, Terry; Reder, Leonard J.; Balian, Harry

    2010-01-01

    BGen software was designed for autogeneration of code based on a graphical representation of a behavior network used for controlling automatic vehicles. A common format used for describing a behavior network, such as that used in the JPL-developed behavior-based control system, CARACaS ["Control Architecture for Robotic Agent Command and Sensing" (NPO-43635), NASA Tech Briefs, Vol. 32, No. 10 (October 2008), page 40] includes a graph with sensory inputs flowing through the behaviors in order to generate the signals for the actuators that drive and steer the vehicle. A computer program to translate Unified Modeling Language (UML) Freeform Implementation Diagrams into a legacy C implementation of Behavior Network has been developed in order to simplify the development of C-code for behavior-based control systems. UML is a popular standard developed by the Object Management Group (OMG) to model software architectures graphically. The C implementation of a Behavior Network is functioning as a decision tree.

  16. Failure environment analysis tool applications

    Science.gov (United States)

    Pack, Ginger L.; Wadsworth, David B.

    1993-02-01

    Understanding risks and avoiding failure are daily concerns for the women and men of NASA. Although NASA's mission propels us to push the limits of technology, and though the risks are considerable, the NASA community has instilled within, the determination to preserve the integrity of the systems upon which our mission and, our employees lives and well-being depend. One of the ways this is being done is by expanding and improving the tools used to perform risk assessment. The Failure Environment Analysis Tool (FEAT) was developed to help engineers and analysts more thoroughly and reliably conduct risk assessment and failure analysis. FEAT accomplishes this by providing answers to questions regarding what might have caused a particular failure; or, conversely, what effect the occurrence of a failure might have on an entire system. Additionally, FEAT can determine what common causes could have resulted in other combinations of failures. FEAT will even help determine the vulnerability of a system to failures, in light of reduced capability. FEAT also is useful in training personnel who must develop an understanding of particular systems. FEAT facilitates training on system behavior, by providing an automated environment in which to conduct 'what-if' evaluation. These types of analyses make FEAT a valuable tool for engineers and operations personnel in the design, analysis, and operation of NASA space systems.

  17. Decision Analysis Tools for Volcano Observatories

    Science.gov (United States)

    Hincks, T. H.; Aspinall, W.; Woo, G.

    2005-12-01

    Staff at volcano observatories are predominantly engaged in scientific activities related to volcano monitoring and instrumentation, data acquisition and analysis. Accordingly, the academic education and professional training of observatory staff tend to focus on these scientific functions. From time to time, however, staff may be called upon to provide decision support to government officials responsible for civil protection. Recognizing that Earth scientists may have limited technical familiarity with formal decision analysis methods, specialist software tools that assist decision support in a crisis should be welcome. A review is given of two software tools that have been under development recently. The first is for probabilistic risk assessment of human and economic loss from volcanic eruptions, and is of practical use in short and medium-term risk-informed planning of exclusion zones, post-disaster response, etc. A multiple branch event-tree architecture for the software, together with a formalism for ascribing probabilities to branches, have been developed within the context of the European Community EXPLORIS project. The second software tool utilizes the principles of the Bayesian Belief Network (BBN) for evidence-based assessment of volcanic state and probabilistic threat evaluation. This is of practical application in short-term volcano hazard forecasting and real-time crisis management, including the difficult challenge of deciding when an eruption is over. An open-source BBN library is the software foundation for this tool, which is capable of combining synoptically different strands of observational data from diverse monitoring sources. A conceptual vision is presented of the practical deployment of these decision analysis tools in a future volcano observatory environment. Summary retrospective analyses are given of previous volcanic crises to illustrate the hazard and risk insights gained from use of these tools.

  18. Perancangan Network Monitoring Tools Menggunakan Autonomous Agent Java

    Directory of Open Access Journals (Sweden)

    Khurniawan Eko S

    2016-08-01

    Full Text Available Tugas pengelolaan jaringan yang dilakukan administrator jaringan diantaranya yaitu pengumpulan informasi resource jaringan yang tersedia. Teknologi SNMP (Simple Network Management Protocol memberikan fleksibilitas bagi administrator jaringan dalam mengatur network secara keseluruhan dari satu lokasi. Aplikasi Network Monitoring Tools berbasis Agent JAVA terdiri dari Master agent yang bertugas untuk melakukan management Request agent serta akses database. Request agent yang bertugas untuk melakukan pemantauan server yang mengimplementasi library SNMP4j dengan sistem multi-agent. Disisi interface, aplikasi Network Monitoring Tools menggunakan media web sebagai interface administrator sehingga dapat digunakan darimana saja  dan kapan saja.  Hasil dari penelitian ini memperlihatkan bahwa aplikasi yang dibuat bekerja sebagai Network Monitoring Tools mampu bekerja dengan persen error pada kisaran 0-18%. Selain itu Aplikasi ini menghasilkan tren pembacaan data server lebih stabil dan cepat dibandingkan dengan aplikasi Cacti. Hal ini didukung oleh kemampuan Request Agent yang mampu merespon tingkat beban kerja server yang di pantau.

  19. Dynamic Hurricane Data Analysis Tool

    Science.gov (United States)

    Knosp, Brian W.; Li, Peggy; Vu, Quoc A.

    2009-01-01

    A dynamic hurricane data analysis tool allows users of the JPL Tropical Cyclone Information System (TCIS) to analyze data over a Web medium. The TCIS software is described in the previous article, Tropical Cyclone Information System (TCIS) (NPO-45748). This tool interfaces with the TCIS database to pull in data from several different atmospheric and oceanic data sets, both observed by instruments. Users can use this information to generate histograms, maps, and profile plots for specific storms. The tool also displays statistical values for the user-selected parameter for the mean, standard deviation, median, minimum, and maximum values. There is little wait time, allowing for fast data plots over date and spatial ranges. Users may also zoom-in for a closer look at a particular spatial range. This is version 1 of the software. Researchers will use the data and tools on the TCIS to understand hurricane processes, improve hurricane forecast models and identify what types of measurements the next generation of instruments will need to collect.

  20. Mapping, Awareness, And Virtualization Network Administrator Training Tool Virtualization Module

    Science.gov (United States)

    2016-03-01

    AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL VIRTUALIZATION MODULE by Erik W. Berndt March 2016 Thesis Advisor: John Gibson...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MAPPING, AWARENESS, AND VIRTUALIZATION NETWORK ADMINISTRATOR TRAINING TOOL... VIRTUALIZATION MODULE 5. FUNDING NUMBERS 6. AUTHOR(S) Erik W. Berndt 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) Naval Postgraduate School

  1. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  2. Water Network Tool for Resilience (WNTR) User Manual -

    Science.gov (United States)

    The Water Network Tool for Resilience (WNTR) is a new Python package designed to simulate and analyze resilience of water distribution networks to a variety of disaster scenarios. WNTR can help water utilities to explore the capacity of their systems to handle disasters and gui...

  3. Developing security tools of WSN and WBAN networks applications

    CERN Document Server

    A M El-Bendary, Mohsen

    2015-01-01

    This book focuses on two of the most rapidly developing areas in wireless technology (WT) applications, namely, wireless sensors networks (WSNs) and wireless body area networks (WBANs). These networks can be considered smart applications of the recent WT revolutions. The book presents various security tools and scenarios for the proposed enhanced-security of WSNs, which are supplemented with numerous computer simulations. In the computer simulation section, WSN modeling is addressed using MATLAB programming language.

  4. Graphical Multiprocessing Analysis Tool (GMAT)

    Energy Technology Data Exchange (ETDEWEB)

    Seager, M.K.; Campbell, S.; Sikora, S.; Strout, R.; Zosel, M.

    1988-03-01

    The design and debugging of parallel programs is a difficult task due to the complex synchronization and data scoping issues involed. to aid the programmer in paralle code dvelopment we have developed two methodologies for the graphical display of execution of parallel codes. The Graphical Multiprocessing Analysis Tools (GMAT) consist of stategraph, which represents an inheritance tree of task states, and timeline, which represens task as flowing sequence of events. Information about the code can be displayed as the application runs (dynamic mode) or played back with time under user control (static mode). This document discusses the design and user interface issues involved in developing the parallel application display GMAT family. Also, we present an introductory user's guide for both tools. 4 figs.

  5. Stability analysis using SDSA tool

    Science.gov (United States)

    Goetzendorf-Grabowski, Tomasz; Mieszalski, Dawid; Marcinkiewicz, Ewa

    2011-11-01

    The SDSA (Simulation and Dynamic Stability Analysis) application is presented as a tool for analysing the dynamic characteristics of the aircraft just in the conceptual design stage. SDSA is part of the CEASIOM (Computerized Environment for Aircraft Synthesis and Integrated Optimization Methods) software environment which was developed within the SimSAC (Simulating Aircraft Stability And Control Characteristics for Use in Conceptual Design) project, funded by the European Commission 6th Framework Program. SDSA can also be used as stand alone software, and integrated with other design and optimisation systems using software wrappers. This paper focuses on the main functionalities of SDSA and presents both computational and free flight experimental results to compare and validate the presented software. Two aircraft are considered, the EADS Ranger 2000 and the Warsaw University designed PW-6 glider. For the two cases considered here the SDSA software is shown to be an excellent tool for predicting dynamic characteristics of an aircraft.

  6. Extending Stochastic Network Calculus to Loss Analysis

    Directory of Open Access Journals (Sweden)

    Chao Luo

    2013-01-01

    Full Text Available Loss is an important parameter of Quality of Service (QoS. Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor.

  7. Computer-mediated-communication and social networking tools at work

    NARCIS (Netherlands)

    Ou, C.X.J.; Sia, C.L.; Hui, C.K.

    2013-01-01

    Purpose – Advances in information technology (IT) have resulted in the development of various computer‐mediated communication (CMC) and social networking tools. However, quantifying the benefits of utilizing these tools in the organizational context remains a challenge. In this study, the authors

  8. Social network analysis for program implementation.

    Science.gov (United States)

    Valente, Thomas W; Palinkas, Lawrence A; Czaja, Sara; Chu, Kar-Hai; Brown, C Hendricks

    2015-01-01

    This paper introduces the use of social network analysis theory and tools for implementation research. The social network perspective is useful for understanding, monitoring, influencing, or evaluating the implementation process when programs, policies, practices, or principles are designed and scaled up or adapted to different settings. We briefly describe common barriers to implementation success and relate them to the social networks of implementation stakeholders. We introduce a few simple measures commonly used in social network analysis and discuss how these measures can be used in program implementation. Using the four stage model of program implementation (exploration, adoption, implementation, and sustainment) proposed by Aarons and colleagues [1] and our experience in developing multi-sector partnerships involving community leaders, organizations, practitioners, and researchers, we show how network measures can be used at each stage to monitor, intervene, and improve the implementation process. Examples are provided to illustrate these concepts. We conclude with expected benefits and challenges associated with this approach.

  9. Advantages of Social Network Analysis in Educational Research

    Science.gov (United States)

    Ushakov, K. M.; Kukso, K. N.

    2015-01-01

    Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…

  10. Optimizing the ASC WAN: evaluating network performance tools for comparing transport protocols.

    Energy Technology Data Exchange (ETDEWEB)

    Lydick, Christopher L.

    2007-07-01

    The Advanced Simulation & Computing Wide Area Network (ASC WAN), which is a high delay-bandwidth network connection between US Department of Energy National Laboratories, is constantly being examined and evaluated for efficiency. One of the current transport-layer protocols which is used, TCP, was developed for traffic demands which are different from that on the ASC WAN. The Stream Control Transport Protocol (SCTP), on the other hand, has shown characteristics which make it more appealing to networks such as these. Most important, before considering a replacement for TCP on any network, a testing tool that performs well against certain criteria needs to be found. In order to try to find such a tool, two popular networking tools (Netperf v.2.4.3 & v.2.4.6 (OpenSS7 STREAMS), and Iperf v.2.0.6) were tested. These tools implement both TCP and SCTP and were evaluated using four metrics: (1) How effectively can the tool reach a throughput near the bandwidth? (2) How much of the CPU does the tool utilize during operation? (3) Is the tool freely and widely available? And, (4) Is the tool actively developed? Following the analysis of those tools, this paper goes further into explaining some recommendations and ideas for future work.

  11. Methodologies and techniques for analysis of network flow data

    Energy Technology Data Exchange (ETDEWEB)

    Bobyshev, A.; Grigoriev, M.; /Fermilab

    2004-12-01

    Network flow data gathered at the border routers and core switches is used at Fermilab for statistical analysis of traffic patterns, passive network monitoring, and estimation of network performance characteristics. Flow data is also a critical tool in the investigation of computer security incidents. Development and enhancement of flow based tools is an on-going effort. This paper describes the most recent developments in flow analysis at Fermilab.

  12. Network Analysis, Architecture, and Design

    CERN Document Server

    McCabe, James D

    2007-01-01

    Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua

  13. Navy Network Dependability: Models, Metrics, and Tools

    Science.gov (United States)

    2010-01-01

    surveillance; TCDL = Tactical Common Data Link; UHF = ultra high frequency; UFO = ultra-high-frequency follow-on; WGS = Wideband Gapfiller Satellite. RAND...VOICE (DMR VALUES) UFO OE-82 UHF LOS VOICE (DMR VALUES) UHF SATCOM VOICE DMR UHF LOS VOICE DMR TVs ADMS KIV-7 COMSEC ADNS SW ADNS II HW ISNS SW ISNS HW...Data Link; UHF = ultra high frequency; UFO = ultra-high-frequency follow-on; WGS = Wideband Gapfiller Satellite. RAND MG1003-1.1 4 Navy Network

  14. A Mobile Network Planning Tool Based on Data Analytics

    Directory of Open Access Journals (Sweden)

    Jessica Moysen

    2017-01-01

    Full Text Available Planning future mobile networks entails multiple challenges due to the high complexity of the network to be managed. Beyond 4G and 5G networks are expected to be characterized by a high densification of nodes and heterogeneity of layers, applications, and Radio Access Technologies (RAT. In this context, a network planning tool capable of dealing with this complexity is highly convenient. The objective is to exploit the information produced by and already available in the network to properly deploy, configure, and optimise network nodes. This work presents such a smart network planning tool that exploits Machine Learning (ML techniques. The proposed approach is able to predict the Quality of Service (QoS experienced by the users based on the measurement history of the network. We select Physical Resource Block (PRB per Megabit (Mb as our main QoS indicator to optimise, since minimizing this metric allows offering the same service to users by consuming less resources, so, being more cost-effective. Two cases of study are considered in order to evaluate the performance of the proposed scheme, one to smartly plan the small cell deployment in a dense indoor scenario and a second one to timely face a detected fault in a macrocell network.

  15. Collaboration tools for the global accelerator network: Workshop Report

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deborah [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Olson, Gary [Univ. of Michigan, Ann Arbor, MI (United States); Olson, Judy [Univ. of Michigan, Ann Arbor, MI (United States)

    2002-09-15

    The concept of a ''Global Accelerator Network'' (GAN) has been put forward as a means for inter-regional collaboration in the operation of internationally constructed and operated frontier accelerator facilities. A workshop was held to allow representatives of the accelerator community and of the collaboratory development community to meet and discuss collaboration tools for the GAN environment. This workshop, called the Collaboration Tools for the Global Accelerator Network (GAN) Workshop, was held on August 26, 2002 at Lawrence Berkeley National Laboratory. The goal was to provide input about collaboration tools in general and to provide a strawman for the GAN collaborative tools environment. The participants at the workshop represented accelerator physicists, high-energy physicists, operations, technology tool developers, and social scientists that study scientific collaboration.

  16. MCF: a tool to find multi-scale community profiles in biological networks.

    Science.gov (United States)

    Gao, Shang; Chen, Alan; Rahmani, Ali; Jarada, Tamer; Alhajj, Reda; Demetrick, Doug; Zeng, Jia

    2013-12-01

    Recent developments of complex graph clustering methods have implicated the practical applications with biological networks in different settings. Multi-scale Community Finder (MCF) is a tool to profile network communities (i.e., clusters of nodes) with the control of community sizes. The controlling parameter is referred to as the scale of the network community profile. MCF is able to find communities in all major types of networks including directed, signed, bipartite, and multi-slice networks. The fast computation promotes the practicability of the tool for large-scaled analysis (e.g., protein-protein interaction and gene co-expression networks). MCF is distributed as an open-source C++ package for academic use with both command line and user interface options, and can be downloaded at http://bsdxd.cpsc.ucalgary.ca/MCF. Detailed user manual and sample data sets are also available at the project website. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  17. Constructing an Intelligent Patent Network Analysis Method

    Directory of Open Access Journals (Sweden)

    Chao-Chan Wu

    2012-11-01

    Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.

  18. 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.

  19. General Mission Analysis Tool (GMAT)

    Science.gov (United States)

    Hughes, Steven P. (Compiler)

    2016-01-01

    This is a software tutorial and presentation demonstrating the application of the General Mission Analysis Tool (GMAT) to the critical design phase of NASA missions. The demonstration discusses GMAT basics, then presents a detailed example of GMAT application to the Transiting Exoplanet Survey Satellite (TESS) mission. Other examples include OSIRIS-Rex. This talk is a combination of existing presentations; a GMAT basics and overview, and technical presentations from the TESS and OSIRIS-REx projects on their application of GMAT to critical mission design. The GMAT basics slides are taken from the open source training material. The OSIRIS-REx slides are from a previous conference presentation. The TESS slides are a streamlined version of the CDR package provided by the project with SBU and ITAR data removed by the TESS project.

  20. The nitrogen footprint tool network: a multi-institution program ...

    Science.gov (United States)

    Anthropogenic sources of reactive nitrogen have local and global impacts on air and water quality and detrimental effects on human and ecosystem health. This paper uses the nitrogen footprint tool (NFT) to determine the amount of nitrogen (N) released as a result of institutional consumption. The sectors accounted for include food (consumption and the upstream production), energy, transportation, fertilizer, research animals, and agricultural research. The NFT is then used for scenario analysis to manage and track reductions to institution N footprints, which are driven by the consumption behaviors of both the institution itself and its constituent individuals. In this paper, the first seven institution N footprint results are presented. The institution NFT network aims to develop footprints for many institutions to encourage widespread upper-level management strategies that will create significant reductions in reactive N released to the environment. Energy use and food purchases are the two largest contributors to institution N footprints. Ongoing efforts by institutions to reduce greenhouse gas emissions also help to reduce the N footprint, but the impact of food production on N pollution has not been directly addressed by the higher-ed sustainability community. The NFT Network found that institutions could reduce their N footprints by optimizing food purchasing to reduce consumption of animal products and minimize food waste, as well as reducing dependence o

  1. Web based educational tool for neural network robot control

    Directory of Open Access Journals (Sweden)

    Jure Čas

    2007-05-01

    Full Text Available Abstract— This paper describes the application for teleoperations of the SCARA robot via the internet. The SCARA robot is used by students of mehatronics at the University of Maribor as a remote educational tool. The developed software consists of two parts i.e. the continuous neural network sliding mode controller (CNNSMC and the graphical user interface (GUI. Application is based on two well-known commercially available software packages i.e. MATLAB/Simulink and LabVIEW. Matlab/Simulink and the DSP2 Library for Simulink are used for control algorithm development, simulation and executable code generation. While this code is executing on the DSP-2 Roby controller and through the analog and digital I/O lines drives the real process, LabVIEW virtual instrument (VI, running on the PC, is used as a user front end. LabVIEW VI provides the ability for on-line parameter tuning, signal monitoring, on-line analysis and via Remote Panels technology also teleoperation. The main advantage of a CNNSMC is the exploitation of its self-learning capability. When friction or an unexpected impediment occurs for example, the user of a remote application has no information about any changed robot dynamic and thus is unable to dispatch it manually. This is not a control problem anymore because, when a CNNSMC is used, any approximation of changed robot dynamic is estimated independently of the remote’s user. Index Terms—LabVIEW; Matlab/Simulink; Neural network control; remote educational tool; robotics

  2. Vulnerability Assessment Tools for Complex Information Networks

    Science.gov (United States)

    2006-11-14

    Panayiotou, C.G., "Perturbation Analysis of a Multiclass Stochastic Fluid Model with Finite Buffer Capacity ", Proc. of 41st IEEE Conf. Decision and...October 2002. 3. Sun, G., Cassandras, C.G., and Panayiotou, C.G., "Perturbation Analysis of a Multiclass Stochastic Fluid Model with Finite Buffer ... Capacity ", Proc. of 41st IEEE Conf. Decision and Control, pp. 2171-2176, Dec. 2002. 4. Cassandras, C.G., and Mookherjee, R., "Receding Horizon Control

  3. GraphCrunch 2: Software tool for network modeling, alignment and clustering.

    Science.gov (United States)

    Kuchaiev, Oleksii; Stevanović, Aleksandar; Hayes, Wayne; Pržulj, Nataša

    2011-01-19

    Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI) data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL") for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other existing tool. Finally, GraphCruch 2 implements an

  4. GraphCrunch 2: Software tool for network modeling, alignment and clustering

    Directory of Open Access Journals (Sweden)

    Hayes Wayne

    2011-01-01

    Full Text Available Abstract Background Recent advancements in experimental biotechnology have produced large amounts of protein-protein interaction (PPI data. The topology of PPI networks is believed to have a strong link to their function. Hence, the abundance of PPI data for many organisms stimulates the development of computational techniques for the modeling, comparison, alignment, and clustering of networks. In addition, finding representative models for PPI networks will improve our understanding of the cell just as a model of gravity has helped us understand planetary motion. To decide if a model is representative, we need quantitative comparisons of model networks to real ones. However, exact network comparison is computationally intractable and therefore several heuristics have been used instead. Some of these heuristics are easily computable "network properties," such as the degree distribution, or the clustering coefficient. An important special case of network comparison is the network alignment problem. Analogous to sequence alignment, this problem asks to find the "best" mapping between regions in two networks. It is expected that network alignment might have as strong an impact on our understanding of biology as sequence alignment has had. Topology-based clustering of nodes in PPI networks is another example of an important network analysis problem that can uncover relationships between interaction patterns and phenotype. Results We introduce the GraphCrunch 2 software tool, which addresses these problems. It is a significant extension of GraphCrunch which implements the most popular random network models and compares them with the data networks with respect to many network properties. Also, GraphCrunch 2 implements the GRAph ALigner algorithm ("GRAAL" for purely topological network alignment. GRAAL can align any pair of networks and exposes large, dense, contiguous regions of topological and functional similarities far larger than any other

  5. Three-Phase Unbalanced Load Flow Tool for Distribution Networks

    DEFF Research Database (Denmark)

    Demirok, Erhan; Kjær, Søren Bækhøj; Sera, Dezso

    2012-01-01

    This work develops a three-phase unbalanced load flow tool tailored for radial distribution networks based on Matlab®. The tool can be used to assess steady-state voltage variations, thermal limits of grid components and power losses in radial MV-LV networks with photovoltaic (PV) generators where...... most of the systems are single phase. New ancillary service such as static reactive power support by PV inverters can be also merged together with the load flow solution tool and thus, the impact of the various reactive power control strategies on the steady-state grid operation can be simply...... investigated. Performance of the load flow solution tool in the sense of resulting bus voltage magnitudes is compared and validated with IEEE 13-bus test feeder....

  6. Passive Fingerprinting Of Computer Network Reconnaissance Tools

    Science.gov (United States)

    2009-09-01

    Fingerprint Summary When reviewing the different data captures for analysis, it was noted that one of the early default Nmap captures had...INTENTIONALLY LEFT BLANK xi LIST OF TABLES Table 1. Nmap (root) Fingerprint Summary... Fingerprint Summary ..................................51 Table 8. CDX Probable Nmap Scan Summary

  7. A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis

    Directory of Open Access Journals (Sweden)

    José Alberto Benítez

    2017-01-01

    Full Text Available There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data.

  8. A Web-Based Tool for Automatic Data Collection, Curation, and Visualization of Complex Healthcare Survey Studies including Social Network Analysis.

    Science.gov (United States)

    Benítez, José Alberto; Labra, José Emilio; Quiroga, Enedina; Martín, Vicente; García, Isaías; Marqués-Sánchez, Pilar; Benavides, Carmen

    2017-01-01

    There is a great concern nowadays regarding alcohol consumption and drug abuse, especially in young people. Analyzing the social environment where these adolescents are immersed, as well as a series of measures determining the alcohol abuse risk or personal situation and perception using a number of questionnaires like AUDIT, FAS, KIDSCREEN, and others, it is possible to gain insight into the current situation of a given individual regarding his/her consumption behavior. But this analysis, in order to be achieved, requires the use of tools that can ease the process of questionnaire creation, data gathering, curation and representation, and later analysis and visualization to the user. This research presents the design and construction of a web-based platform able to facilitate each of the mentioned processes by integrating the different phases into an intuitive system with a graphical user interface that hides the complexity underlying each of the questionnaires and techniques used and presenting the results in a flexible and visual way, avoiding any manual handling of data during the process. Advantages of this approach are shown and compared to the previous situation where some of the tasks were accomplished by time consuming and error prone manipulations of data.

  9. Tourism Destinations Network Analysis, Social Network Analysis Approach

    Directory of Open Access Journals (Sweden)

    2015-09-01

    Full Text Available The tourism industry is becoming one of the world's largest economical sources, and is expected to become the world's first industry by 2020. Previous studies have focused on several aspects of this industry including sociology, geography, tourism management and development, but have paid less attention to analytical and quantitative approaches. This study introduces some network analysis techniques and measures aiming at studying the structural characteristics of tourism networks. More specifically, it presents a methodology to analyze tourism destinations network. We apply the methodology to analyze mazandaran’s Tourism destination network, one of the most famous tourism areas of Iran.

  10. Introduction to Social Network Analysis

    Science.gov (United States)

    Zaphiris, Panayiotis; Ang, Chee Siang

    Social Network analysis focuses on patterns of relations between and among people, organizations, states, etc. It aims to describe networks of relations as fully as possible, identify prominent patterns in such networks, trace the flow of information through them, and discover what effects these relations and networks have on people and organizations. Social network analysis offers a very promising potential for analyzing human-human interactions in online communities (discussion boards, newsgroups, virtual organizations). This Tutorial provides an overview of this analytic technique and demonstrates how it can be used in Human Computer Interaction (HCI) research and practice, focusing especially on Computer Mediated Communication (CMC). This topic acquires particular importance these days, with the increasing popularity of social networking websites (e.g., youtube, myspace, MMORPGs etc.) and the research interest in studying them.

  11. System analysis: Developing tools for the future

    Energy Technology Data Exchange (ETDEWEB)

    De Jong, K.; clever, J.; Draper, J.V.; Davies, B.; Lonks, A.

    1996-02-01

    This report introduces and evaluates system analysis tools that were developed, or are under development, for the Robotics Technology Development Program (RTDP). Additionally, it discusses system analysis work completed using these tools aimed at completing a system analysis of the retrieval of waste from underground storage tanks on the Hanford Reservation near Richland, Washington. The tools developed and evaluated include a mixture of commercially available tools adapted to RTDP requirements, and some tools developed in house. The tools that are included in this report include: a Process Diagramming Tool, a Cost Modeling Tool, an Amortization Modeling Tool, a graphical simulation linked to the Cost Modeling Tool, a decision assistance tool, and a system thinking tool. Additionally, the importance of performance testing to the RTDP and the results of such testing executed is discussed. Further, the results of the Tank Waste Retrieval (TWR) System Diagram, the TWR Operations Cost Model, and the TWR Amortization Model are presented, and the implication of the results are discussed. Finally, the RTDP system analysis tools are assessed and some recommendations are made regarding continuing development of the tools and process.

  12. Network Security Hacks Tips & Tools for Protecting Your Privacy

    CERN Document Server

    Lockhart, Andrew

    2009-01-01

    This second edition of Network Security Hacks offers 125 concise and practical hacks, including more information for Windows administrators, hacks for wireless networking (such as setting up a captive portal and securing against rogue hotspots), and techniques to ensure privacy and anonymity, including ways to evade network traffic analysis, encrypt email and files, and protect against phishing attacks. System administrators looking for reliable answers will also find concise examples of applied encryption, intrusion detection, logging, trending, and incident response.

  13. Novel Screening Tool for Stroke Using Artificial Neural Network.

    Science.gov (United States)

    Abedi, Vida; Goyal, Nitin; Tsivgoulis, Georgios; Hosseinichimeh, Niyousha; Hontecillas, Raquel; Bassaganya-Riera, Josep; Elijovich, Lucas; Metter, Jeffrey E; Alexandrov, Anne W; Liebeskind, David S; Alexandrov, Andrei V; Zand, Ramin

    2017-06-01

    The timely diagnosis of stroke at the initial examination is extremely important given the disease morbidity and narrow time window for intervention. The goal of this study was to develop a supervised learning method to recognize acute cerebral ischemia (ACI) and differentiate that from stroke mimics in an emergency setting. Consecutive patients presenting to the emergency department with stroke-like symptoms, within 4.5 hours of symptoms onset, in 2 tertiary care stroke centers were randomized for inclusion in the model. We developed an artificial neural network (ANN) model. The learning algorithm was based on backpropagation. To validate the model, we used a 10-fold cross-validation method. A total of 260 patients (equal number of stroke mimics and ACIs) were enrolled for the development and validation of our ANN model. Our analysis indicated that the average sensitivity and specificity of ANN for the diagnosis of ACI based on the 10-fold cross-validation analysis was 80.0% (95% confidence interval, 71.8-86.3) and 86.2% (95% confidence interval, 78.7-91.4), respectively. The median precision of ANN for the diagnosis of ACI was 92% (95% confidence interval, 88.7-95.3). Our results show that ANN can be an effective tool for the recognition of ACI and differentiation of ACI from stroke mimics at the initial examination. © 2017 American Heart Association, Inc.

  14. Functional stoichiometric analysis of metabolic networks.

    Science.gov (United States)

    Urbanczik, R; Wagner, C

    2005-11-15

    An important tool in Systems Biology is the stoichiometric modeling of metabolic networks, where the stationary states of the network are described by a high-dimensional polyhedral cone, the so-called flux cone. Exhaustive descriptions of the metabolism can be obtained by computing the elementary vectors of this cone but, owing to a combinatorial explosion of the number of elementary vectors, this approach becomes computationally intractable for genome scale networks. Hence, we propose to instead focus on the conversion cone, a projection of the flux cone, which describes the interaction of the metabolism with its external chemical environment. We present a direct method for calculating the elementary vectors of this cone and, by studying the metabolism of Saccharomyces cerevisiae, we demonstrate that such an analysis is computationally feasible even for genome scale networks.

  15. An Automated Data Analysis Tool for Livestock Market Data

    Science.gov (United States)

    Williams, Galen S.; Raper, Kellie Curry

    2011-01-01

    This article describes an automated data analysis tool that allows Oklahoma Cooperative Extension Service educators to disseminate results in a timely manner. Primary data collected at Oklahoma Quality Beef Network (OQBN) certified calf auctions across the state results in a large amount of data per sale site. Sale summaries for an individual sale…

  16. Sustainability Tools Inventory - Initial Gaps Analysis | Science ...

    Science.gov (United States)

    This report identifies a suite of tools that address a comprehensive set of community sustainability concerns. The objective is to discover whether "gaps" exist in the tool suite’s analytic capabilities. These tools address activities that significantly influence resource consumption, waste generation, and hazard generation including air pollution and greenhouse gases. In addition, the tools have been evaluated using four screening criteria: relevance to community decision making, tools in an appropriate developmental stage, tools that may be transferrable to situations useful for communities, and tools with requiring skill levels appropriate to communities. This document provides an initial gap analysis in the area of community sustainability decision support tools. It provides a reference to communities for existing decision support tools, and a set of gaps for those wishing to develop additional needed tools to help communities to achieve sustainability. It contributes to SHC 1.61.4

  17. Social Network Analysis with sna

    Directory of Open Access Journals (Sweden)

    Carter T. Butts

    2007-12-01

    Full Text Available Modern social network analysis---the analysis of relational data arising from social systems---is a computationally intensive area of research. Here, we provide an overview of a software package which provides support for a range of network analytic functionality within the R statistical computing environment. General categories of currently supported functionality are described, and brief examples of package syntax and usage are shown.

  18. Computational Social Network Analysis

    CERN Document Server

    Hassanien, Aboul-Ella

    2010-01-01

    Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks

  19. Multifractal analysis of mobile social networks

    Science.gov (United States)

    Zheng, Wei; Zhang, Zifeng; Deng, Yufan

    2017-09-01

    As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

  20. Harmonization of European Laboratory Response networks by implementing CWA 15793: Use of a gap analysis and an "insider" exercise as tools

    NARCIS (Netherlands)

    Sundqvist, B.; Allard Bengtsson, U.; Wisselink, H.J.; Peeters, B.P.H.; Rotterdam, van B.; Kampert, E.; Bereczky, S.; Olsson, N.G.J.; Szekely Björndal, A.; Zini, S.; Allix, S.; Knutsson, R.

    2013-01-01

    Laboratory response networks (LRNs) have been established for security reasons in several countries including the Netherlands, France, and Sweden. LRNs function in these countries as a preparedness measure for a coordinated diagnostic response capability in case of a bioterrorism incident or other

  1. Topological analysis of telecommunications networks

    Directory of Open Access Journals (Sweden)

    Milojko V. Jevtović

    2011-01-01

    Full Text Available A topological analysis of the structure of telecommunications networks is a very interesting topic in the network research, but also a key issue in their design and planning. Satisfying multiple criteria in terms of locations of switching nodes as well as their connectivity with respect to the requests for capacity, transmission speed, reliability, availability and cost are the main research objectives. There are three ways of presenting the topology of telecommunications networks: table, matrix or graph method. The table method is suitable for a network of a relatively small number of nodes in relation to the number of links. The matrix method involves the formation of a connection matrix in which its columns present source traffic nodes and its rows are the switching systems that belong to the destination. The method of the topology graph means that the network nodes are connected via directional or unidirectional links. We can thus easily analyze the structural parameters of telecommunications networks. This paper presents the mathematical analysis of the star-, ring-, fully connected loop- and grid (matrix-shaped topology as well as the topology based on the shortest path tree. For each of these topologies, the expressions for determining the number of branches, the middle level of reliability, the medium length and the average length of the link are given in tables. For the fully connected loop network with five nodes the values of all topological parameters are calculated. Based on the topological parameters, the relationships that represent integral and distributed indicators of reliability are given in this work as well as the values of the particular network. The main objectives of the topology optimization of telecommunications networks are: achieving the minimum complexity, maximum capacity, the shortest path message transfer, the maximum speed of communication and maximum economy. The performance of telecommunications networks is

  2. General Mission Analysis Tool (GMAT) Mathematical Specifications

    Science.gov (United States)

    Hughes, Steve

    2007-01-01

    The General Mission Analysis Tool (GMAT) is a space trajectory optimization and mission analysis system developed by NASA and private industry in the spirit of the NASA Mission. GMAT contains new technology and is a testbed for future technology development.

  3. Multi-mission telecom analysis tool

    Science.gov (United States)

    Hanks, D.; Kordon, M.; Baker, J.

    2002-01-01

    In the early formulation phase of a mission it is critically important to have fast, easy to use, easy to integrate space vehicle subsystem analysis tools so that engineers can rapidly perform trade studies not only by themselves but in coordination with other subsystem engineers as well. The Multi-Mission Telecom Analysis Tool (MMTAT) is designed for just this purpose.

  4. Rahnuma: hypergraph-based tool for metabolic pathway prediction and network comparison.

    Science.gov (United States)

    Mithani, Aziz; Preston, Gail M; Hein, Jotun

    2009-07-15

    We present a tool called Rahnuma for prediction and analysis of metabolic pathways and comparison of metabolic networks. Rahnuma represents metabolic networks as hypergraphs and computes all possible pathways between two or more metabolites. It provides an intuitive way to answer biological ques- tions focusing on differences between organisms or the evolution of different species by allowing pathway-based metabolic network comparisons at an organism as well as at a phylogenetic level. Rahnuma is available online at http://portal.stats.ox.ac.uk:8080/rahnuma/.

  5. Enhancing the Understanding of Computer Networking Courses through Software Tools

    OpenAIRE

    Dafalla, Z. I.; Balaji, R. D.

    2015-01-01

    Computer networking is an important specialization in Information and Communication Technologies. However imparting the right knowledge to students can be a challenging task due to the fact that there is not enough time to deliver lengthy labs during normal lecture hours. Augmenting the use of physical machines with software tools help the students to learn beyond the limited lab sessions within the environment of higher Institutions of learning throughout the world. The Institutions focus mo...

  6. RTOL: design and implementation of an network equipment testing tool

    Energy Technology Data Exchange (ETDEWEB)

    Lee, J.Y.; Kim, H.J.; Kim, B.S.; Park, K.H.; An, S.S [Korea University, Seoul (Korea, Republic of); Choi, H.S.; Yu, S.H. [Samsung Electronics, Suwon (Korea, Republic of)

    1997-11-01

    As the infrastructure of information communication network becomes larger and more complicated, many network equipment are being developed. To verify the reliability of such equipment, many test methods have been proposed. But those require a lot of cost and efforts. In this paper, we designed and implemented a test tool, called RTOL(Router Testing command Language system), to verify the functions of network equipment, especially router. RTOL can be used to test OSPF, Appletalk, DecNet, as well as IP and supports the functions of SNMP manager. By using the virtual router functions of RTOL, we can operate many virtual routers with only one router. Finally, we present test results of specific routers by using RTOL. (author). 17 refs., 8 figs., 5 tabs.

  7. Analysis of neural networks

    CERN Document Server

    Heiden, Uwe

    1980-01-01

    The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica­ ted throughout the text. However, they are not explored in de­ tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev­ els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be­ havior of neurons or neuron pools. In this respect the essay is writt...

  8. Neural Networks as a Tool for Georadar Data Processing

    Directory of Open Access Journals (Sweden)

    Szymczyk Piotr

    2015-12-01

    Full Text Available In this article a new neural network based method for automatic classification of ground penetrating radar (GPR traces is proposed. The presented approach is based on a new representation of GPR signals by polynomials approximation. The coefficients of the polynomial (the feature vector are neural network inputs for automatic classification of a special kind of geologic structure—a sinkhole. The analysis and results show that the classifier can effectively distinguish sinkholes from other geologic structures.

  9. Neuronmaster: an integrated tool for applications in neural networks

    Science.gov (United States)

    Rivas-Echeverria, Francklin; Colina-Morles, Eliezer; Sole, Solazver; Perez-Mendez, Anna; Bravo-Bravo, Cesar; Bravo-Bravo, Victor

    2001-03-01

    This work presents the design of an integral environment for the suitable development of neural networks applications. The integrated environment contemplates the following features: A data processing module which encompasses statistical data analysis techniques for variables selection reduction, a variety of learning algorithms, code generator for different computer languages to enable network implementation, a learning sessions planning module and database connectivity facilities via ODBC, RPC, and API.

  10. Mathematical Analysis of Urban Spatial Networks

    CERN Document Server

    Blanchard, Philippe

    2009-01-01

    Cities can be considered to be among the largest and most complex artificial networks created by human beings. Due to the numerous and diverse human-driven activities, urban network topology and dynamics can differ quite substantially from that of natural networks and so call for an alternative method of analysis. The intent of the present monograph is to lay down the theoretical foundations for studying the topology of compact urban patterns, using methods from spectral graph theory and statistical physics. These methods are demonstrated as tools to investigate the structure of a number of real cities with widely differing properties: medieval German cities, the webs of city canals in Amsterdam and Venice, and a modern urban structure such as found in Manhattan. Last but not least, the book concludes by providing a brief overview of possible applications that will eventually lead to a useful body of knowledge for architects, urban planners and civil engineers.

  11. Intentional risk management through complex networks analysis

    CERN Document Server

    Chapela, Victor; Moral, Santiago; Romance, Miguel

    2015-01-01

    This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution,  the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained  in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies a...

  12. Statistical network analysis for analyzing policy networks

    DEFF Research Database (Denmark)

    Robins, Garry; Lewis, Jenny; Wang, Peng

    2012-01-01

    To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social...... 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...

  13. SURFmap: A Network Monitoring Tool Based on the Google Maps API

    NARCIS (Netherlands)

    Hofstede, R.J.; Hofstede, R. J.; Fioreze, Tiago

    2009-01-01

    Network monitoring allows network managers to get a better insight in the network traffic transiting in a managed network. In order to make the tasks of a network manager easier, many network monitoring tools are made available for a wide range of purposes (e.g., traffic accounting, performance

  14. Tools for occupant protection analysis

    NARCIS (Netherlands)

    Slaats, P.M.A.; Lee, W.; Babu, V.; Thomson, K.R.

    2001-01-01

    The design of occupant restraint systems in the automotive industry has shifted from an empirical approach to a computer-aided analysis approach for many years now. Various finite element software programs have been applied in crash safety analysis, and multi-body dynamics codes have been

  15. Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks.

    Science.gov (United States)

    Castet, Jean-Francois; Saleh, Joseph H

    2013-01-01

    This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs) allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats) of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also examined, and the

  16. Interdependent multi-layer networks: modeling and survivability analysis with applications to space-based networks.

    Directory of Open Access Journals (Sweden)

    Jean-Francois Castet

    Full Text Available This article develops a novel approach and algorithmic tools for the modeling and survivability analysis of networks with heterogeneous nodes, and examines their application to space-based networks. Space-based networks (SBNs allow the sharing of spacecraft on-orbit resources, such as data storage, processing, and downlink. Each spacecraft in the network can have different subsystem composition and functionality, thus resulting in node heterogeneity. Most traditional survivability analyses of networks assume node homogeneity and as a result, are not suited for the analysis of SBNs. This work proposes that heterogeneous networks can be modeled as interdependent multi-layer networks, which enables their survivability analysis. The multi-layer aspect captures the breakdown of the network according to common functionalities across the different nodes, and it allows the emergence of homogeneous sub-networks, while the interdependency aspect constrains the network to capture the physical characteristics of each node. Definitions of primitives of failure propagation are devised. Formal characterization of interdependent multi-layer networks, as well as algorithmic tools for the analysis of failure propagation across the network are developed and illustrated with space applications. The SBN applications considered consist of several networked spacecraft that can tap into each other's Command and Data Handling subsystem, in case of failure of its own, including the Telemetry, Tracking and Command, the Control Processor, and the Data Handling sub-subsystems. Various design insights are derived and discussed, and the capability to perform trade-space analysis with the proposed approach for various network characteristics is indicated. The select results here shown quantify the incremental survivability gains (with respect to a particular class of threats of the SBN over the traditional monolith spacecraft. Failure of the connectivity between nodes is also

  17. Advanced functional network analysis in the geosciences: The pyunicorn package

    Science.gov (United States)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  18. VALIDERING AV VERKTYGET "ENTERPRISE ARCHITECTURE ANALYSIS TOOL"

    OpenAIRE

    Österlind, Magnus

    2011-01-01

    The Enterprise Architecture Analysis Tool, EAAT, is a software tool developed by the department of Industrial Information- and Control systems, ICS, at the Royal Institute of Technology, Stockholm, Sweden. EAAT is a modeling tool that combines Enterprise Architecture (EA) modeling with probabilistic relational modeling. Therefore EAAT makes it possible to design, describe and analyze the organizational structure, business processes, information systems and infrastructure within an enterprise....

  19. Benefits and Pitfalls: Simple Guidelines for the Use of Social Networking Tools in K-12 Education

    Science.gov (United States)

    Huffman, Stephanie

    2013-01-01

    The article will outline a framework for the use of social networking tools in K-12 education framed around four thought provoking questions: 1) what are the benefits and pitfalls of using social networking tools in P-12 education, 2) how do we plan effectively for the use of social networking tool, 3) what role does professional development play…

  20. Social Networking Tools and Teacher Education Learning Communities: A Case Study

    Science.gov (United States)

    Poulin, Michael T.

    2014-01-01

    Social networking tools have become an integral part of a pre-service teacher's educational experience. As a result, the educational value of social networking tools in teacher preparation programs must be examined. The specific problem addressed in this study is that the role of social networking tools in teacher education learning communities…

  1. netview p: a network visualization tool to unravel complex population structure using genome-wide SNPs.

    Science.gov (United States)

    Steinig, Eike J; Neuditschko, Markus; Khatkar, Mehar S; Raadsma, Herman W; Zenger, Kyall R

    2016-01-01

    Network-based approaches are emerging as valuable tools for the analysis of complex genetic structure in wild and captive populations. netview p combines data quality control with the construction of population networks through mutual k-nearest neighbours thresholds applied to genome-wide SNPs. The program is cross-platform compatible, open-source and efficiently operates on data ranging from hundreds to hundreds of thousands of SNPs. The pipeline was used for the analysis of pedigree data from simulated (n = 750, SNPs = 1279) and captive silver-lipped pearl oysters (n = 415, SNPs = 1107), wild populations of the European hake from the Atlantic and Mediterranean (n = 834, SNPs = 380) and grey wolves from North America (n = 239, SNPs = 78 255). The population networks effectively visualize large- and fine-scale genetic structure within and between populations, including family-level structure and relationships. netview p comprises a network-based addition to other population analysis tools and provides user-friendly access to a complex network analysis pipeline through implementation in python. © 2015 John Wiley & Sons Ltd.

  2. Data Farming Process and Initial Network Analysis Capabilities

    Directory of Open Access Journals (Sweden)

    Gary Horne

    2016-01-01

    Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.

  3. 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

  4. Quick Spacecraft Thermal Analysis Tool Project

    Data.gov (United States)

    National Aeronautics and Space Administration — For spacecraft design and development teams concerned with cost and schedule, the Quick Spacecraft Thermal Analysis Tool (QuickSTAT) is an innovative software suite...

  5. 2010 Solar Market Transformation Analysis and Tools

    Energy Technology Data Exchange (ETDEWEB)

    none,

    2010-04-01

    This document describes the DOE-funded solar market transformation analysis and tools under development in Fiscal Year 2010 so that stakeholders can access available resources and get engaged where interested.

  6. Analysis of Layered Social Networks

    Science.gov (United States)

    2006-09-01

    xiii List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv I. Introduction ...Islamiya JP Joint Publication JTC Joint Targeting Cycle KPP Key Player Problem MCDM Multi-Criteria Decision Making MP Mathematical Programming MST...ANALYSIS OF LAYERED SOCIAL NETWORKS I. Introduction “To know them means to eliminate them” - Colonel Mathieu in the movie, Battle of Algiers

  7. Databases and tools for constructing signal transduction networks in cancer.

    Science.gov (United States)

    Nam, Seungyoon

    2017-01-01

    Traditionally, biologists have devoted their careers to studying individual biological entities of their own interest, partly due to lack of available data regarding that entity. Large, highthroughput data, too complex for conventional processing methods (i.e., "big data"), has accumulated in cancer biology, which is freely available in public data repositories. Such challenges urge biologists to inspect their biological entities of interest using novel approaches, firstly including repository data retrieval. Essentially, these revolutionary changes demand new interpretations of huge datasets at a systems-level, by so called "systems biology". One of the representative applications of systems biology is to generate a biological network from high-throughput big data, providing a global map of molecular events associated with specific phenotype changes. In this review, we introduce the repositories of cancer big data and cutting-edge systems biology tools for network generation, and improved identification of therapeutic targets. [BMB Reports 2017; 50(1): 12-19].

  8. Beyond marks: new tools to visualise student engagement via social networks

    Directory of Open Access Journals (Sweden)

    Joanne L. Badge

    2012-02-01

    Full Text Available Evidence shows that engaged students perform better academically than disinterested students. Measurement of engagement with education is difficult and imprecise, especially in large student cohorts. Traditional measurements such as summary statistics derived from assessment are crude secondary measures of engagement at best and do not provide much support for educators to work with students and curate engagement during teaching periods. We have used academic-related student contributions to a public social network as a proxy for engagement. Statistical summaries and novel data visualisation tools provide subtle and powerful insights into online student peer networks. Analysis of data collected shows that network visualisation can be an important curation tool for educators interested in cultivating student engagement.

  9. Statistical analysis of network data with R

    CERN Document Server

    Kolaczyk, Eric D

    2014-01-01

    Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).

  10. NetworkAnalyst--integrative approaches for protein-protein interaction network analysis and visual exploration.

    Science.gov (United States)

    Xia, Jianguo; Benner, Maia J; Hancock, Robert E W

    2014-07-01

    Biological network analysis is a powerful approach to gain systems-level understanding of patterns of gene expression in different cell types, disease states and other biological/experimental conditions. Three consecutive steps are required--identification of genes or proteins of interest, network construction and network analysis and visualization. To date, researchers have to learn to use a combination of several tools to accomplish this task. In addition, interactive visualization of large networks has been primarily restricted to locally installed programs. To address these challenges, we have developed NetworkAnalyst, taking advantage of state-of-the-art web technologies, to enable high performance network analysis with rich user experience. NetworkAnalyst integrates all three steps and presents the results via a powerful online network visualization framework. Users can upload gene or protein lists, single or multiple gene expression datasets to perform comprehensive gene annotation and differential expression analysis. Significant genes are mapped to our manually curated protein-protein interaction database to construct relevant networks. The results are presented through standard web browsers for network analysis and interactive exploration. NetworkAnalyst supports common functions for network topology and module analyses. Users can easily search, zoom and highlight nodes or modules, as well as perform functional enrichment analysis on these selections. The networks can be customized with different layouts, colors or node sizes, and exported as PNG, PDF or GraphML files. Comprehensive FAQs, tutorials and context-based tips and instructions are provided. NetworkAnalyst currently supports protein-protein interaction network analysis for human and mouse and is freely available at http://www.networkanalyst.ca. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Distributed Denial of Service Tools, Trin00, Tribe Flood Network, Tribe Flood Network 2000 and Stacheldraht.

    Energy Technology Data Exchange (ETDEWEB)

    Criscuolo, P. J.

    2000-02-14

    One type of attack on computer systems is know as a Denial of Service (DoS) attack. A DoS attack is designed to prevent legitimate users from using a system. Traditional Denial of Service attacks are done by exploiting a buffer overflow, exhausting system resources, or exploiting a system bug that results in a system that is no longer functional. In the summer of 1999, a new breed of attack has been developed called Distributed Denial of Service (DDoS) attack. Several educational and high capacity commercial sites have been affected by these DDoS attacks. A DDoS attack uses multiple machines operating in concert to attack a network or site. There is very little that can be done if you are the target of a DDoS. The nature of these attacks cause so much extra network traffic that it is difficult for legitimate traffic to reach your site while blocking the forged attacking packets. The intent of this paper is to help sites not be involved in a DDoS attack. The first tools developed to perpetrate the DDoS attack were Trin00 and Tribe Flood Network (TFN). They spawned the next generation of tools called Tribe Flood Network 2000 (TFN2K) and Stacheldraht (German for Barb Wire). These DDoS attack tools are designed to bring one or more sites down by flooding the victim with large amounts of network traffic originating at multiple locations and remotely controlled by a single client. This paper discusses how these DDoS tools work, how to detect them, and specific technical information on each individual tool. It is written with the system administrator in mind. It assumes that the reader has basic knowledge of the TCP/IP Protocol.

  12. Software Tool for Real-Time Power Quality Analysis

    Directory of Open Access Journals (Sweden)

    CZIKER, A. C.

    2013-11-01

    Full Text Available A software tool dedicated for the analysis of power signals containing harmonic and interharmonic components, unbalance, voltage dips and voltage swells is presented. The software tool is a virtual instrument, which uses innovative algorithms based on time and frequency domains analysis to process power signals. In order to detect the temporary disturbances, edge detection is proposed, whereas for the harmonic analysis Gaussian filter banks are implemented. Considering that a signal recovery algorithm is applied, the harmonic analysis can be made even if voltage dips or swells appear. The virtual instrument input data can be recorded or online signals; the last ones being get through a data acquisition board. The virtual instrument was tested using both virtually created and real signals from measurements performed in distribution networks. The paper contains a numeric example made on a synthetic digital signal and an analysis made in real-time.

  13. Paediatric Automatic Phonological Analysis Tools (APAT).

    Science.gov (United States)

    Saraiva, Daniela; Lousada, Marisa; Hall, Andreia; Jesus, Luis M T

    2017-12-01

    To develop the pediatric Automatic Phonological Analysis Tools (APAT) and to estimate inter and intrajudge reliability, content validity, and concurrent validity. The APAT were constructed using Excel spreadsheets with formulas. The tools were presented to an expert panel for content validation. The corpus used in the Portuguese standardized test Teste Fonético-Fonológico - ALPE produced by 24 children with phonological delay or phonological disorder was recorded, transcribed, and then inserted into the APAT. Reliability and validity of APAT were analyzed. The APAT present strong inter- and intrajudge reliability (>97%). The content validity was also analyzed (ICC = 0.71), and concurrent validity revealed strong correlations between computerized and manual (traditional) methods. The development of these tools contributes to fill existing gaps in clinical practice and research, since previously there were no valid and reliable tools/instruments for automatic phonological analysis, which allowed the analysis of different corpora.

  14. Analysis of neural networks through base functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.

    Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more

  15. Transmission analysis in WDM networks

    DEFF Research Database (Denmark)

    Rasmussen, Christian Jørgen

    1999-01-01

    This thesis describes the development of a computer-based simulator for transmission analysis in optical wavelength division multiplexing networks. A great part of the work concerns fundamental optical network simulator issues. Among these issues are identification of the versatility and user......-friendliness demands which such a simulator must meet, development of the "spectral window representation" for representation of the optical signals and finding an effective way of handling the optical signals in the computer memory. One important issue more is the rules for the determination of the order in which...... the different component models are invoked during the simulation of a system. A simple set of rules which makes it possible to simulate any network architectures is laid down. The modelling of the nonlinear fibre and the optical receiver is also treated. The work on the fibre concerns the numerical solution...

  16. Photogrammetry Tool for Forensic Analysis

    Science.gov (United States)

    Lane, John

    2012-01-01

    A system allows crime scene and accident scene investigators the ability to acquire visual scene data using cameras for processing at a later time. This system uses a COTS digital camera, a photogrammetry calibration cube, and 3D photogrammetry processing software. In a previous instrument developed by NASA, the laser scaling device made use of parallel laser beams to provide a photogrammetry solution in 2D. This device and associated software work well under certain conditions. In order to make use of a full 3D photogrammetry system, a different approach was needed. When using multiple cubes, whose locations relative to each other are unknown, a procedure that would merge the data from each cube would be as follows: 1. One marks a reference point on cube 1, then marks points on cube 2 as unknowns. This locates cube 2 in cube 1 s coordinate system. 2. One marks reference points on cube 2, then marks points on cube 1 as unknowns. This locates cube 1 in cube 2 s coordinate system. 3. This procedure is continued for all combinations of cubes. 4. The coordinate of all of the found coordinate systems is then merged into a single global coordinate system. In order to achieve maximum accuracy, measurements are done in one of two ways, depending on scale: when measuring the size of objects, the coordinate system corresponding to the nearest cube is used, or when measuring the location of objects relative to a global coordinate system, a merged coordinate system is used. Presently, traffic accident analysis is time-consuming and not very accurate. Using cubes with differential GPS would give absolute positions of cubes in the accident area, so that individual cubes would provide local photogrammetry calibration to objects near a cube.

  17. Analysis Tool Web Services from the EMBL-EBI.

    Science.gov (United States)

    McWilliam, Hamish; Li, Weizhong; Uludag, Mahmut; Squizzato, Silvano; Park, Young Mi; Buso, Nicola; Cowley, Andrew Peter; Lopez, Rodrigo

    2013-07-01

    Since 2004 the European Bioinformatics Institute (EMBL-EBI) has provided access to a wide range of databases and analysis tools via Web Services interfaces. This comprises services to search across the databases available from the EMBL-EBI and to explore the network of cross-references present in the data (e.g. EB-eye), services to retrieve entry data in various data formats and to access the data in specific fields (e.g. dbfetch), and analysis tool services, for example, sequence similarity search (e.g. FASTA and NCBI BLAST), multiple sequence alignment (e.g. Clustal Omega and MUSCLE), pairwise sequence alignment and protein functional analysis (e.g. InterProScan and Phobius). The REST/SOAP Web Services (http://www.ebi.ac.uk/Tools/webservices/) interfaces to these databases and tools allow their integration into other tools, applications, web sites, pipeline processes and analytical workflows. To get users started using the Web Services, sample clients are provided covering a range of programming languages and popular Web Service tool kits, and a brief guide to Web Services technologies, including a set of tutorials, is available for those wishing to learn more and develop their own clients. Users of the Web Services are informed of improvements and updates via a range of methods.

  18. Chemometric Tools in Environmental Data Analysis

    Science.gov (United States)

    Reczynski, Witold; Jakubowska, Malgorzata; Bas, Boguslaw; Niewiara, Ewa; Kubiak, Władysław W.

    2007-12-01

    Chemometric analysis of the Dobczyce Reservoir sediments is presented herein. The sediments have been sampled at 17 points, dried, digested and quantitatively analyzed for 12 elements, covering a three-year period (2004-2006). Substantial variations in composition due to the hydrological and environmental reasons were found. The use of mathematical and statistical tools enables objective and effective analysis of obtained data.

  19. Spectral Analysis of Rich Network Topology in Social Networks

    Science.gov (United States)

    Wu, Leting

    2013-01-01

    Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…

  20. Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network.

    Science.gov (United States)

    Petrescu-Prahova, Miruna; Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B; Anderson, Lynda A

    2015-08-20

    Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level.

  1. Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

    Directory of Open Access Journals (Sweden)

    Ufa Ruslan A.

    2015-01-01

    Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

  2. Built Environment Energy Analysis Tool Overview (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Porter, C.

    2013-04-01

    This presentation provides an overview of the Built Environment Energy Analysis Tool, which is designed to assess impacts of future land use/built environment patterns on transportation-related energy use and greenhouse gas (GHG) emissions. The tool can be used to evaluate a range of population distribution and urban design scenarios for 2030 and 2050. This tool was produced as part of the Transportation Energy Futures (TEF) project, a Department of Energy-sponsored multi-agency project initiated to pinpoint underexplored strategies for abating GHGs and reducing petroleum dependence related to transportation.

  3. Collaborative Tools for e-Participation across Networks: The Comuno Networking Site for Public Governance and Services

    Directory of Open Access Journals (Sweden)

    Michael Kaschesky

    2010-04-01

    Full Text Available This paper presents collaborative tools for public participation across multiple networking sites. The tools are part of the Comuno networking site for public governance and services, which is particularly targeted at the public sector (currently in alpha testing at http://comuno.org. The Broadcast tool allows cross-posting content from Comuno to a wide variety of other networking sites, such as Facebook or Twitter. The UserFeed and TopicFeed tools build RSS feeds from content published by a specific user or under a specific topic. The LifeStream tool gathers a user’s activities across multiple networking sites in the private account section at Comuno. These tools and related aspects of the Comuno networking site are discussed and presented in the context of deliberation and opinion-forming in a Swiss bilingual city.

  4. Analysis of Semantic Networks using Complex Networks Concepts

    DEFF Research Database (Denmark)

    Ortiz-Arroyo, Daniel

    2013-01-01

    In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...... results indicate that this approach provides good results on the semantic network analyzed in this paper....

  5. 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.

  6. DANNP: an efficient artificial neural network pruning tool

    Directory of Open Access Journals (Sweden)

    Mona Alshahrani

    2017-11-01

    Full Text Available Background Artificial neural networks (ANNs are a robust class of machine learning models and are a frequent choice for solving classification problems. However, determining the structure of the ANNs is not trivial as a large number of weights (connection links may lead to overfitting the training data. Although several ANN pruning algorithms have been proposed for the simplification of ANNs, these algorithms are not able to efficiently cope with intricate ANN structures required for complex classification problems. Methods We developed DANNP, a web-based tool, that implements parallelized versions of several ANN pruning algorithms. The DANNP tool uses a modified version of the Fast Compressed Neural Network software implemented in C++ to considerably enhance the running time of the ANN pruning algorithms we implemented. In addition to the performance evaluation of the pruned ANNs, we systematically compared the set of features that remained in the pruned ANN with those obtained by different state-of-the-art feature selection (FS methods. Results Although the ANN pruning algorithms are not entirely parallelizable, DANNP was able to speed up the ANN pruning up to eight times on a 32-core machine, compared to the serial implementations. To assess the impact of the ANN pruning by DANNP tool, we used 16 datasets from different domains. In eight out of the 16 datasets, DANNP significantly reduced the number of weights by 70%–99%, while maintaining a competitive or better model performance compared to the unpruned ANN. Finally, we used a naïve Bayes classifier derived with the features selected as a byproduct of the ANN pruning and demonstrated that its accuracy is comparable to those obtained by the classifiers trained with the features selected by several state-of-the-art FS methods. The FS ranking methodology proposed in this study allows the users to identify the most discriminant features of the problem at hand. To the best of our knowledge

  7. DANNP: an efficient artificial neural network pruning tool

    KAUST Repository

    Alshahrani, Mona

    2017-11-06

    Background Artificial neural networks (ANNs) are a robust class of machine learning models and are a frequent choice for solving classification problems. However, determining the structure of the ANNs is not trivial as a large number of weights (connection links) may lead to overfitting the training data. Although several ANN pruning algorithms have been proposed for the simplification of ANNs, these algorithms are not able to efficiently cope with intricate ANN structures required for complex classification problems. Methods We developed DANNP, a web-based tool, that implements parallelized versions of several ANN pruning algorithms. The DANNP tool uses a modified version of the Fast Compressed Neural Network software implemented in C++ to considerably enhance the running time of the ANN pruning algorithms we implemented. In addition to the performance evaluation of the pruned ANNs, we systematically compared the set of features that remained in the pruned ANN with those obtained by different state-of-the-art feature selection (FS) methods. Results Although the ANN pruning algorithms are not entirely parallelizable, DANNP was able to speed up the ANN pruning up to eight times on a 32-core machine, compared to the serial implementations. To assess the impact of the ANN pruning by DANNP tool, we used 16 datasets from different domains. In eight out of the 16 datasets, DANNP significantly reduced the number of weights by 70%–99%, while maintaining a competitive or better model performance compared to the unpruned ANN. Finally, we used a naïve Bayes classifier derived with the features selected as a byproduct of the ANN pruning and demonstrated that its accuracy is comparable to those obtained by the classifiers trained with the features selected by several state-of-the-art FS methods. The FS ranking methodology proposed in this study allows the users to identify the most discriminant features of the problem at hand. To the best of our knowledge, DANNP (publicly

  8. Networks and network analysis for defence and security

    CERN Document Server

    Masys, Anthony J

    2014-01-01

    Networks and Network Analysis for Defence and Security discusses relevant theoretical frameworks and applications of network analysis in support of the defence and security domains. This book details real world applications of network analysis to support defence and security. Shocks to regional, national and global systems stemming from natural hazards, acts of armed violence, terrorism and serious and organized crime have significant defence and security implications. Today, nations face an uncertain and complex security landscape in which threats impact/target the physical, social, economic

  9. Teaching Students How to Integrate and Assess Social Networking Tools in Marketing Communications

    Science.gov (United States)

    Schlee, Regina Pefanis; Harich, Katrin R.

    2013-01-01

    This research is based on two studies that focus on teaching students how to integrate and assess social networking tools in marketing communications. Study 1 examines how students in marketing classes utilize social networking tools and explores their attitudes regarding the use of such tools for marketing communications. Study 2 focuses on an…

  10. Unraveling protein networks with power graph analysis.

    Science.gov (United States)

    Royer, Loïc; Reimann, Matthias; Andreopoulos, Bill; Schroeder, Michael

    2008-07-11

    Networks play a crucial role in computational biology, yet their analysis and representation is still an open problem. Power Graph Analysis is a lossless transformation of biological networks into a compact, less redundant representation, exploiting the abundance of cliques and bicliques as elementary topological motifs. We demonstrate with five examples the advantages of Power Graph Analysis. Investigating protein-protein interaction networks, we show how the catalytic subunits of the casein kinase II complex are distinguishable from the regulatory subunits, how interaction profiles and sequence phylogeny of SH3 domains correlate, and how false positive interactions among high-throughput interactions are spotted. Additionally, we demonstrate the generality of Power Graph Analysis by applying it to two other types of networks. We show how power graphs induce a clustering of both transcription factors and target genes in bipartite transcription networks, and how the erosion of a phosphatase domain in type 22 non-receptor tyrosine phosphatases is detected. We apply Power Graph Analysis to high-throughput protein interaction networks and show that up to 85% (56% on average) of the information is redundant. Experimental networks are more compressible than rewired ones of same degree distribution, indicating that experimental networks are rich in cliques and bicliques. Power Graphs are a novel representation of networks, which reduces network complexity by explicitly representing re-occurring network motifs. Power Graphs compress up to 85% of the edges in protein interaction networks and are applicable to all types of networks such as protein interactions, regulatory networks, or homology networks.

  11. Computational Tools for the Secondary Analysis of Metabolomics Experiments

    Directory of Open Access Journals (Sweden)

    Sean Cameron Booth

    2013-01-01

    Full Text Available Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

  12. COMPUTATIONAL TOOLS FOR THE SECONDARY ANALYSIS OF METABOLOMICS EXPERIMENTS

    Directory of Open Access Journals (Sweden)

    Sean C. Booth

    2013-01-01

    Full Text Available Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

  13. DNA sequence analysis using hierarchical ART-based classification networks

    Energy Technology Data Exchange (ETDEWEB)

    LeBlanc, C.; Hruska, S.I. [Florida State Univ., Tallahassee, FL (United States); Katholi, C.R.; Unnasch, T.R. [Univ. of Alabama, Birmingham, AL (United States)

    1994-12-31

    Adaptive resonance theory (ART) describes a class of artificial neural network architectures that act as classification tools which self-organize, work in real-time, and require no retraining to classify novel sequences. We have adapted ART networks to provide support to scientists attempting to categorize tandem repeat DNA fragments from Onchocerca volvulus. In this approach, sequences of DNA fragments are presented to multiple ART-based networks which are linked together into two (or more) tiers; the first provides coarse sequence classification while the sub- sequent tiers refine the classifications as needed. The overall rating of the resulting classification of fragments is measured using statistical techniques based on those introduced to validate results from traditional phylogenetic analysis. Tests of the Hierarchical ART-based Classification Network, or HABclass network, indicate its value as a fast, easy-to-use classification tool which adapts to new data without retraining on previously classified data.

  14. Signed Link Analysis in Social Media Networks

    OpenAIRE

    Beigi, Ghazaleh; Tang, Jiliang; Liu, Huan

    2016-01-01

    Numerous real-world relations can be represented by signed networks with positive links (e.g., trust) and negative links (e.g., distrust). Link analysis plays a crucial role in understanding the link formation and can advance various tasks in social network analysis such as link prediction. The majority of existing works on link analysis have focused on unsigned social networks. The existence of negative links determines that properties and principles of signed networks are substantially dist...

  15. Social network analysis in medical education

    OpenAIRE

    Isba, Rachel; Woolf, Katherine; Hanneman, Robert

    2016-01-01

    Content\\ud Humans are fundamentally social beings. The social systems within which we live our lives (families, schools, workplaces, professions, friendship groups) have a significant influence on our health, success and well-being. These groups can be characterised as networks and analysed using social network analysis.\\ud \\ud Social Network Analysis\\ud Social network analysis is a mainly quantitative method for analysing how relationships between individuals form and affect those individual...

  16. Introduction to stream network habitat analysis

    Science.gov (United States)

    Bartholow, John M.; Waddle, Terry J.

    1986-01-01

    be fed back to the design of new alternatives, which themselves may be similarly tested. One may get as sophisticated an analysis as the decisionmaking process demands. Figure 1 shows a decision point that asks whether the results from the micro- or macrohabitat models display cumulative or synergistic effects. If they do, then network habitat analysis is the appropriate tool. We are left, however, in a difficult bind. We may not know a priori whether the effects are cumulative or synergistic unless some network-type questions are investigated as part of the scoping process. The next several sections raise issues designed to alert the modeler to relevant questions necessary to address this paradox.

  17. Social Networking Tools for Informal Scholarly Communication Prove Popular for Academics at Two Universities

    Directory of Open Access Journals (Sweden)

    Aoife Lawton

    2016-04-01

    Full Text Available Objective – To investigate the adoption, use, perceived impact of, and barriers to using social networking tools for scholarly communication at two universities. Design – Cross-institutional quantitative study using an online survey. Setting – Academics working in the disciplines of the humanities and social sciences at two universities: one in Europe and one in the Middle East. Methods – An online survey was devised based on a previous survey (Al-Aufi, 2007 and informed by relevant research. The survey was piloted by 10 academics at the 2 participating universities. Post pilot it was revised and then circulated to all academics from similar faculties at two universities. Three follow up emails were sent to both sets of academics. The data was analyzed using Statistical Package for the Social Sciences (SPSS software. Descriptive and inferential statistics were analyzed using ANOVA tests. Main Results – The survey achieved a 34% response rate (n=130. The majority of participants were from the university based in the Middle East and were male (70.8%. Most of the responses were from academics under 40 years of age. The use of notebooks was prevalent at both universities. “Notebooks” is used as a term to describe laptops, netbooks, or ultra-book computers. The majority reported use of social networking tools for informal scholarly communication (70.1%, valuing this type of use. 29.9% of respondents reported they do not use social networking tools for this purpose. Barriers were identified as lack of incentive, digital literacy, training, and concerns over Internet security. Among the non-users, barriers included low interest in their use and a perceived lack of relevancy of such tools for scholarly communication. The types of tools used the most were those with social connection functions, such as Facebook and Twitter. The tools used the least were social bookmarking tools. A one-way analysis of variance (ANOVA test indicated that

  18. Applied regression analysis a research tool

    CERN Document Server

    Pantula, Sastry; Dickey, David

    1998-01-01

    Least squares estimation, when used appropriately, is a powerful research tool. A deeper understanding of the regression concepts is essential for achieving optimal benefits from a least squares analysis. This book builds on the fundamentals of statistical methods and provides appropriate concepts that will allow a scientist to use least squares as an effective research tool. Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to...

  19. Statistical Tools for Forensic Analysis of Toolmarks

    Energy Technology Data Exchange (ETDEWEB)

    David Baldwin; Max Morris; Stan Bajic; Zhigang Zhou; James Kreiser

    2004-04-22

    Recovery and comparison of toolmarks, footprint impressions, and fractured surfaces connected to a crime scene are of great importance in forensic science. The purpose of this project is to provide statistical tools for the validation of the proposition that particular manufacturing processes produce marks on the work-product (or tool) that are substantially different from tool to tool. The approach to validation involves the collection of digital images of toolmarks produced by various tool manufacturing methods on produced work-products and the development of statistical methods for data reduction and analysis of the images. The developed statistical methods provide a means to objectively calculate a ''degree of association'' between matches of similarly produced toolmarks. The basis for statistical method development relies on ''discriminating criteria'' that examiners use to identify features and spatial relationships in their analysis of forensic samples. The developed data reduction algorithms utilize the same rules used by examiners for classification and association of toolmarks.

  20. Topological clustering as a tool for planning water quality monitoring in water distribution networks

    DEFF Research Database (Denmark)

    Kirstein, Jonas Kjeld; Albrechtsen, Hans-Jørgen; Rygaard, Martin

    2015-01-01

    ) identify steady clusters for a part of the network where an actual contamination has occurred; (2) analyze this event by the use of mesh diagrams; and (3) analyze the use of mesh diagrams as a decision support tool for planning water quality monitoring. Initially, the network model was divided...... into strongly and weakly connected clusters for selected time periods and mesh diagrams were used for analysing cluster connections in the Nørrebro district. Here, areas of particular interest for water quality monitoring were identified by including user-information about consumption rates and consumers...... particular sensitive towards water quality deterioration. The analysis revealed sampling locations within steady clusters, which increased samples' comparability over time. Furthermore, the method provided a simplified overview of water movement in complex distribution networks, and could assist...

  1. Network-based analysis of proteomic profiles

    KAUST Repository

    Wong, Limsoon

    2016-01-26

    Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.

  2. Topological Analysis of Wireless Networks (TAWN)

    Science.gov (United States)

    2016-05-31

    19b. TELEPHONE NUMBER (Include area code) 31-05-2016 FINAL REPORT 12-02-2015 -- 31-05-2016 Topological Analysis of Wireless Networks (TAWN) Robinson...mathematical literature on sheaves that describes how to draw global ( network -wide) inferences from them. Wireless network , local homology, sheaf...topology U U U UU 32 Michael Robinson 202-885-3681 Final Report: May 2016 Topological Analysis of Wireless Networks Principal Investigator: Prof. Michael

  3. Review Essay: Does Qualitative Network Analysis Exist?

    Directory of Open Access Journals (Sweden)

    Rainer Diaz-Bone

    2007-01-01

    Full Text Available Social network analysis was formed and established in the 1970s as a way of analyzing systems of social relations. In this review the theoretical-methodological standpoint of social network analysis ("structural analysis" is introduced and the different forms of social network analysis are presented. Structural analysis argues that social actors and social relations are embedded in social networks, meaning that action and perception of actors as well as the performance of social relations are influenced by the network structure. Since the 1990s structural analysis has integrated concepts such as agency, discourse and symbolic orientation and in this way structural analysis has opened itself. Since then there has been increasing use of qualitative methods in network analysis. They are used to include the perspective of the analyzed actors, to explore networks, and to understand network dynamics. In the reviewed book, edited by Betina HOLLSTEIN and Florian STRAUS, the twenty predominantly empirically orientated contributions demonstrate the possibilities of combining quantitative and qualitative methods in network analyses in different research fields. In this review we examine how the contributions succeed in applying and developing the structural analysis perspective, and the self-positioning of "qualitative network analysis" is evaluated. URN: urn:nbn:de:0114-fqs0701287

  4. Drawing tool recognition by stroke ending analysis

    Science.gov (United States)

    Vill, Maria C.; Sablatnig, Robert

    2008-02-01

    The aim of our work is the development of image analysis tools and methods for the investigation of drawings and drawn drafts in order to investigate the authorship, to identify copies or more general to allow for a comparison of different types of drawings. It was and is common for artists to draw their design as several drafts on paper. These drawings can show how some elements were adjusted until the artist was satisfied with the composition. Therefore it can bring insights into the practice of artists and painting and/or drawing schools. This information is useful for art historians, because it can relate artists to each other. The goal of this paper is to describe a stroke classification algorithm which can recognize the drawing tool based on the shape of the endings of an open stroke. In this context, "open" means that both endings of a stroke are free-standing, uncovered and do not pass into another stroke. These endings are prominent features whose shape carries information about the drawing tool and are therefore used as features to distinguish different drawing tools. Our results show that it is possible to use these endings as input a drawing tool classificator.

  5. NETWORKING TOOLS FOR SHOPPING MALLS: HOW TO IMPLEMENT THEM AND MEASURE THEIR EFFECTIVENESS

    Directory of Open Access Journals (Sweden)

    Evgeniya Vasilevna Elistratova

    2017-10-01

    Full Text Available Despite the importance of shopping malls for the contemporary society and their network nature there is no algorithmic basis for support of implementation of networking tools in the business activity of shopping malls. The goal of the present paper is to develop this basis. The paper contains an algorithm of implementation of networking tools which includes five stages. For each stage detailed comments and recommendations are given. A list of indexes of effectiveness of networking tools is proposed. A method for evaluation of the effectiveness of measures of implementation of networking tools is described. A diagnostic matrix which can be used for evaluation of the effectiveness of the company during the proccess of implementation of networking tools is given.

  6. Designing a Tool for History Textbook Analysis

    Directory of Open Access Journals (Sweden)

    Katalin Eszter Morgan

    2012-11-01

    Full Text Available This article describes the process by which a five-dimensional tool for history textbook analysis was conceptualized and developed in three stages. The first stage consisted of a grounded theory approach to code the content of the sampled chapters of the books inductively. After that the findings from this coding process were combined with principles of text analysis as derived from the literature, specifically focusing on the notion of semiotic mediation as theorized by Lev VYGOTSKY. We explain how we then entered the third stage of the development of the tool, comprising five dimensions. Towards the end of the article we show how the tool could be adapted to serve other disciplines as well. The argument we forward in the article is for systematic and well theorized tools with which to investigate textbooks as semiotic mediators in education. By implication, textbook authors can also use these as guidelines. URN: http://nbn-resolving.de/urn:nbn:de:0114-fqs130170

  7. Social network analysis community detection and evolution

    CERN Document Server

    Missaoui, Rokia

    2015-01-01

    This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

  8. Network analysis literacy a practical approach to the analysis of networks

    CERN Document Server

    Zweig, Katharina A

    2014-01-01

    Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.

  9. Investigating scientific literacy documents with linguistic network analysis

    DEFF Research Database (Denmark)

    Bruun, Jesper; Evans, Robert Harry; Dolin, Jens

    2009-01-01

    International discussions of scientific literacy (SL) are extensive and numerous sizeable documents on SL exist. Thus, comparing different conceptions of SL is methodologically challenging. We developed an analytical tool which couples the theory of complex networks with text analysis in order...

  10. SBAT. A stochastic BPMN analysis tool

    DEFF Research Database (Denmark)

    Herbert, Luke Thomas; Hansen, Zaza Nadja Lee; Jacobsen, Peter

    2014-01-01

    This paper presents SBAT, a tool framework for the modelling and analysis of complex business workflows. SBAT is applied to analyse an example from the Danish baked goods industry. Based upon the Business Process Modelling and Notation (BPMN) language for business process modelling, we describe...... a formalised variant of this language extended to support the addition of intention preserving stochastic branching and parameterised reward annotations. Building on previous work, we detail the design of SBAT, a software tool which allows for the analysis of BPMN models. Within SBAT, properties of interest...... and the value of associated rewards in states of interest for a real-world example from a case company in the Danish baked goods industry. The developments are presented in a generalised fashion to make them relevant to the general problem of implementing quantitative probabilistic model checking of graph...

  11. TROVE: A User-friendly Tool for Visualizing and Analyzing Cancer Hallmarks in Signaling Networks.

    Science.gov (United States)

    Chua, Huey Eng; Bhowmick, Sourav S; Zheng, Jie

    2017-09-22

    Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks. In particular, TROVE facilitates hallmark analysis specific to particular cancer types. Available under the Eclipse Public License from: https://sites.google.com/site/cosbyntu/softwares/trove and https://github.com/trove2017/Trove. hechua@ntu.edu.sg or assourav@ntu.edu.sg.

  12. Applications of Social Network Analysis

    Science.gov (United States)

    Thilagam, P. Santhi

    A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.

  13. e-Dermatology: social networks and other web based tools.

    Science.gov (United States)

    Taberner, R

    2016-03-01

    The use by patients of social networking sites and the Internet to look for health related information has already become an everyday phenomenon. If, as dermatologists, we want to be part of this new conversation and provide quality content, we will have to adapt to digital media and find new ways of communicating with both our patients and our colleagues. Dozens of Spanish dermatologists have already ventured into the online space and have begun to provide important content through blogs, which they also disseminate via the social media. However, the use of these new technologies can also pose certain risks from the standpoint of ethics and our codes of practice and even place an individual's digital reputation in jeopardy. Another aspect of this new situation is that the Internet produces information saturation, and the appropriate use of certain tools can help to improve our productivity and prevent such information overload or infoxication. Copyright © 2015 AEDV. Published by Elsevier España, S.L.U. All rights reserved.

  14. Understanding complex interactions using social network analysis.

    Science.gov (United States)

    Pow, Janette; Gayen, Kaberi; Elliott, Lawrie; Raeside, Robert

    2012-10-01

    The aim of this paper is to raise the awareness of social network analysis as a method to facilitate research in nursing research. The application of social network analysis in assessing network properties has allowed greater insight to be gained in many areas including sociology, politics, business organisation and health care. However, the use of social networks in nursing has not received sufficient attention. Review of literature and illustration of the application of the method of social network analysis using research examples. First, the value of social networks will be discussed. Then by using illustrative examples, the value of social network analysis to nursing will be demonstrated. The method of social network analysis is found to give greater insights into social situations involving interactions between individuals and has particular application to the study of interactions between nurses and between nurses and patients and other actors. Social networks are systems in which people interact. Two quantitative techniques help our understanding of these networks. The first is visualisation of the network. The second is centrality. Individuals with high centrality are key communicators in a network. Applying social network analysis to nursing provides a simple method that helps gain an understanding of human interaction and how this might influence various health outcomes. It allows influential individuals (actors) to be identified. Their influence on the formation of social norms and communication can determine the extent to which new interventions or ways of thinking are accepted by a group. Thus, working with key individuals in a network could be critical to the success and sustainability of an intervention. Social network analysis can also help to assess the effectiveness of such interventions for the recipient and the service provider. © 2012 Blackwell Publishing Ltd.

  15. ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

    Science.gov (United States)

    Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

    2008-08-12

    New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

  16. Network meta-analysis, electrical networks and graph theory.

    Science.gov (United States)

    Rücker, Gerta

    2012-12-01

    Network meta-analysis is an active field of research in clinical biostatistics. It aims to combine information from all randomized comparisons among a set of treatments for a given medical condition. We show how graph-theoretical methods can be applied to network meta-analysis. A meta-analytic graph consists of vertices (treatments) and edges (randomized comparisons). We illustrate the correspondence between meta-analytic networks and electrical networks, where variance corresponds to resistance, treatment effects to voltage, and weighted treatment effects to current flows. Based thereon, we then show that graph-theoretical methods that have been routinely applied to electrical networks also work well in network meta-analysis. In more detail, the resulting consistent treatment effects induced in the edges can be estimated via the Moore-Penrose pseudoinverse of the Laplacian matrix. Moreover, the variances of the treatment effects are estimated in analogy to electrical effective resistances. It is shown that this method, being computationally simple, leads to the usual fixed effect model estimate when applied to pairwise meta-analysis and is consistent with published results when applied to network meta-analysis examples from the literature. Moreover, problems of heterogeneity and inconsistency, random effects modeling and including multi-armed trials are addressed. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

  17. WiFiSiM: An Educational Tool for the Study and Design of Wireless Networks

    Science.gov (United States)

    Mateo Sanguino, T. J.; Serrano Lopez, C.; Marquez Hernandez, F. A.

    2013-01-01

    A new educational simulation tool designed for the generic study of wireless networks, the Wireless Fidelity Simulator (WiFiSim), is presented in this paper. The goal of this work was to create and implement a didactic tool to improve the teaching and learning of computer networks by means of two complementary strategies: simulating the behavior…

  18. Enhancing Lifelong Competence Development and Management Systems with Social Network-based Concepts and Tools

    NARCIS (Netherlands)

    Cheak, Alicia; Angehrn, Albert; Sloep, Peter

    2006-01-01

    This paper addresses the challenge of enhancing the social dimension of lifelong Competence Development and Management Systems with social network-based concepts and tools. Our premise is that through a combination of social network visualization tools, simulations, stimulus agents and management

  19. Conformal polishing approach: Tool footprint analysis

    Directory of Open Access Journals (Sweden)

    José A Dieste

    2016-02-01

    Full Text Available Polishing process is one of the most critical manufacturing processes during a metal part production because it determines the final quality of the product. Free-form surface polishing is a handmade process with lots of rejected parts, scrap generation and time and energy consumption. Two different research lines are being developed: prediction models of the final surface quality parameters and an analysis of the amount of material removed depending on the polishing parameters to predict the tool footprint during the polishing task. This research lays the foundations for a future automatic conformal polishing system. It is based on rotational and translational tool with dry abrasive in the front mounted at the end of a robot. A tool to part concept is used, useful for large or heavy workpieces. Results are applied on different curved parts typically used in tooling industry, aeronautics or automotive. A mathematical model has been developed to predict the amount of material removed in function of polishing parameters. Model has been fitted for different abrasives and raw materials. Results have shown deviations under 20% that implies a reliable and controllable process. Smaller amount of material can be removed in controlled areas of a three-dimensional workpiece.

  20. Knickpoint finder: A software tool that improves neotectonic analysis

    Science.gov (United States)

    Queiroz, G. L.; Salamuni, E.; Nascimento, E. R.

    2015-03-01

    This work presents a new software tool for morphometric analysis of drainage networks based on the methods of Hack (1973) and Etchebehere et al. (2004). This tool is applicable to studies of morphotectonics and neotectonics. The software used a digital elevation model (DEM) to identify the relief breakpoints along drainage profiles (knickpoints). The program was coded in Python for use on the ArcGIS platform and is called Knickpoint Finder. A study area was selected to test and evaluate the software's ability to analyze and identify neotectonic morphostructures based on the morphology of the terrain. For an assessment of its validity, we chose an area of the James River basin, which covers most of the Piedmont area of Virginia (USA), which is an area of constant intraplate seismicity and non-orogenic active tectonics and exhibits a relatively homogeneous geodesic surface currently being altered by the seismogenic features of the region. After using the tool in the chosen area, we found that the knickpoint locations are associated with the geologic structures, epicenters of recent earthquakes, and drainages with rectilinear anomalies. The regional analysis demanded the use of a spatial representation of the data after processing using Knickpoint Finder. The results were satisfactory in terms of the correlation of dense areas of knickpoints with active lineaments and the rapidity of the identification of deformed areas. Therefore, this software tool may be considered useful in neotectonic analyses of large areas and may be applied to any area where there is DEM coverage.

  1. Statistical Analysis of Bus Networks in India

    CERN Document Server

    Chatterjee, Atanu; Ramadurai, Gitakrishnan

    2015-01-01

    Through the past decade the field of network science has established itself as a common ground for the cross-fertilization of exciting inter-disciplinary studies which has motivated researchers to model almost every physical system as an interacting network consisting of nodes and links. Although public transport networks such as airline and railway networks have been extensively studied, the status of bus networks still remains in obscurity. In developing countries like India, where bus networks play an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer some of the basic questions on its evolution, growth, robustness and resiliency. In this paper, we model the bus networks of major Indian cities as graphs in \\textit{L}-space, and evaluate their various statistical properties using concepts from network science. Our analysis reveals a wide spectrum of network topology with the common underlying feature of small-world property. We observe tha...

  2. A GIS Tool for simulating Nitrogen transport along schematic Network

    Science.gov (United States)

    Tavakoly, A. A.; Maidment, D. R.; Yang, Z.; Whiteaker, T.; David, C. H.; Johnson, S.

    2012-12-01

    An automated method called the Arc Hydro Schematic Processor has been developed for water process computation on schematic networks formed from the NHDPlus and similar GIS river networks. The sechemtaic network represents the hydrologic feature on the ground and is a network of links and nodes. SchemaNodes show hydrologic features, such as catchments or stream junctions. SchemaLinks prescripe the connections between nodes. The schematic processor uses the schematic network to pass informatin through a watershed and move water or pollutants dwonstream. In addition, the schematic processor has a capability to use additional programming applied to the passed and/or received values and manipulating data trough network. This paper describes how the schemtic processor can be used to simulate nitrogen transport and transformation on river networks. For this purpose the nitrogen loads is estimated on the NHDPlus river network using the Schematic Processor coupled with the river routing model for the Texas Gulf Coast Hydrologic Region.

  3. Egocentric social network analysis of pathological gambling.

    Science.gov (United States)

    Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S

    2013-03-01

    To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.

  4. Cohesion network analysis of CSCL participation.

    Science.gov (United States)

    Dascalu, Mihai; McNamara, Danielle S; Trausan-Matu, Stefan; Allen, Laura K

    2017-04-13

    The broad use of computer-supported collaborative-learning (CSCL) environments (e.g., instant messenger-chats, forums, blogs in online communities, and massive open online courses) calls for automated tools to support tutors in the time-consuming process of analyzing collaborative conversations. In this article, the authors propose and validate the cohesion network analysis (CNA) model, housed within the ReaderBench platform. CNA, grounded in theories of cohesion, dialogism, and polyphony, is similar to social network analysis (SNA), but it also considers text content and discourse structure and, uniquely, uses automated cohesion indices to generate the underlying discourse representation. Thus, CNA enhances the power of SNA by explicitly considering semantic cohesion while modeling interactions between participants. The primary purpose of this article is to describe CNA analysis and to provide a proof of concept, by using ten chat conversations in which multiple participants debated the advantages of CSCL technologies. Each participant's contributions were human-scored on the basis of their relevance in terms of covering the central concepts of the conversation. SNA metrics, applied to the CNA sociogram, were then used to assess the quality of each member's degree of participation. The results revealed that the CNA indices were strongly correlated to the human evaluations of the conversations. Furthermore, a stepwise regression analysis indicated that the CNA indices collectively predicted 54% of the variance in the human ratings of participation. The results provide promising support for the use of automated computational assessments of collaborative participation and of individuals' degrees of active involvement in CSCL environments.

  5. Satellite image analysis using neural networks

    Science.gov (United States)

    Sheldon, Roger A.

    1990-01-01

    The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

  6. Sovereign public debt crisis in Europe. A network analysis

    Science.gov (United States)

    Matesanz, David; Ortega, Guillermo J.

    2015-10-01

    In this paper we analyse the evolving network structure of the quarterly public debt-to-GDP ratio from 2000 to 2014. By applying tools and concepts coming from complex systems we study the effects of the global financial crisis over public debt network connections and communities. Two main results arise from this analysis: firstly, countries public debts tend to synchronize their evolution, increasing global connectivity in the network and dramatically decreasing the number of communities. Secondly, a disruption in previous structure is observed at the time of the shock, emerging a more centralized and less diversify network topological organization which might be more prone to suffer contagion effects. This last fact is evidenced by an increasing tendency in countries of similar level of public debt to be connected between them, which we have quantified by the network assortativity.

  7. Social Network Analysis and informal trade

    DEFF Research Database (Denmark)

    Walther, Olivier

    networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...

  8. Social network analysis and supply chain management

    Directory of Open Access Journals (Sweden)

    Raúl Rodríguez Rodríguez

    2016-01-01

    Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

  9. Cmapanalysis: an extensible concept map analysis tool

    Directory of Open Access Journals (Sweden)

    Alberto J. Cañas

    2013-03-01

    Full Text Available Concept maps are used extensively as an assessment tool, and the literature is abundant with studies on the use of concept maps for assessment and on the assessment of concept maps. The assessment of concept maps can be an arduous process, in particular when assessing a large number of maps. CmapAnalysis is a software tool that facilitates performing various analysis measures on a collection of concept maps. A set of measures that consider size, quality and structure properties of the maps are included. The program is designed to be extensible, allowing users to add their own measures. The program is not intended to replace the individual evaluation of concept maps by teachers and instructors, as it does not capable of “understanding” the content of the maps. It is aimed at researchers who are looking for more general trends and measures across a large number of maps, and who can extend it with their own measures. The output of CmapAnalysis is an Excel spreadsheet that can be further analyzed.

  10. Enhancement of Local Climate Analysis Tool

    Science.gov (United States)

    Horsfall, F. M.; Timofeyeva, M. M.; Dutton, J.

    2012-12-01

    The National Oceanographic and Atmospheric Administration (NOAA) National Weather Service (NWS) will enhance its Local Climate Analysis Tool (LCAT) to incorporate specific capabilities to meet the needs of various users including energy, health, and other communities. LCAT is an online interactive tool that provides quick and easy access to climate data and allows users to conduct analyses at the local level such as time series analysis, trend analysis, compositing, correlation and regression techniques, with others to be incorporated as needed. LCAT uses principles of Artificial Intelligence in connecting human and computer perceptions on application of data and scientific techniques in multiprocessing simultaneous users' tasks. Future development includes expanding the type of data currently imported by LCAT (historical data at stations and climate divisions) to gridded reanalysis and General Circulation Model (GCM) data, which are available on global grids and thus will allow for climate studies to be conducted at international locations. We will describe ongoing activities to incorporate NOAA Climate Forecast System (CFS) reanalysis data (CFSR), NOAA model output data, including output from the National Multi Model Ensemble Prediction System (NMME) and longer term projection models, and plans to integrate LCAT into the Earth System Grid Federation (ESGF) and its protocols for accessing model output and observational data to ensure there is no redundancy in development of tools that facilitate scientific advancements and use of climate model information in applications. Validation and inter-comparison of forecast models will be included as part of the enhancement to LCAT. To ensure sustained development, we will investigate options for open sourcing LCAT development, in particular, through the University Corporation for Atmospheric Research (UCAR).

  11. mizuRoute version 1: A river network routing tool for a continental domain water resources applications

    Science.gov (United States)

    Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

    2016-01-01

    This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

  12. Web-based pre-Analysis Tools

    CERN Document Server

    Moskalets, Tetiana

    2014-01-01

    The project consists in the initial development of a web based and cloud computing services to allow students and researches to perform fast and very useful cut-based pre-analysis on a browser, using real data and official Monte-Carlo simulations (MC). Several tools are considered: ROOT files filter, JavaScript Multivariable Cross-Filter, JavaScript ROOT browser and JavaScript Scatter-Matrix Libraries. Preliminary but satisfactory results have been deployed online for test and future upgrades.

  13. Artwork Analysis Tools for VLSI Circuits.

    Science.gov (United States)

    1980-06-01

    derived frcm the art- work.i~nFo :.- Is zr Code DI t pecal Sculnfv CLA a uPICAT OP T0416 PA*6WM Dine Bftee AMA& -’M Artwork Analysis Tools for VLSI Circuits... code of the program and in pre-generated bit tables. The design rules thcmselves are not input directly into the checker. The rules were interpreted...circuit simulation is swich -level sintulation. In this type, transistors are modeled as switches that are either on or off. Fixed delays are a%.ociated

  14. 4th International Conference in Network Analysis

    CERN Document Server

    Koldanov, Petr; Pardalos, Panos

    2016-01-01

    The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The "Fourth International Conference in Network Analysis," held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis.

  15. Topology analysis of social networks extracted from literature.

    Science.gov (United States)

    Waumans, Michaël C; Nicodème, Thibaut; Bersini, Hugues

    2015-01-01

    In a world where complex networks are an increasingly important part of science, it is interesting to question how the new reading of social realities they provide applies to our cultural background and in particular, popular culture. Are authors of successful novels able to reproduce social networks faithful to the ones found in reality? Is there any common trend connecting an author's oeuvre, or a genre of fiction? Such an analysis could provide new insight on how we, as a culture, perceive human interactions and consume media. The purpose of the work presented in this paper is to define the signature of a novel's story based on the topological analysis of its social network of characters. For this purpose, an automated tool was built that analyses the dialogs in novels, identifies characters and computes their relationships in a time-dependent manner in order to assess the network's evolution over the course of the story.

  16. Topology analysis of social networks extracted from literature.

    Directory of Open Access Journals (Sweden)

    Michaël C Waumans

    Full Text Available In a world where complex networks are an increasingly important part of science, it is interesting to question how the new reading of social realities they provide applies to our cultural background and in particular, popular culture. Are authors of successful novels able to reproduce social networks faithful to the ones found in reality? Is there any common trend connecting an author's oeuvre, or a genre of fiction? Such an analysis could provide new insight on how we, as a culture, perceive human interactions and consume media. The purpose of the work presented in this paper is to define the signature of a novel's story based on the topological analysis of its social network of characters. For this purpose, an automated tool was built that analyses the dialogs in novels, identifies characters and computes their relationships in a time-dependent manner in order to assess the network's evolution over the course of the story.

  17. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  18. METHODOLOGY OF MATHEMATICAL ANALYSIS IN POWER NETWORK

    OpenAIRE

    Jerzy Szkutnik; Mariusz Kawecki

    2008-01-01

    Power distribution network analysis is taken into account. Based on correlation coefficient authors establish methodology of mathematical analysis useful in finding substations bear responsibility for power stoppage. Also methodology of risk assessment will be carried out.

  19. [Applications of elementary mode analysis in biological network and pathway analysis].

    Science.gov (United States)

    Zhao, Quanyu; Yu, Shuiyan; Shi, Jiping

    2013-06-01

    Elementary mode analysis is the widely applied tool in metabolic pathway analysis. Studies based on elementary mode analysis (EMA) were performed for both metabolic network and signal transduction network. Its analytical objective is from cell to bioreactor, and even ecological system. EMA is available to describe biological behaviors by steady state and dynamic models. Not only microorganism metabolism but also human health could be evaluated by EMA. The algorithms and software for calculating elementary mode (EM) were analyzed. The applications of EMA are reviewed such as special metabolic pathway and robustness of metabolic network, metabolic flux decomposition, metabolic flux analysis at steady state, dynamic model and bioprocess simulation, network structure and regulation, strain design and signal transduction network. Solving combinatorial explosion, exploring the relations between EM and metabolic regulation, and improving the algorithm efficiency of strain design are important issues of EMA in future.

  20. Setup Analysis: Combining SMED with Other Tools

    Directory of Open Access Journals (Sweden)

    Stadnicka Dorota

    2015-02-01

    Full Text Available The purpose of this paper is to propose the methodology for the setup analysis, which can be implemented mainly in small and medium enterprises which are not convinced to implement the setups development. The methodology was developed after the research which determined the problem. Companies still have difficulties with a long setup time. Many of them do nothing to decrease this time. A long setup is not a sufficient reason for companies to undertake any actions towards the setup time reduction. To encourage companies to implement SMED it is essential to make some analyses of changeovers in order to discover problems. The methodology proposed can really encourage the management to take a decision about the SMED implementation, and that was verified in a production company. The setup analysis methodology is made up of seven steps. Four of them concern a setups analysis in a chosen area of a company, such as a work stand which is a bottleneck with many setups. The goal is to convince the management to begin actions concerning the setups improvement. The last three steps are related to a certain setup and, there, the goal is to reduce a setup time and the risk of problems which can appear during the setup. In this paper, the tools such as SMED, Pareto analysis, statistical analysis, FMEA and other were used.

  1. Simulated, Emulated, and Physical Investigative Analysis (SEPIA) of networked systems.

    Energy Technology Data Exchange (ETDEWEB)

    Burton, David P.; Van Leeuwen, Brian P.; McDonald, Michael James; Onunkwo, Uzoma A.; Tarman, Thomas David; Urias, Vincent E.

    2009-09-01

    This report describes recent progress made in developing and utilizing hybrid Simulated, Emulated, and Physical Investigative Analysis (SEPIA) environments. Many organizations require advanced tools to analyze their information system's security, reliability, and resilience against cyber attack. Today's security analysis utilize real systems such as computers, network routers and other network equipment, computer emulations (e.g., virtual machines) and simulation models separately to analyze interplay between threats and safeguards. In contrast, this work developed new methods to combine these three approaches to provide integrated hybrid SEPIA environments. Our SEPIA environments enable an analyst to rapidly configure hybrid environments to pass network traffic and perform, from the outside, like real networks. This provides higher fidelity representations of key network nodes while still leveraging the scalability and cost advantages of simulation tools. The result is to rapidly produce large yet relatively low-cost multi-fidelity SEPIA networks of computers and routers that let analysts quickly investigate threats and test protection approaches.

  2. Neural networks as a tool for unit commitment

    DEFF Research Database (Denmark)

    Rønne-Hansen, Peter; Rønne-Hansen, Jan

    1991-01-01

    Some of the fundamental problems when solving the power system unit commitment problem by means of neural networks have been attacked. It has been demonstrated for a small example that neural networks might be a viable alternative. Some of the major problems solved in this initiating phase form...

  3. Auditory Display as a Tool for Teaching Network Intrusion Detection

    Directory of Open Access Journals (Sweden)

    M.A. Garcia-Ruiz

    2008-06-01

    Full Text Available Teaching network intrusion detection, or NID(the identification of violations of a security policy in acomputer network is a challenging task, because studentsneed to analyze many data from network logs and in realtime to identify patterns of network attacks, making theseactivities visually tiring. This paper describes an ongoingresearch concerned with designing and applying sounds thatrepresent meaningful information in interfaces(sonification to support teaching of NID. An usability testwas conducted with engineering students. Natural soundeffects (auditory icons and musical sounds (earcons wereused to represent network attacks. A post-activityquestionnaire showed that most students preferred auditoryicons for analyzing NID, and all of them were veryinterested in the design and application of sonifications.

  4. Differential dependency network analysis to identify condition-specific topological changes in biological networks.

    Science.gov (United States)

    Zhang, Bai; Li, Huai; Riggins, Rebecca B; Zhan, Ming; Xuan, Jianhua; Zhang, Zhen; Hoffman, Eric P; Clarke, Robert; Wang, Yue

    2009-02-15

    Significant efforts have been made to acquire data under different conditions and to construct static networks that can explain various gene regulation mechanisms. However, gene regulatory networks are dynamic and condition-specific; under different conditions, networks exhibit different regulation patterns accompanied by different transcriptional network topologies. Thus, an investigation on the topological changes in transcriptional networks can facilitate the understanding of cell development or provide novel insights into the pathophysiology of certain diseases, and help identify the key genetic players that could serve as biomarkers or drug targets. Here, we report a differential dependency network (DDN) analysis to detect statistically significant topological changes in the transcriptional networks between two biological conditions. We propose a local dependency model to represent the local structures of a network by a set of conditional probabilities. We develop an efficient learning algorithm to learn the local dependency model using the Lasso technique. A permutation test is subsequently performed to estimate the statistical significance of each learned local structure. In testing on a simulation dataset, the proposed algorithm accurately detected all the genes with network topological changes. The method was then applied to the estrogen-dependent T-47D estrogen receptor-positive (ER+) breast cancer cell line datasets and human and mouse embryonic stem cell datasets. In both experiments using real microarray datasets, the proposed method produced biologically meaningful results. We expect DDN to emerge as an important bioinformatics tool in transcriptional network analyses. While we focus specifically on transcriptional networks, the DDN method we introduce here is generally applicable to other biological networks with similar characteristics. The DDN MATLAB toolbox and experiment data are available at http://www.cbil.ece.vt.edu/software.htm.

  5. P2PStudio - Monitoring, Controlling and Visualization Tool for Peer-to-Peer Networks Research

    OpenAIRE

    Kotilainen, Niko; Vapa, Mikko; Auvinen, Annemari; Weber, Matthieu; Vuori, Jarkko

    2006-01-01

    Peer-to-Peer Studio has been developed as a monitoring, controlling and visualization tool for peer-to-peer networks. It uses a centralized architecture to gather events from a peer-to-peer network and can be used to visualize network topology and to send different commands to individual peer-to-peer nodes. The tool has been used with Chedar Peer-to-Peer network to study the behavior of different peer-to-peer resource discovery and topology management algorithms and for visualizing the result...

  6. Weighted Complex Network Analysis of Pakistan Highways

    Directory of Open Access Journals (Sweden)

    Yasir Tariq Mohmand

    2013-01-01

    Full Text Available The structure and properties of public transportation networks have great implications in urban planning, public policies, and infectious disease control. This study contributes a weighted complex network analysis of travel routes on the national highway network of Pakistan. The network is responsible for handling 75 percent of the road traffic yet is largely inadequate, poor, and unreliable. The highway network displays small world properties and is assortative in nature. Based on the betweenness centrality of the nodes, the most important cities are identified as this could help in identifying the potential congestion points in the network. Keeping in view the strategic location of Pakistan, such a study is of practical importance and could provide opportunities for policy makers to improve the performance of the highway network.

  7. Predictive structural dynamic network analysis.

    Science.gov (United States)

    Chen, Rong; Herskovits, Edward H

    2015-04-30

    Classifying individuals based on magnetic resonance data is an important task in neuroscience. Existing brain network-based methods to classify subjects analyze data from a cross-sectional study and these methods cannot classify subjects based on longitudinal data. We propose a network-based predictive modeling method to classify subjects based on longitudinal magnetic resonance data. Our method generates a dynamic Bayesian network model for each group which represents complex spatiotemporal interactions among brain regions, and then calculates a score representing that subject's deviation from expected network patterns. This network-derived score, along with other candidate predictors, are used to construct predictive models. We validated the proposed method based on simulated data and the Alzheimer's Disease Neuroimaging Initiative study. For the Alzheimer's Disease Neuroimaging Initiative study, we built a predictive model based on the baseline biomarker characterizing the baseline state and the network-based score which was constructed based on the state transition probability matrix. We found that this combined model achieved 0.86 accuracy, 0.85 sensitivity, and 0.87 specificity. For the Alzheimer's Disease Neuroimaging Initiative study, the model based on the baseline biomarkers achieved 0.77 accuracy. The accuracy of our model is significantly better than the model based on the baseline biomarkers (p-value=0.002). We have presented a method to classify subjects based on structural dynamic network model based scores. This method is of great importance to distinguish subjects based on structural network dynamics and the understanding of the network architecture of brain processes and disorders. Copyright © 2015 Elsevier B.V. All rights reserved.

  8. Automated Steel Cleanliness Analysis Tool (ASCAT)

    Energy Technology Data Exchange (ETDEWEB)

    Gary Casuccio (RJ Lee Group); Michael Potter (RJ Lee Group); Fred Schwerer (RJ Lee Group); Dr. Richard J. Fruehan (Carnegie Mellon University); Dr. Scott Story (US Steel)

    2005-12-30

    The objective of this study was to develop the Automated Steel Cleanliness Analysis Tool (ASCATTM) to permit steelmakers to evaluate the quality of the steel through the analysis of individual inclusions. By characterizing individual inclusions, determinations can be made as to the cleanliness of the steel. Understanding the complicating effects of inclusions in the steelmaking process and on the resulting properties of steel allows the steel producer to increase throughput, better control the process, reduce remelts, and improve the quality of the product. The ASCAT (Figure 1) is a steel-smart inclusion analysis tool developed around a customized next-generation computer controlled scanning electron microscopy (NG-CCSEM) hardware platform that permits acquisition of inclusion size and composition data at a rate never before possible in SEM-based instruments. With built-in customized ''intelligent'' software, the inclusion data is automatically sorted into clusters representing different inclusion types to define the characteristics of a particular heat (Figure 2). The ASCAT represents an innovative new tool for the collection of statistically meaningful data on inclusions, and provides a means of understanding the complicated effects of inclusions in the steel making process and on the resulting properties of steel. Research conducted by RJLG with AISI (American Iron and Steel Institute) and SMA (Steel Manufactures of America) members indicates that the ASCAT has application in high-grade bar, sheet, plate, tin products, pipes, SBQ, tire cord, welding rod, and specialty steels and alloys where control of inclusions, whether natural or engineered, are crucial to their specification for a given end-use. Example applications include castability of calcium treated steel; interstitial free (IF) degasser grade slag conditioning practice; tundish clogging and erosion minimization; degasser circulation and optimization; quality assessment

  9. 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 ).

  10. International Assistance for Low-Emission Development Planning: Coordinated Low Emissions Assistance Network (CLEAN) Inventory of Activities and Tools--Preliminary Trends

    Energy Technology Data Exchange (ETDEWEB)

    Cox, S.; Benioff, R.

    2011-05-01

    The Coordinated Low Emissions Assistance Network (CLEAN) is a voluntary network of international practitioners supporting low-emission planning in developing countries. The network seeks to improve quality of support through sharing project information, tools, best practices and lessons, and by fostering harmonized assistance. CLEAN has developed an inventory to track and analyze international technical support and tools for low-carbon planning activities in developing countries. This paper presents a preliminary analysis of the inventory to help identify trends in assistance activities and tools available to support developing countries with low-emission planning.

  11. Simplified building energy analysis tool for architects

    Science.gov (United States)

    Chaisuparasmikul, Pongsak

    Energy Modeler is an energy software program designed to study the relative change of energy uses (heating, cooling, and lighting loads) in different architectural design schemes. This research focuses on developing a tool to improve energy efficiency of the built environment. The research studied the impact of different architectural design response for two distinct global climates: temperate and tropical climatic zones. This energy-based interfacing program is intended to help architects, engineers, educators, students, building designers, major consumers of architectural services, and other professionals whose work interfaces with that of architects, perceive, quickly visualize, and compare energy performance and savings of different design schemes. The buildings in which we live or work have a great impact on our natural environment. Energy savings and consumption reductions in our buildings probably are the best indications of solutions to help environmental sustainability; by reducing the depletion of the world's fossil fuel (oil, natural gas, coal etc.). Architects when they set about designing an environmentally responsive building for an owner or the public, often lack the energy-based information and design tools to tell them whether the building loads and energy consumption are very responsive to the modifications that they made. Buildings are dynamic in nature and changeable over time, with many design variables involved. Architects really need energy-based rules or tools to assist them in the design process. Energy efficient design for sustainable solutions requires attention throughout the design process and is very related to architectural solutions. Early involvement is the only guaranteed way of properly considering fundamental building design issues related to building site, form and exposure. The research presents the methodology and process, which leads to the discussion of the research findings. The innovative work is to make these tools

  12. Analysis of machining and machine tools

    CERN Document Server

    Liang, Steven Y

    2016-01-01

    This book delivers the fundamental science and mechanics of machining and machine tools by presenting systematic and quantitative knowledge in the form of process mechanics and physics. It gives readers a solid command of machining science and engineering, and familiarizes them with the geometry and functionality requirements of creating parts and components in today’s markets. The authors address traditional machining topics, such as: single and multiple point cutting processes grinding components accuracy and metrology shear stress in cutting cutting temperature and analysis chatter They also address non-traditional machining, such as: electrical discharge machining electrochemical machining laser and electron beam machining A chapter on biomedical machining is also included. This book is appropriate for advanced undergraduate and graduate mechani cal engineering students, manufacturing engineers, and researchers. Each chapter contains examples, exercises and their solutions, and homework problems that re...

  13. Wavelet bicoherence: A new turbulence analysis tool

    Energy Technology Data Exchange (ETDEWEB)

    van Milligen, B.P.; Sanchez, E.; Estrada, T.; Hidalgo, C.; Branas, B. [Asociacion EURATOM-CIEMAT, Madrid (Spain); Carreras, B. [Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831 (United States); Garcia, L. [Universidad Carlos III, Madrid (Spain)

    1995-08-01

    A recently introduced tool for the analysis of turbulence, wavelet bicoherence [van Milligen, Hidalgo, and Sanchez, Phys. Rev. Lett. {bold 16}, 395 (1995)], is investigated. It is capable of detecting phase coupling---nonlinear interactions of the lowest (quadratic) order---with time resolution. To demonstrate its potential, it is applied to numerical models of chaos and turbulence and to real measurements. It detected the coupling interaction between two coupled van der Pol oscillators. When applied to a model of drift wave turbulence relevant to plasma physics, it detected a highly localized coherent structure. Analyzing reflectometry measurements made in fusion plasmas, it detected temporal intermittency and a strong increase in nonlinear phase coupling coinciding with the L/H (low-to-high confinement mode) transition. {copyright} {ital 1995} {ital American} {ital Institute} {ital of} {ital Physics}.

  14. Using the General Mission Analysis Tool (GMAT)

    Science.gov (United States)

    Hughes, Steven P.; Conway, Darrel J.; Parker, Joel

    2017-01-01

    This is a software tutorial and presentation demonstrating the application of the General Mission Analysis Tool (GMAT). These slides will be used to accompany the demonstration. The demonstration discusses GMAT basics, then presents a detailed example of GMAT application to the Transiting Exoplanet Survey Satellite (TESS) mission. This talk is a combination of existing presentations and material; system user guide and technical documentation; a GMAT basics and overview, and technical presentations from the TESS projects on their application of GMAT to critical mission design. The GMAT basics slides are taken from the open source training material. The TESS slides are a streamlined version of the CDR package provided by the project with SBU and ITAR data removed by the TESS project. Slides for navigation and optimal control are borrowed from system documentation and training material.

  15. Industrial entrepreneurial network: Structural and functional analysis

    Science.gov (United States)

    Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.

    2016-12-01

    Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.

  16. Social networking as an advertising tool in Russia and abroad

    Directory of Open Access Journals (Sweden)

    Ageeva Y. A.

    2016-01-01

    Full Text Available This study contrasts the behavioural patterns of users on Facebook with those on VKontakte using data collected by Facebook and a survey of Russian VKontakte users. The authors analyse the key differences between the two popular social networks, including what users perceived to be the most attractive options, the amount of time spent online and attitudes toward advertising. The results have been used to evaluate the potential of social networks (SMM for business promotion in Russia.

  17. Cost analysis and estimating tools and techniques

    CERN Document Server

    Nussbaum, Daniel

    1990-01-01

    Changes in production processes reflect the technological advances permeat­ ing our products and services. U. S. industry is modernizing and automating. In parallel, direct labor is fading as the primary cost driver while engineering and technology related cost elements loom ever larger. Traditional, labor-based ap­ proaches to estimating costs are losing their relevance. Old methods require aug­ mentation with new estimating tools and techniques that capture the emerging environment. This volume represents one of many responses to this challenge by the cost analysis profession. The Institute of Cost Analysis (lCA) is dedicated to improving the effective­ ness of cost and price analysis and enhancing the professional competence of its members. We encourage and promote exchange of research findings and appli­ cations between the academic community and cost professionals in industry and government. The 1990 National Meeting in Los Angeles, jointly spo~sored by ICA and the National Estimating Society (NES),...

  18. 3rd International Conference on Network Analysis

    CERN Document Server

    Kalyagin, Valery; Pardalos, Panos

    2014-01-01

    This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications.  Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale...

  19. Social network analysis in medical education.

    Science.gov (United States)

    Isba, Rachel; Woolf, Katherine; Hanneman, Robert

    2017-01-01

    Humans are fundamentally social beings. The social systems within which we live our lives (families, schools, workplaces, professions, friendship groups) have a significant influence on our health, success and well-being. These groups can be characterised as networks and analysed using social network analysis. Social network analysis is a mainly quantitative method for analysing how relationships between individuals form and affect those individuals, but also how individual relationships build up into wider social structures that influence outcomes at a group level. Recent increases in computational power have increased the accessibility of social network analysis methods for application to medical education research. Social network analysis has been used to explore team-working, social influences on attitudes and behaviours, the influence of social position on individual success, and the relationship between social cohesion and power. This makes social network analysis theories and methods relevant to understanding the social processes underlying academic performance, workplace learning and policy-making and implementation in medical education contexts. Social network analysis is underused in medical education, yet it is a method that could yield significant insights that would improve experiences and outcomes for medical trainees and educators, and ultimately for patients. © 2016 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

  20. Nonprofit Organizations in Disaster Response and Management: A Network Analysis

    Directory of Open Access Journals (Sweden)

    NAIM KAPUCU

    2018-01-01

    Full Text Available This paper tracks changes in the national disaster management system with regard to the nonprofit sector by looking at the roles ascribed to nonprofit organizations in the Federal Response Plan (FRP, National Response Plan (NRP, and National Response Framework (NRF. Additionally, the data collected from news reports and organizational after action reports about the inter-organizational interactions of emergency management agencies during the September 11th attacks and Hurricane Katrina are analyzed by using network analysis tools. The findings of the study indicate that there has been an increase in the interactions of the National Voluntary Organizations Active in Disasters (NVOAD network member organizations on par with policy changes in the NRP to involve nonprofit organizations in the national disaster planning process. In addition, those organizations close to the center of the network experienced enhanced communication and resource acquisition allowing them to successfully accomplish their missions, a finding that supports the development of strong network connections.

  1. Stochastic approach to observability analysis in water networks

    Directory of Open Access Journals (Sweden)

    S. Díaz

    2016-07-01

    Full Text Available This work presents an alternative technique to the existing methods for observability analysis (OA in water networks, which is a prior essential step for the implementation of state estimation (SE techniques within such systems. The methodology presented here starts from a known hydraulic state and assumes random gaussian distributions for the uncertainty of some hydraulic variables, which is then propagated to the rest of the system. This process is repeated again to analyze the change in the network uncertainty when metering devices considered as error-free are included, based on which the network observability can be evaluated. The method’s potential is presented in an illustrative example, which shows the additional information that this methodology provides with respect to traditional OA approaches. This proposal allows a better understanding of the network and constitutes a practical tool to prioritize the location of additional meters, thus enhancing the transformation of large urban areas into actual smart cities.

  2. A Neural-Network-Based Semi-Automated Geospatial Classification Tool

    Science.gov (United States)

    Hale, R. G.; Herzfeld, U. C.

    2014-12-01

    North America's largest glacier system, the Bering Bagley Glacier System (BBGS) in Alaska, surged in 2011-2013, as shown by rapid mass transfer, elevation change, and heavy crevassing. Little is known about the physics controlling surge glaciers' semi-cyclic patterns; therefore, it is crucial to collect and analyze as much data as possible so that predictive models can be made. In addition, physical signs frozen in ice in the form of crevasses may help serve as a warning for future surges. The BBGS surge provided an opportunity to develop an automated classification tool for crevasse classification based on imagery collected from small aircraft. The classification allows one to link image classification to geophysical processes associated with ice deformation. The tool uses an approach that employs geostatistical functions and a feed-forward perceptron with error back-propagation. The connectionist-geostatistical approach uses directional experimental (discrete) variograms to parameterize images into a form that the Neural Network (NN) can recognize. In an application to preform analysis on airborne video graphic data from the surge of the BBGS, an NN was able to distinguish 18 different crevasse classes with 95 percent or higher accuracy, for over 3,000 images. Recognizing that each surge wave results in different crevasse types and that environmental conditions affect the appearance in imagery, we designed the tool's semi-automated pre-training algorithm to be adaptable. The tool can be optimized to specific settings and variables of image analysis: (airborne and satellite imagery, different camera types, observation altitude, number and types of classes, and resolution). The generalization of the classification tool brings three important advantages: (1) multiple types of problems in geophysics can be studied, (2) the training process is sufficiently formalized to allow non-experts in neural nets to perform the training process, and (3) the time required to

  3. Analysis of complex networks using aggressive abstraction.

    Energy Technology Data Exchange (ETDEWEB)

    Colbaugh, Richard; Glass, Kristin.; Willard, Gerald

    2008-10-01

    This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.

  4. Social Networking as a Tool for Lifelong Learning with Orthopedically Impaired Learners

    National Research Council Canada - National Science Library

    Metin Ersoy; Ahmet Güneyli

    2016-01-01

      This paper discusses how Turkish Cypriot orthopedically impaired learners who are living in North Cyprus use social networking as a tool for leisure and education, and to what extent they satisfy...

  5. Applying social network analysis in economic geography: framing some key analytic issues

    NARCIS (Netherlands)

    Wal, A.L.J. ter; Boschma, R.A.

    2007-01-01

    Social network analysis attracts increasing attention in economic geography. We claim social network analysis is a promising tool for empirically investigating the structure and evolution of inter-organizational interaction and knowledge flows within and across regions. However, the potential of

  6. Built Environment Analysis Tool: April 2013

    Energy Technology Data Exchange (ETDEWEB)

    Porter, C.

    2013-05-01

    This documentation describes the tool development. It was created to evaluate the effects of built environment scenarios on transportation energy and greenhouse gas (GHG) emissions. This documentation also provides guidance on how to apply the tool.

  7. Utah's Regional/Urban ANSS Seismic Network---Strategies and Tools for Quality Performance

    Science.gov (United States)

    Burlacu, R.; Arabasz, W. J.; Pankow, K. L.; Pechmann, J. C.; Drobeck, D. L.; Moeinvaziri, A.; Roberson, P. M.; Rusho, J. A.

    2007-05-01

    The University of Utah's regional/urban seismic network (224 stations recorded: 39 broadband, 87 strong-motion, 98 short-period) has become a model for locally implementing the Advanced National Seismic System (ANSS) because of successes in integrating weak- and strong-motion recording and in developing an effective real-time earthquake information system. Early achievements included implementing ShakeMap, ShakeCast, point-to- multipoint digital telemetry, and an Earthworm Oracle database, as well as in-situ calibration of all broadband and strong-motion stations and submission of all data and metadata into the IRIS DMC. Regarding quality performance, our experience as a medium-size regional network affirms the fundamental importance of basics such as the following: for data acquisition, deliberate attention to high-quality field installations, signal quality, and computer operations; for operational efficiency, a consistent focus on professional project management and human resources; and for customer service, healthy partnerships---including constant interactions with emergency managers, engineers, public policy-makers, and other stakeholders as part of an effective state earthquake program. (Operational cost efficiencies almost invariably involve trade-offs between personnel costs and the quality of hardware and software.) Software tools that we currently rely on for quality performance include those developed by UUSS (e.g., SAC and shell scripts for estimating local magnitudes) and software developed by other organizations such as: USGS (Earthworm), University of Washington (interactive analysis software), ISTI (SeisNetWatch), and IRIS (PDCC, BUD tools). Although there are many pieces, there is little integration. One of the main challenges we face is the availability of a complete and coherent set of tools for automatic and post-processing to assist in achieving the goals/requirements set forth by ANSS. Taking our own network---and ANSS---to the next level

  8. The Application of Social Network Analysis to Accounting and Auditing

    DEFF Research Database (Denmark)

    Kacanski, Slobodan; Lusher, Dean

    2017-01-01

    This article aims to extend methodological possibilities for conducting research in accounting and auditing by providing an overview of how current developments in social network analysis (SNA) could serve as a powerful set of theoretical and methodological tools for this purpose. SNA focuses...... for different analyses. The example of a one-mode network between audit partners is presented, to which a number of previously outlined concepts are applied and discussed. Finally, we describe the potential of a cutting-edge statistical method for SNA, exponential random graph model (ERGM), which act...

  9. Spectrum-Based and Collaborative Network Topology Analysis and Visualization

    Science.gov (United States)

    Hu, Xianlin

    2013-01-01

    Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying network topology is very important to network analysis. In this dissertation, we study networks by…

  10. THE SMALL BODY GEOPHYSICAL ANALYSIS TOOL

    Science.gov (United States)

    Bercovici, Benjamin; McMahon, Jay

    2017-10-01

    The Small Body Geophysical Analysis Tool (SBGAT) that we are developing aims at providing scientists and mission designers with a comprehensive, easy to use, open-source analysis tool. SBGAT is meant for seamless generation of valuable simulated data originating from small bodies shape models, combined with advanced shape-modification properties.The current status of SBGAT is as follows:The modular software architecture that was specified in the original SBGAT proposal was implemented in the form of two distinct packages: a dynamic library SBGAT Core containing the data structure and algorithm backbone of SBGAT, and SBGAT Gui which wraps the former inside a VTK, Qt user interface to facilitate user/data interaction. This modular development facilitates maintenance and addi- tion of new features. Note that SBGAT Core can be utilized independently from SBGAT Gui.SBGAT is presently being hosted on a GitHub repository owned by SBGAT’s main developer. This repository is public and can be accessed at https://github.com/bbercovici/SBGAT. Along with the commented code, one can find the code documentation at https://bbercovici.github.io/sbgat-doc/index.html. This code documentation is constently updated in order to reflect new functionalities.SBGAT’s user’s manual is available at https://github.com/bbercovici/SBGAT/wiki. This document contains a comprehensive tutorial indicating how to retrieve, compile and run SBGAT from scratch.Some of the upcoming development goals are listed hereafter. First, SBGAT's dynamics module will be extented: the PGM algorithm is the only type of analysis method currently implemented. Future work will therefore consists in broadening SBGAT’s capabilities with the Spherical Harmonics Expansion of the gravity field and the calculation of YORP coefficients. Second, synthetic measurements will soon be available within SBGAT. The software should be able to generate synthetic observations of different type (radar, lightcurve, point clouds

  11. Complex Network Analysis of Guangzhou Metro

    Directory of Open Access Journals (Sweden)

    Yasir Tariq Mohmand

    2015-11-01

    Full Text Available The structure and properties of public transportation networks can provide suggestions for urban planning and public policies. This study contributes a complex network analysis of the Guangzhou metro. The metro network has 236 kilometers of track and is the 6th busiest metro system of the world. In this paper topological properties of the network are explored. We observed that the network displays small world properties and is assortative in nature. The network possesses a high average degree of 17.5 with a small diameter of 5. Furthermore, we also identified the most important metro stations based on betweenness and closeness centralities. These could help in identifying the probable congestion points in the metro system and provide policy makers with an opportunity to improve the performance of the metro system.

  12. Analysis of the experimental positron lifetime spectra by neural networks

    Directory of Open Access Journals (Sweden)

    Avdić Senada

    2003-01-01

    Full Text Available This paper deals with the analysis of experimental positron lifetime spectra in polymer materials by using various algorithms of neural networks. A method based on the use of artificial neural networks for unfolding the mean lifetime and intensity of the spectral components of simulated positron lifetime spectra was previously suggested and tested on simulated data [Pžzsitetal, Applied Surface Science, 149 (1998, 97]. In this work, the applicability of the method to the analysis of experimental positron spectra has been verified in the case of spectra from polymer materials with three components. It has been demonstrated that the backpropagation neural network can determine the spectral parameters with a high accuracy and perform the decomposi-tion of lifetimes which differ by 10% or more. The backpropagation network has not been suitable for the identification of both the parameters and the number of spectral components. Therefore, a separate artificial neural network module has been designed to solve the classification problem. Module types based on self-organizing map and learning vector quantization algorithms have been tested. The learning vector quantization algorithm was found to have better performance and reliability. A complete artificial neural network analysis tool of positron lifetime spectra has been constructed to include a spectra classification module and parameter evaluation modules for spectra with a different number of components. In this way, both flexibility and high resolution can be achieved.

  13. Performance Evaluation of 5G Millimeter-Wave Cellular Access Networks Using a Capacity-Based Network Deployment Tool

    Directory of Open Access Journals (Sweden)

    Michel Matalatala

    2017-01-01

    Full Text Available The next fifth generation (5G of wireless communication networks comes with a set of new features to satisfy the demand of data-intensive applications: millimeter-wave frequencies, massive antenna arrays, beamforming, dense cells, and so forth. In this paper, we investigate the use of beamforming techniques through various architectures and evaluate the performance of 5G wireless access networks, using a capacity-based network deployment tool. This tool is proposed and applied to a realistic area in Ghent, Belgium, to simulate realistic 5G networks that respond to the instantaneous bit rate required by the active users. The results show that, with beamforming, 5G networks require almost 15% more base stations and 4 times less power to provide more capacity to the users and the same coverage performances, in comparison with the 4G reference network. Moreover, they are 3 times more energy efficient than the 4G network and the hybrid beamforming architecture appears to be a suitable architecture for beamforming to be considered when designing a 5G cellular network.

  14. Statistical Analysis of Bus Networks in India.

    Science.gov (United States)

    Chatterjee, Atanu; Manohar, Manju; Ramadurai, Gitakrishnan

    2016-01-01

    In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future.

  15. Solar Array Verification Analysis Tool (SAVANT) Developed

    Science.gov (United States)

    Bailey, Sheila G.; Long, KIenwyn J.; Curtis, Henry B.; Gardner, Barbara; Davis, Victoria; Messenger, Scott; Walters, Robert

    1999-01-01

    Modeling solar cell performance for a specific radiation environment to obtain the end-of-life photovoltaic array performance has become both increasingly important and, with the rapid advent of new types of cell technology, more difficult. For large constellations of satellites, a few percent difference in the lifetime prediction can have an enormous economic impact. The tool described here automates the assessment of solar array on-orbit end-of-life performance and assists in the development and design of ground test protocols for different solar cell designs. Once established, these protocols can be used to calculate on-orbit end-of-life performance from ground test results. The Solar Array Verification Analysis Tool (SAVANT) utilizes the radiation environment from the Environment Work Bench (EWB) model developed by the NASA Lewis Research Center s Photovoltaic and Space Environmental Effects Branch in conjunction with Maxwell Technologies. It then modifies and combines this information with the displacement damage model proposed by Summers et al. (ref. 1) of the Naval Research Laboratory to determine solar cell performance during the course of a given mission. The resulting predictions can then be compared with flight data. The Environment WorkBench (ref. 2) uses the NASA AE8 (electron) and AP8 (proton) models of the radiation belts to calculate the trapped radiation flux. These fluxes are integrated over the defined spacecraft orbit for the duration of the mission to obtain the total omnidirectional fluence spectra. Components such as the solar cell coverglass, adhesive, and antireflective coatings can slow and attenuate the particle fluence reaching the solar cell. In SAVANT, a continuous slowing down approximation is used to model this effect.

  16. GFI Network Security and PCI Compliance Power Tools

    CERN Document Server

    Posey, Brien

    2008-01-01

    Today all companies, U.S. federal agencies, and non-profit organizations have valuable data on their servers that needs to be secured. One of the challenges for IT experts is learning how to use new products in a time-efficient manner, so that new implementations can go quickly and smoothly. Learning how to set up sophisticated products is time-consuming, and can be confusing. GFI's LANguard Network Security Scanner reports vulnerabilities so that they can be mitigated before unauthorized intruders can wreck havoc on your network. To take advantage of the best things that GFI's LANguard Networ

  17. SNAP: A General Purpose Network Analysis and Graph Mining Library.

    Science.gov (United States)

    Leskovec, Jure; Sosič, Rok

    2016-10-01

    Large networks are becoming a widely used abstraction for studying complex systems in a broad set of disciplines, ranging from social network analysis to molecular biology and neuroscience. Despite an increasing need to analyze and manipulate large networks, only a limited number of tools are available for this task. Here, we describe Stanford Network Analysis Platform (SNAP), a general-purpose, high-performance system that provides easy to use, high-level operations for analysis and manipulation of large networks. We present SNAP functionality, describe its implementational details, and give performance benchmarks. SNAP has been developed for single big-memory machines and it balances the trade-off between maximum performance, compact in-memory graph representation, and the ability to handle dynamic graphs where nodes and edges are being added or removed over time. SNAP can process massive networks with hundreds of millions of nodes and billions of edges. SNAP offers over 140 different graph algorithms that can efficiently manipulate large graphs, calculate structural properties, generate regular and random graphs, and handle attributes and meta-data on nodes and edges. Besides being able to handle large graphs, an additional strength of SNAP is that networks and their attributes are fully dynamic, they can be modified during the computation at low cost. SNAP is provided as an open source library in C++ as well as a module in Python. We also describe the Stanford Large Network Dataset, a set of social and information real-world networks and datasets, which we make publicly available. The collection is a complementary resource to our SNAP software and is widely used for development and benchmarking of graph analytics algorithms.

  18. Synthesize, optimize, analyze, repeat (SOAR): Application of neural network tools to ECG patient monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Watrous, R.; Towell, G.; Glassman, M.S. [Siemens Corporate Research, Princeton, NJ (United States)

    1995-12-31

    Results are reported from the application of tools for synthesizing, optimizing and analyzing neural networks to an ECG Patient Monitoring task. A neural network was synthesized from a rule-based classifier and optimized over a set of normal and abnormal heartbeats. The classification error rate on a separate and larger test set was reduced by a factor of 2. When the network was analyzed and reduced in size by a factor of 40%, the same level of performance was maintained.

  19. Capturing complexity: Mixing methods in the analysis of a European tobacco control policy network.

    Science.gov (United States)

    Weishaar, Heide; Amos, Amanda; Collin, Jeff

    Social network analysis (SNA), a method which can be used to explore networks in various contexts, has received increasing attention. Drawing on the development of European smoke-free policy, this paper explores how a mixed method approach to SNA can be utilised to investigate a complex policy network. Textual data from public documents, consultation submissions and websites were extracted, converted and analysed using plagiarism detection software and quantitative network analysis, and qualitative data from public documents and 35 interviews were thematically analysed. While the quantitative analysis enabled understanding of the network's structure and components, the qualitative analysis provided in-depth information about specific actors' positions, relationships and interactions. The paper establishes that SNA is suited to empirically testing and analysing networks in EU policymaking. It contributes to methodological debates about the antagonism between qualitative and quantitative approaches and demonstrates that qualitative and quantitative network analysis can offer a powerful tool for policy analysis.

  20. Topology Analysis of Social Networks Extracted from Literature

    Science.gov (United States)

    2015-01-01

    In a world where complex networks are an increasingly important part of science, it is interesting to question how the new reading of social realities they provide applies to our cultural background and in particular, popular culture. Are authors of successful novels able to reproduce social networks faithful to the ones found in reality? Is there any common trend connecting an author’s oeuvre, or a genre of fiction? Such an analysis could provide new insight on how we, as a culture, perceive human interactions and consume media. The purpose of the work presented in this paper is to define the signature of a novel’s story based on the topological analysis of its social network of characters. For this purpose, an automated tool was built that analyses the dialogs in novels, identifies characters and computes their relationships in a time-dependent manner in order to assess the network’s evolution over the course of the story. PMID:26039072

  1. Multilayer motif analysis of brain networks

    Science.gov (United States)

    Battiston, Federico; Nicosia, Vincenzo; Chavez, Mario; Latora, Vito

    2017-04-01

    In the last decade, network science has shed new light both on the structural (anatomical) and on the functional (correlations in the activity) connectivity among the different areas of the human brain. The analysis of brain networks has made possible to detect the central areas of a neural system and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on anatomical and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows us to perform an analysis of the human brain where the structural and functional layers are considered together. In this work, we describe how to classify the subgraphs of a multiplex network, and we extend the motif analysis to networks with an arbitrary number of layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, anatomical and functional, respectively, obtained from diffusion and functional magnetic resonance imaging. Results indicate that subgraphs in which the presence of a physical connection between brain areas (links at the structural layer) coexists with a non-trivial positive correlation in their activities are statistically overabundant. Finally, we investigate the existence of a reinforcement mechanism between the two layers by looking at how the probability to find a link in one layer depends on the intensity of the connection in the other one. Showing that functional connectivity is non-trivially constrained by the underlying anatomical network, our work contributes to a better understanding of the interplay between the structure and function in the human brain.

  2. SaTool - a Software Tool for Structural Analysis of Complex Automation Systems

    DEFF Research Database (Denmark)

    Blanke, Mogens; Lorentzen, Torsten

    2006-01-01

    The paper introduces SaTool, a tool for structural analysis, the use of the Matlab (R)-based implementation is presented and special features are introduced, which were motivated by industrial users. Salient features of tool are presented, including the ability to specify the behavior of a comple...

  3. Bank-firm credit network in Japan: an analysis of a bipartite network.

    Science.gov (United States)

    Marotta, Luca; Miccichè, Salvatore; Fujiwara, Yoshi; Iyetomi, Hiroshi; Aoyama, Hideaki; Gallegati, Mauro; Mantegna, Rosario N

    2015-01-01

    We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms.

  4. Development of Tools for DER Components in a Distribution Network

    DEFF Research Database (Denmark)

    Mihet-Popa, Lucian; Koch-Ciobotaru, C; Isleifsson, Fridrik Rafn

    2012-01-01

    The increasing amount of Distributed Energy Resources (DER) components into distribution networks involves the development of accurate simulation models that take into account an increasing number of factors that influence the output power from the DG systems. This paper presents two simulation m...

  5. Faculty Use of Author Identifiers and Researcher Networking Tools

    Science.gov (United States)

    Tran, Clara Y.; Lyon, Jennifer A.

    2017-01-01

    This cross-sectional survey focused on faculty use and knowledge of author identifiers and researcher networking systems, and professional use of social media, at a large state university. Results from 296 completed faculty surveys representing all disciplines (9.3% response rate) show low levels of awareness and variable resource preferences. The…

  6. Social Networking Tools to Facilitate Cross-Program Collaboration

    Science.gov (United States)

    Wallace, Paul; Howard, Barbara

    2010-01-01

    Students working on a highly collaborative project used social networking technology for community building activities as well as basic project-related communication. Requiring students to work on cross-program projects gives them real-world experience working in diverse, geographically dispersed groups. An application used at Appalachian State…

  7. STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

    Directory of Open Access Journals (Sweden)

    VanBuren Vincent

    2009-10-01

    Full Text Available Abstract Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation

  8. PyRAT - python radiography analysis tool (u)

    Energy Technology Data Exchange (ETDEWEB)

    Temple, Brian A [Los Alamos National Laboratory; Buescher, Kevin L [Los Alamos National Laboratory; Armstrong, Jerawan C [Los Alamos National Laboratory

    2011-01-14

    PyRAT is a radiography analysis tool used to reconstruction images of unknown 1-0 objects. The tool is written in Python and developed for use on LINUX and Windows platforms. The tool is capable of performing nonlinear inversions of the images with minimal manual interaction in the optimization process. The tool utilizes the NOMAD mixed variable optimization tool to perform the optimization.

  9. The Annotation, Mapping, Expression and Network (AMEN suite of tools for molecular systems biology

    Directory of Open Access Journals (Sweden)

    Primig Michael

    2008-02-01

    Full Text Available Abstract Background High-throughput genome biological experiments yield large and multifaceted datasets that require flexible and user-friendly analysis tools to facilitate their interpretation by life scientists. Many solutions currently exist, but they are often limited to specific steps in the complex process of data management and analysis and some require extensive informatics skills to be installed and run efficiently. Results We developed the Annotation, Mapping, Expression and Network (AMEN software as a stand-alone, unified suite of tools that enables biological and medical researchers with basic bioinformatics training to manage and explore genome annotation, chromosomal mapping, protein-protein interaction, expression profiling and proteomics data. The current version provides modules for (i uploading and pre-processing data from microarray expression profiling experiments, (ii detecting groups of significantly co-expressed genes, and (iii searching for enrichment of functional annotations within those groups. Moreover, the user interface is designed to simultaneously visualize several types of data such as protein-protein interaction networks in conjunction with expression profiles and cellular co-localization patterns. We have successfully applied the program to interpret expression profiling data from budding yeast, rodents and human. Conclusion AMEN is an innovative solution for molecular systems biological data analysis freely available under the GNU license. The program is available via a website at the Sourceforge portal which includes a user guide with concrete examples, links to external databases and helpful comments to implement additional functionalities. We emphasize that AMEN will continue to be developed and maintained by our laboratory because it has proven to be extremely useful for our genome biological research program.

  10. Network graph analysis and visualization with Gephi

    CERN Document Server

    Cherven, Ken

    2013-01-01

    A practical, hands-on guide, that provides you with all the tools you need to visualize and analyze your data using network graphs with Gephi.This book is for data analysts who want to intuitively reveal patterns and trends, highlight outliers, and tell stories with their data using Gephi. It is great for anyone looking to explore interactions within network datasets, whether the data comes from social media or elsewhere. It is also a valuable resource for those seeking to learn more about Gephi without being overwhelmed by technical details.

  11. Dynamic network-based epistasis analysis: Boolean examples

    Directory of Open Access Journals (Sweden)

    Eugenio eAzpeitia

    2011-12-01

    Full Text Available In this review we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the topologies of gene interactions infered. This has been acknowledged in several previous papers and reviews, but here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson (herein, classical epistasis, defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus. Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct gene interaction topologies are hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our review complements previous accounts, not

  12. Emulation Platform for Cyber Analysis of Wireless Communication Network Protocols

    Energy Technology Data Exchange (ETDEWEB)

    Van Leeuwen, Brian P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Eldridge, John M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

    2017-11-01

    Wireless networking and mobile communications is increasing around the world and in all sectors of our lives. With increasing use, the density and complexity of the systems increase with more base stations and advanced protocols to enable higher data throughputs. The security of data transported over wireless networks must also evolve with the advances in technologies enabling more capable wireless networks. However, means for analysis of the effectiveness of security approaches and implementations used on wireless networks are lacking. More specifically a capability to analyze the lower-layer protocols (i.e., Link and Physical layers) is a major challenge. An analysis approach that incorporates protocol implementations without the need for RF emissions is necessary. In this research paper several emulation tools and custom extensions that enable an analysis platform to perform cyber security analysis of lower layer wireless networks is presented. A use case of a published exploit in the 802.11 (i.e., WiFi) protocol family is provided to demonstrate the effectiveness of the described emulation platform.

  13. Parallel Enhancements of the General Mission Analysis Tool Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The General Mission Analysis Tool (GMAT) is a state of the art spacecraft mission design tool under active development at NASA's Goddard Space Flight Center (GSFC)....

  14. 1st International Conference on Network Analysis

    CERN Document Server

    Kalyagin, Valery; Pardalos, Panos

    2013-01-01

    This volume contains a selection of contributions from the "First International Conference in Network Analysis," held at the University of Florida, Gainesville, on December 14-16, 2011. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of this volume is to overcome this difficulty by collecting the major results found by the participants and combining them in one easily accessible compilation. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the...

  15. A Study on Parallel Computation Tools on Networked PCs

    Directory of Open Access Journals (Sweden)

    Heru Suhartanto

    2010-10-01

    Full Text Available Many models for natural phenomena, engineering applications and industries need powerfull computing resources to solve their problems. High Performance Computing resources were introduced by many researchers. This comes in the form of Supercomputers and with operating systems and tools for development such as parallel compiler and its library. However, these resources are  expensive for the investation and maintenance, hence people need some alternatives. Many people then introduced parallel distributed computing by using available computing resource such as PCs. Each of these PCs is treated  s a processors, hence the cluster of the PC behaves as Multiprocessors Computer. Many tools are developed for such purposes. This paper studies the peformance of the currently popular tools such as Parallel Virta\\ual Machine (PVM, Message Passing Interface (MPI, Java Remote Method Invocation (RMI and Java Common Object Request Broker Architecture (CORBA. Some experiments were conducted on a cluster of PCs, the results show significant speed up. Each of those tools are identified suitable for a certain implementation and programming purposes.

  16. Radon concentration: A tool for assessing the fracture network at ...

    African Journals Online (AJOL)

    drinie

    2003-01-01

    Jan 1, 2003 ... geothermal systems. In: Ivanovich M and Harmon RS(eds.) Uranium. Series Disequilibrium: Applications to Earth, Marine and Environ- mental Sciences. Clarendon Press, Oxford. 631-668. LEVIN M (2000 ) The radon emanation technique as a tool in ground water exploration. Borehole Water J. 46 22-26.

  17. Benchmarking selected computational gene network growing tools in context of virus-host interactions.

    Science.gov (United States)

    Taye, Biruhalem; Vaz, Candida; Tanavde, Vivek; Kuznetsov, Vladimir A; Eisenhaber, Frank; Sugrue, Richard J; Maurer-Stroh, Sebastian

    2017-07-19

    Several available online tools provide network growing functions where an algorithm utilizing different data sources suggests additional genes/proteins that should connect an input gene set into functionally meaningful networks. Using the well-studied system of influenza host interactions, we compare the network growing function of two free tools GeneMANIA and STRING and the commercial IPA for their performance of recovering known influenza A virus host factors previously identified from siRNA screens. The result showed that given small (~30 genes) or medium (~150 genes) input sets all three network growing tools detect significantly more known host factors than random human genes with STRING overall performing strongest. Extending the networks with all the three tools significantly improved the detection of GO biological processes of known host factors compared to not growing networks. Interestingly, the rate of identification of true host factors using computational network growing is equal or better to doing another experimental siRNA screening study which could also be true and applied to other biological pathways/processes.

  18. Use of Social Networks as an Educational Tool

    OpenAIRE

    Tiryakioglu, Filiz; Erzurum, Funda

    2011-01-01

    Social network, particularly Facebook, can be defined as a unique online service, platform, or area where social communication and/or social relations can be established and individuals intensely share information. This definition implies that communication specialists should have more expertise and interest in social media than any other group of experts. Based on this assumption, the present study investigated the views and attitudes of instructors in the Faculty of Communication Sciences a...

  19. Analysis tools for the interplay between genome layout and regulation.

    Science.gov (United States)

    Bouyioukos, Costas; Elati, Mohamed; Képès, François

    2016-06-06

    Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

  20. Network Anomaly Detection Based on Wavelet Analysis

    Directory of Open Access Journals (Sweden)

    Ali A. Ghorbani

    2008-11-01

    Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.

  1. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview...

  2. NNSYSID and NNCTRL Tools for system identification and control with neural networks

    DEFF Research Database (Denmark)

    Nørgaard, Magnus; Ravn, Ole; Poulsen, Niels Kjølstad

    2001-01-01

    choose among several designs such as direct inverse control, internal model control, nonlinear feedforward, feedback linearisation, optimal control, gain scheduling based on instantaneous linearisation of neural network models and nonlinear model predictive control. This article gives an overview......Two toolsets for use with MATLAB have been developed: the neural network based system identification toolbox (NNSYSID) and the neural network based control system design toolkit (NNCTRL). The NNSYSID toolbox has been designed to assist identification of nonlinear dynamic systems. It contains...... a number of nonlinear model structures based on neural networks, effective training algorithms and tools for model validation and model structure selection. The NNCTRL toolkit is an add-on to NNSYSID and provides tools for design and simulation of control systems based on neural networks. The user can...

  3. ENTVis: A Visual Analytic Tool for Entropy-Based Network Traffic Anomaly Detection.

    Science.gov (United States)

    Zhou, Fangfang; Huang, Wei; Zhao, Ying; Shi, Yang; Liang, Xing; Fan, Xiaoping

    2015-01-01

    Entropy-based traffic metrics have received substantial attention in network traffic anomaly detection because entropy can provide fine-grained metrics of traffic distribution characteristics. However, some practical issues--such as ambiguity, lack of detailed distribution information, and a large number of false positives--affect the application of entropy-based traffic anomaly detection. In this work, we introduce a visual analytic tool called ENTVis to help users understand entropy-based traffic metrics and achieve accurate traffic anomaly detection. ENTVis provides three coordinated views and rich interactions to support a coherent visual analysis on multiple perspectives: the timeline group view for perceiving situations and finding hints of anomalies, the Radviz view for clustering similar anomalies in a period, and the matrix view for understanding traffic distributions and diagnosing anomalies in detail. Several case studies have been performed to verify the usability and effectiveness of our method. A further evaluation was conducted via expert review.

  4. Trimming of mammalian transcriptional networks using network component analysis

    Directory of Open Access Journals (Sweden)

    Liao James C

    2010-10-01

    Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm

  5. Drug discovery in the era of Facebook--new tools for scientific networking.

    Science.gov (United States)

    Bailey, David S; Zanders, Edward D

    2008-10-01

    Social networking is beginning to make an impact on the drug discovery process. While bioinformatics and chemoinformatics underpin research at a scientific level, rapid communication between individual researchers across continents now allows the global exchange of ideas, tools and technologies. Networking at this level of speed and reach is quite a recent phenomenon. It facilitates the development of common interests, accelerates technology transfer and increases cooperative and competitive behaviour. In this review, we critically evaluate different web based networking approaches as effective resources for the drug discovery scientist. We also ask whether social networking sites will evolve into serious and credible resources for the drug discovery community.

  6. Evaluating a Social Network Analytic Tool to Support Outbreak Management and Contact Tracing in an Outbreak of Pertussis

    OpenAIRE

    Munene, Esther; Mottice, S.; Reid, J

    2013-01-01

    Objective To determine the feasibility and value of a social network analysis tool to support pertussis outbreak management and contact tracing in the state of Utah. Introduction Pertussis (i.e., whooping cough) is on the rise in the US. To implement effective prevention and treatment strategies, it is critical to conduct timely contact tracing and evaluate people who may have come into contact with an infected person. We describe a collaborative effort between epidemiologists and public heal...

  7. Early stage design and analysis of biorefinery networks

    DEFF Research Database (Denmark)

    Sin, Gürkan

    2013-01-01

    of the process configuration which exhibits the best performances, for a given set of economical, technical and environmental criteria. To this end, we formulate a computer-aided framework as an enabling technology for early stage design and analysis of biorefineries. The tool represents different raw materials......, different products and different available technologies and proposes a conceptual (early stage) biorefinery network. This network can then be the basis for further detailed and rigorous model-based studies. In this talk, we demonstrate the application of the tool for generating an early stage optimal......Recent work regarding biorefineries resulted in many competing concepts and technologies for conversion of renewable bio-based feedstock into many promising products including fuels, chemicals, materials, etc. The design of a biorefinery process requires, at its earlier stages, the selection...

  8. SATURN (Situational Awareness Tool for Urban Responder Networks)

    Science.gov (United States)

    2012-07-01

    section around a rear tire or the front bumper . The underlying feature is based on Histograms of Oriented Gradients (HoG) [5], but formulated at...characterized by 15 perceptual colors commonly used for describing cars in classified ads. A set of MATLAB-based tools was developed to establish...appear on the map view and are denoted by either car or person icons. If conducted with an incident, search results may be further shared among

  9. Social network analysis applied to team sports analysis

    CERN Document Server

    Clemente, Filipe Manuel; Mendes, Rui Sousa

    2016-01-01

    Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.

  10. A graph-based system for network-vulnerability analysis

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C.

    1998-06-01

    This paper presents a graph-based approach to network vulnerability analysis. The method is flexible, allowing analysis of attacks from both outside and inside the network. It can analyze risks to a specific network asset, or examine the universe of possible consequences following a successful attack. The graph-based tool can identify the set of attack paths that have a high probability of success (or a low effort cost) for the attacker. The system could be used to test the effectiveness of making configuration changes, implementing an intrusion detection system, etc. The analysis system requires as input a database of common attacks, broken into atomic steps, specific network configuration and topology information, and an attacker profile. The attack information is matched with the network configuration information and an attacker profile to create a superset attack graph. Nodes identify a stage of attack, for example the class of machines the attacker has accessed and the user privilege level he or she has compromised. The arcs in the attack graph represent attacks or stages of attacks. By assigning probabilities of success on the arcs or costs representing level-of-effort for the attacker, various graph algorithms such as shortest-path algorithms can identify the attack paths with the highest probability of success.

  11. Network graph analysis of category fluency testing.

    Science.gov (United States)

    Lerner, Alan J; Ogrocki, Paula K; Thomas, Peter J

    2009-03-01

    Category fluency is impaired early in Alzheimer disease (AD). Graph theory is a technique to analyze complex relationships in networks. Features of interest in network analysis include the number of nodes and edges, and variables related to their interconnectedness. Other properties important in network analysis are "small world properties" and "scale-free" properties. The small world property (popularized as the so-called "6 degrees of separation") arises when the majority of connections are local, but a number of connections are to distant nodes. Scale-free networks are characterized by the presence of a few nodes with many connections, and many more nodes with fewer connections. To determine if category fluency data can be analyzed using graph theory. To compare normal elderly, mild cognitive impairment (MCI) and AD network graphs, and characterize changes seen with increasing cognitive impairment. Category fluency results ("animals" recorded over 60 s) from normals (n=38), MCI (n=33), and AD (n=40) completing uniform data set evaluations were converted to network graphs of all unique cooccurring neighbors, and compared for network variables. For Normal, MCI and AD, mean clustering coefficients were 0.21, 0.22, 0.30; characteristic path lengths were 3.27, 3.17, and 2.65; small world properties decreased with increasing cognitive impairment, and all graphs showed scale-free properties. Rank correlations of the 25 commonest items ranged from 0.75 to 0.83. Filtering of low-degree nodes in normal and MCI graphs resulted in properties similar to the AD network graph. Network graph analysis is a promising technique for analyzing changes in category fluency. Our technique results in nonrandom graphs consistent with well-characterized properties for these types of graphs.

  12. Performance Analysis of 3G Communication Network

    Directory of Open Access Journals (Sweden)

    Toni Anwar

    2013-09-01

    Full Text Available In this project, third generation (3G technologies research had been carried out to design and optimization conditions for 3G network. The 3G wireless mobile communication networks are growing at an ever faster rate, and this is likely to continue in the foreseeable future. Some services such as e-mail, web browsing etc allow the transition of the network from circuit switched to packet switched operation, resulting in increased overall network performance. Higher reliability, better coverage and services, higher capacity, mobility management, and wireless multimedia are all parts of the network performance. Throughput and spectral efficiency are fundamental parameters in capacity planning for 3G cellular network deployments. This project investigates also the downlink (DL and uplink (UL throughput and spectral efficiency performance of the standard Universal Mobile Telecommunications system (UMTS system for different scenarios of user and different technologies. Power consumption comparison for different mobile technology is also discussed. The analysis can significantly help system engineers to obtain crucial performance characteristics of 3G network. At the end of the paper, coverage area of 3G from one of the mobile network in Malaysia is presented.

  13. Medical image analysis with artificial neural networks.

    Science.gov (United States)

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.

  14. Fast network centrality analysis using GPUs

    Directory of Open Access Journals (Sweden)

    Shi Zhiao

    2011-05-01

    Full Text Available Abstract Background With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs. Results We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package gpu-fan (GPU-based Fast Analysis of Networks for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks. Conclusions gpu-fan provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL at http://bioinfo.vanderbilt.edu/gpu-fan/.

  15. Kinetic analysis of complex metabolic networks

    Energy Technology Data Exchange (ETDEWEB)

    Stephanopoulos, G. [MIT, Cambridge, MA (United States)

    1996-12-31

    A new methodology is presented for the analysis of complex metabolic networks with the goal of metabolite overproduction. The objective is to locate a small number of reaction steps in a network that have maximum impact on network flux amplification and whose rate can also be increased without functional network derangement. This method extends the concepts of Metabolic Control Analysis to groups of reactions and offers the means for calculating group control coefficients as measures of the control exercised by groups of reactions on the overall network fluxes and intracellular metabolite pools. It is further demonstrated that the optimal strategy for the effective increase of network fluxes, while maintaining an uninterrupted supply of intermediate metabolites, is through the coordinated amplification of multiple (as opposed to a single) reaction steps. Satisfying this requirement invokes the concept of the concentration control to coefficient, which emerges as a critical parameter in the identification of feasible enzymatic modifications with maximal impact on the network flux. A case study of aromatic aminoacid production is provided to illustrate these concepts.

  16. HANSIS software tool for the automated analysis of HOLZ lines

    Energy Technology Data Exchange (ETDEWEB)

    Holec, D., E-mail: david.holec@unileoben.ac.at [Department of Materials Science and Metallurgy, University of Cambridge, Pembroke Street, Cambridge CB2 3QZ (United Kingdom); Sridhara Rao, D.V.; Humphreys, C.J. [Department of Materials Science and Metallurgy, University of Cambridge, Pembroke Street, Cambridge CB2 3QZ (United Kingdom)

    2009-06-15

    A software tool, named as HANSIS (HOLZ analysis), has been developed for the automated analysis of higher-order Laue zone (HOLZ) lines in convergent beam electron diffraction (CBED) patterns. With this tool, the angles and distances between the HOLZ intersections can be measured and the data can be presented graphically with a user-friendly interface. It is capable of simultaneous analysis of several HOLZ patterns and thus provides a tool for systematic studies of CBED patterns.

  17. Exploration Knowledge Sharing Networks Using Social Network Analysis Methods

    Directory of Open Access Journals (Sweden)

    Győző Attila Szilágyi

    2017-10-01

    Full Text Available Knowledge sharing within organization is one of the key factor for success. The organization, where knowledge sharing takes place faster and more efficiently, is able to adapt to changes in the market environment more successfully, and as a result, it may obtain a competitive advantage. Knowledge sharing in an organization is carried out through formal and informal human communication contacts during work. This forms a multi-level complex network whose quantitative and topological characteristics largely determine how quickly and to what extent the knowledge travels within organization. The study presents how different networks of knowledge sharing in the organization can be explored by means of network analysis methods through a case study, and which role play the properties of these networks in fast and sufficient spread of knowledge in organizations. The study also demonstrates the practical applications of our research results. Namely, on the basis of knowledge sharing educational strategies can be developed in an organization, and further, competitiveness of an organization may increase due to those strategies’ application.

  18. Using Granular-Evidence-Based Adaptive Networks for Sensitivity Analysis

    OpenAIRE

    Vališevskis, A.

    2002-01-01

    This paper considers the possibility of using adaptive networks for sensitivity analysis. Adaptive network that processes fuzzy granules is described. The adaptive network training algorithm can be used for sensitivity analysis of decision making models. Furthermore, a case study concerning sensitivity analysis is described, which shows in what way the adaptive network can be used for sensitivity analysis.

  19. A new research tool for hybrid Bayesian networks using script language

    Science.gov (United States)

    Sun, Wei; Park, Cheol Young; Carvalho, Rommel

    2011-06-01

    While continuous variables become more and more inevitable in Bayesian networks for modeling real-life applications in complex systems, there are not much software tools to support it. Popular commercial Bayesian network tools such as Hugin, and Netica etc., are either expensive or have to discretize continuous variables. In addition, some free programs existing in the literature, commonly known as BNT, GeNie/SMILE, etc, have their own advantages and disadvantages respectively. In this paper, we introduce a newly developed Java tool for model construction and inference for hybrid Bayesian networks. Via the representation power of the script language, this tool can build the hybrid model automatically based on a well defined string that follows the specific grammars. Furthermore, it implements several inference algorithms capable to accommodate hybrid Bayesian networks, including Junction Tree algorithm (JT) for conditional linear Gaussian model (CLG), and Direct Message Passing (DMP) for general hybrid Bayesian networks with CLG structure. We believe this tool will be useful for researchers in the field.

  20. A Tool for Modelling the Probability of Landslides Impacting Road Networks

    Science.gov (United States)

    Taylor, Faith E.; Santangelo, Michele; Marchesini, Ivan; Malamud, Bruce D.; Guzzetti, Fausto

    2014-05-01

    our landslide susceptibility map was adjusted to further reduce the susceptibility near each road based on the road level (primary, secondary, tertiary). For each model run, we superimposed the spatial location of landslide drops with the road network, and recorded the number, size and location of road blockages recorded, along with landslides within 50 and 100 m of the different road levels. Network analysis tools available in GRASS GIS were also applied to measure the impact upon the road network in terms of connectivity. The model was performed 100 times in a Monte-Carlo simulation for each region. Initial results show reasonable agreement between model output and the observed landslide inventories in terms of the number of road blockages. In Collazzone (length of road network = 153 km, landslide density = 5.2 landslides km-2), the median number of modelled road blockages over 100 model runs was 5 (±2.5 standard deviation) compared to the mapped inventory observed number of 5 road blockages. In Northridge (length of road network = 780 km, landslide density = 8.7 landslides km-2), the median number of modelled road blockages over 100 model runs was 108 (±17.2 standard deviation) compared to the mapped inventory observed number of 48 road blockages. As we progress with model development, we believe this semi-stochastic modelling approach will potentially aid civil protection agencies to explore different scenarios of road network potential damage as the result of different magnitude landslide triggering event scenarios.

  1. Extending Network Analysis with Social Inclusions: A Chinese Entrepreneur Building Social Capital

    NARCIS (Netherlands)

    Peverelli, P.J.; Song, L.J.W.

    2011-01-01

    Social network analysis is a highly useful tool to study the way individuals form alliances to cope with their daily tasks on the micro-level. We can map the interaction between the key persons involved into a graph, representing the social network. The result is then a snapshot of who interacts

  2. Forensic analysis of video steganography tools

    Directory of Open Access Journals (Sweden)

    Thomas Sloan

    2015-05-01

    Full Text Available Steganography is the art and science of concealing information in such a way that only the sender and intended recipient of a message should be aware of its presence. Digital steganography has been used in the past on a variety of media including executable files, audio, text, games and, notably, images. Additionally, there is increasing research interest towards the use of video as a media for steganography, due to its pervasive nature and diverse embedding capabilities. In this work, we examine the embedding algorithms and other security characteristics of several video steganography tools. We show how all feature basic and severe security weaknesses. This is potentially a very serious threat to the security, privacy and anonymity of their users. It is important to highlight that most steganography users have perfectly legal and ethical reasons to employ it. Some common scenarios would include citizens in oppressive regimes whose freedom of speech is compromised, people trying to avoid massive surveillance or censorship, political activists, whistle blowers, journalists, etc. As a result of our findings, we strongly recommend ceasing any use of these tools, and to remove any contents that may have been hidden, and any carriers stored, exchanged and/or uploaded online. For many of these tools, carrier files will be trivial to detect, potentially compromising any hidden data and the parties involved in the communication. We finish this work by presenting our steganalytic results, that highlight a very poor current state of the art in practical video steganography tools. There is unfortunately a complete lack of secure and publicly available tools, and even commercial tools offer very poor security. We therefore encourage the steganography community to work towards the development of more secure and accessible video steganography tools, and make them available for the general public. The results presented in this work can also be seen as a useful

  3. The Analysis of Duocentric Social Networks: A Primer.

    Science.gov (United States)

    Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

    2015-02-01

    Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

  4. Social network analysis of study environment

    Directory of Open Access Journals (Sweden)

    Blaženka Divjak

    2010-06-01

    Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.

  5. The Nitrogen Footprint Tool network: A multi-institution program to reduce nitrogen pollution

    Science.gov (United States)

    Castner, Elizabeth A.; Leah, Allison M.; Leary, Neal; Baron, Jill; Compton, Jana E.; Galloway, James N.; Hastings, Meredith G.; Kimiecik, Jacob; Lantz-Trissel, Jonathan; de la Riguera, Elizabeth; Ryals, Rebecca

    2017-01-01

    Anthropogenic sources of reactive nitrogen have local and global impacts on air and water quality and detrimental effects on human and ecosystem health. This paper uses the nitrogen footprint tool (NFT) to determine the amount of nitrogen (N) released as a result of institutional consumption. The sectors accounted for include food (consumption and upstream production), energy, transportation, fertilizer, research animals, and agricultural research. The NFT is then used for scenario analysis to manage and track reductions, which are driven by the consumption behaviors of both the institution itself and its constituent individuals. In this paper, the first seven completed institution nitrogen footprint results are presented. The institution NFT network aims to develop footprints for many institutions to encourage widespread upper-level management strategies that will create significant reductions in reactive nitrogen released to the environment. Energy use and food purchases are the two largest sectors contributing to institution nitrogen footprints. Ongoing efforts by institutions to reduce greenhouse gas emissions also help to reduce the nitrogen footprint, but the impact of food production on nitrogen pollution has not been directly addressed by the higher-ed sustainability community. The NFT Network found that institutions could reduce their nitrogen footprints by optimizing food purchasing to reduce consumption of animal products and minimize food waste, as well as reducing dependence on fossil fuels for energy.

  6. Tensor Fusion Network for Multimodal Sentiment Analysis

    OpenAIRE

    Zadeh, Amir; Chen, Minghai; Poria, Soujanya; Cambria, Erik; Morency, Louis-Philippe

    2017-01-01

    Multimodal sentiment analysis is an increasingly popular research area, which extends the conventional language-based definition of sentiment analysis to a multimodal setup where other relevant modalities accompany language. In this paper, we pose the problem of multimodal sentiment analysis as modeling intra-modality and inter-modality dynamics. We introduce a novel model, termed Tensor Fusion Network, which learns both such dynamics end-to-end. The proposed approach is tailored for the vola...

  7. Network analysis of eight industrial symbiosis systems

    Science.gov (United States)

    Zhang, Yan; Zheng, Hongmei; Shi, Han; Yu, Xiangyi; Liu, Gengyuan; Su, Meirong; Li, Yating; Chai, Yingying

    2016-06-01

    Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the internal structural or functional characteristics of a park. To analyze a park's structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics (density and network degree centralization) to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types: weak completeness, and two forms of strong completeness, namely "anchor tenant" mutualism and "equality-oriented" mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for "anchor tenant" mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in "equality-oriented" mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems' internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park (Shandong Lubei).

  8. Milling tool wear diagnosis by feed motor current signal using an artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Khajavi, Mehrdad Nouri; Nasernia, Ebrahim; Rostaghi, Mostafa [Dept. of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran (Iran, Islamic Republic of)

    2016-11-15

    In this paper, a Multi-layer perceptron (MLP) neural network was used to predict tool wear in face milling. For this purpose, a series of experiments was conducted using a milling machine on a CK45 work piece. Tool wear was measured by an optical microscope. To improve the accuracy and reliability of the monitoring system, tool wear state was classified into five groups, namely, no wear, slight wear, normal wear, severe wear and broken tool. Experiments were conducted with the aforementioned tool wear states, and different machining conditions and data were extracted. An increase in current amplitude was observed as the tool wear increased. Furthermore, effects of parameters such as tool wear, feed, and cut depth on motor current consumption were analyzed. Considering the complexity of the wear state classification, a multi-layer neural network was used. The root mean square of motor current, feed, cut depth, and tool rpm were chosen as the input and amount of flank wear as the output of MLP. Results showed good performance of the designed tool wear monitoring system.

  9. A statistical analysis of UK financial networks

    Science.gov (United States)

    Chu, J.; Nadarajah, S.

    2017-04-01

    In recent years, with a growing interest in big or large datasets, there has been a rise in the application of large graphs and networks to financial big data. Much of this research has focused on the construction and analysis of the network structure of stock markets, based on the relationships between stock prices. Motivated by Boginski et al. (2005), who studied the characteristics of a network structure of the US stock market, we construct network graphs of the UK stock market using same method. We fit four distributions to the degree density of the vertices from these graphs, the Pareto I, Fréchet, lognormal, and generalised Pareto distributions, and assess the goodness of fit. Our results show that the degree density of the complements of the market graphs, constructed using a negative threshold value close to zero, can be fitted well with the Fréchet and lognormal distributions.

  10. FDTD simulation tools for UWB antenna analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Brocato, Robert Wesley

    2005-02-01

    This paper describes the development of a set of software tools useful for analyzing ultra-wideband (UWB) antennas and structures. These tools are used to perform finite difference time domain (FDTD) simulation of a conical antenna with continuous wave (CW) and UWB pulsed excitations. The antenna is analyzed using spherical coordinate-based FDTD equations that are derived from first principles. The simulation results for CW excitation are compared to simulation and measured results from published sources; the results for UWB excitation are new.

  11. FDTD simulation tools for UWB antenna analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Brocato, Robert Wesley

    2004-12-01

    This paper describes the development of a set of software tools useful for analyzing ultra-wideband (UWB) antennas and structures. These tools are used to perform finite difference time domain (FDTD) simulation of a conical antenna with continuous wave (CW) and UWB pulsed excitations. The antenna is analyzed using spherical coordinate-based FDTD equations that are derived from first principles. The simulation results for CW excitation are compared to simulation and measured results from published sources; the results for UWB excitation are new.

  12. Applied and computational harmonic analysis on graphs and networks

    Science.gov (United States)

    Irion, Jeff; Saito, Naoki

    2015-09-01

    In recent years, the advent of new sensor technologies and social network infrastructure has provided huge opportunities and challenges for analyzing data recorded on such networks. In the case of data on regular lattices, computational harmonic analysis tools such as the Fourier and wavelet transforms have well-developed theories and proven track records of success. It is therefore quite important to extend such tools from the classical setting of regular lattices to the more general setting of graphs and networks. In this article, we first review basics of graph Laplacian matrices, whose eigenpairs are often interpreted as the frequencies and the Fourier basis vectors on a given graph. We point out, however, that such an interpretation is misleading unless the underlying graph is either an unweighted path or cycle. We then discuss our recent effort of constructing multiscale basis dictionaries on a graph, including the Hierarchical Graph Laplacian Eigenbasis Dictionary and the Generalized Haar-Walsh Wavelet Packet Dictionary, which are viewed as generalizations of the classical hierarchical block DCTs and the Haar-Walsh wavelet packets, respectively, to the graph setting. Finally, we demonstrate the usefulness of our dictionaries by using them to simultaneously segment and denoise 1-D noisy signals sampled on regular lattices, a problem where classical tools have difficulty.

  13. In silico Biochemical Reaction Network Analysis (IBRENA): a package for simulation and analysis of reaction networks.

    Science.gov (United States)

    Liu, Gang; Neelamegham, Sriram

    2008-04-15

    We present In silico Biochemical Reaction Network Analysis (IBRENA), a software package which facilitates multiple functions including cellular reaction network simulation and sensitivity analysis (both forward and adjoint methods), coupled with principal component analysis, singular-value decomposition and model reduction. The software features a graphical user interface that aids simulation and plotting of in silico results. While the primary focus is to aid formulation, testing and reduction of theoretical biochemical reaction networks, the program can also be used for analysis of high-throughput genomic and proteomic data. The software package, manual and examples are available at http://www.eng.buffalo.edu/~neel/ibrena

  14. Friending Adolescents on Social Networking Websites: A Feasible Research Tool.

    Science.gov (United States)

    Brockman, Libby N; Christakis, Dimitri A; Moreno, Megan A

    2014-01-01

    Social networking sites (SNSs) are increasingly used for research. This paper reports on two studies examining the feasibility of friending adolescents on SNSs for research purposes. Study 1 took place on www.MySpace.com where public profiles belonging to 18-year-old adolescents received a friend request from an unknown physician. Study 2 took place on www.Facebook.com where college freshmen from two US universities, enrolled in an ongoing research study, received a friend request from a known researcher's profile. Acceptance and retention rates of friend requests were calculated for both studies. Study 1: 127 participants received a friend request; participants were 18 years-old, 62.2% male and 51.8% Caucasian. 49.6% accepted the friend request. After 9 months, 76% maintained the online friendship, 12.7% defriended the study profile and 11% deactivated their profile. Study 2: 338 participants received a friend request; participants were 18 years-old, 56.5% female and 75.1% Caucasian. 99.7% accepted the friend request. Over 12 months, 3.3% defriended the study profile and 4.1% deactivated their profile. These actions were often temporary; the overall 12-month friendship retention rate was 96.1%. Friending adolescents on SNSs is feasible and friending adolescents from a familiar profile may be more effective for maintaining online friendship with research participants over time.

  15. Mapping, Awareness, and Virtualization Network Administrator Training Tool (MAVNATT) Architecture and Framework

    Science.gov (United States)

    2015-06-01

    exporting, and sharing? 2. What are suitable libraries and application program interfaces (APIs) that can be utilized to create a graphical user...capable of all network monitoring areas and can also perform integrated network discovery with SNMP, LDAP, ICMP, SSH , and other protocols [24], [27], [28...based Mapping Yes (ICMP, SNMP, WMI) Yes (Plugin Dependent) Yes (ICMP, SNMP, WMI, LDAP, SSH ) 24 3. Virtualization Virtualization tools

  16. Organizational network analysis for two networks in the Washington State Department of Transportation.

    Science.gov (United States)

    2010-10-01

    Organizational network analysis (ONA) consists of gathering data on information sharing and : connectivity in a group, calculating network measures, creating network maps, and using this : information to analyze and improve the functionality of the g...

  17. Buffer$--An Economic Analysis Tool

    Science.gov (United States)

    Gary Bentrup

    2007-01-01

    Buffer$ is an economic spreadsheet tool for analyzing the cost-benefits of conservation buffers by resource professionals. Conservation buffers are linear strips of vegetation managed for multiple landowner and societal objectives. The Microsoft Excel based spreadsheet can calculate potential income derived from a buffer, including income from cost-share/incentive...

  18. Developing an intelligence analysis process through social network analysis

    Science.gov (United States)

    Waskiewicz, Todd; LaMonica, Peter

    2008-04-01

    Intelligence analysts are tasked with making sense of enormous amounts of data and gaining an awareness of a situation that can be acted upon. This process can be extremely difficult and time consuming. Trying to differentiate between important pieces of information and extraneous data only complicates the problem. When dealing with data containing entities and relationships, social network analysis (SNA) techniques can be employed to make this job easier. Applying network measures to social network graphs can identify the most significant nodes (entities) and edges (relationships) and help the analyst further focus on key areas of concern. Strange developed a model that identifies high value targets such as centers of gravity and critical vulnerabilities. SNA lends itself to the discovery of these high value targets and the Air Force Research Laboratory (AFRL) has investigated several network measures such as centrality, betweenness, and grouping to identify centers of gravity and critical vulnerabilities. Using these network measures, a process for the intelligence analyst has been developed to aid analysts in identifying points of tactical emphasis. Organizational Risk Analyzer (ORA) and Terrorist Modus Operandi Discovery System (TMODS) are the two applications used to compute the network measures and identify the points to be acted upon. Therefore, the result of leveraging social network analysis techniques and applications will provide the analyst and the intelligence community with more focused and concentrated analysis results allowing them to more easily exploit key attributes of a network, thus saving time, money, and manpower.

  19. Generalized Geophysical Retrieval and Analysis Tool for Planetary Atmospheres Project

    Data.gov (United States)

    National Aeronautics and Space Administration — CPI proposes to develop an innovative, generalized retrieval algorithm and analysis tool (GRANT) that will facilitate analysis of remote sensing data from both...

  20. Phylodynamic analysis of a viral infection network

    Directory of Open Access Journals (Sweden)

    Teiichiro eShiino

    2012-07-01

    Full Text Available Viral infections by sexual and droplet transmission routes typically spread through a complex host-to-host contact network. Clarifying the transmission network and epidemiological parameters affecting the variations and dynamics of a specific pathogen is a major issue in the control of infectious diseases. However, conventional methods such as interview and/or classical phylogenetic analysis of viral gene sequences have inherent limitations and often fail to detect infectious clusters and transmission connections. Recent improvements in computational environments now permit the analysis of large datasets. In addition, novel analytical methods have been developed that serve to infer the evolutionary dynamics of virus genetic diversity using sample date information and sequence data. This type of framework, termed phylodynamics, helps connect some of the missing links on viral transmission networks, which are often hard to detect by conventional methods of epidemiology. With sufficient number of sequences available, one can use this new inference method to estimate theoretical epidemiological parameters such as temporal distributions of the primary infection, fluctuation of the pathogen population size, basic reproductive number, and the mean time span of disease infectiousness. Transmission networks estimated by this framework often have the properties of a scale-free network, which are characteristic of infectious and social communication processes. Network analysis based on phylodynamics has alluded to various suggestions concerning the infection dynamics associated with a given community and/or risk behavior. In this review, I will summarize the current methods available for identifying the transmission network using phylogeny, and present an argument on the possibilities of applying the scale-free properties to these existing frameworks.

  1. General Mission Analysis Tool (GMAT) User's Guide (Draft)

    Science.gov (United States)

    Hughes, Steven P.

    2007-01-01

    4The General Mission Analysis Tool (GMAT) is a space trajectory optimization and mission analysis system. This document is a draft of the users guide for the tool. Included in the guide is information about Configuring Objects/Resources, Object Fields: Quick Look-up Tables, and Commands and Events.

  2. FEAT - FAILURE ENVIRONMENT ANALYSIS TOOL (UNIX VERSION)

    Science.gov (United States)

    Pack, G.

    1994-01-01

    The Failure Environment Analysis Tool, FEAT, enables people to see and better understand the effects of failures in a system. FEAT uses digraph models to determine what will happen to a system if a set of failure events occurs and to identify the possible causes of a selected set of failures. Failures can be user-selected from either engineering schematic or digraph model graphics, and the effects or potential causes of the failures will be color highlighted on the same schematic or model graphic. As a design tool, FEAT helps design reviewers understand exactly what redundancies have been built into a system and where weaknesses need to be protected or designed out. A properly developed digraph will reflect how a system functionally degrades as failures accumulate. FEAT is also useful in operations, where it can help identify causes of failures after they occur. Finally, FEAT is valuable both in conceptual development and as a training aid, since digraphs can identify weaknesses in scenarios as well as hardware. Digraphs models for use with FEAT are generally built with the Digraph Editor, a Macintosh-based application which is distributed with FEAT. The Digraph Editor was developed specifically with the needs of FEAT users in mind and offers several time-saving features. It includes an icon toolbox of components required in a digraph model and a menu of functions for manipulating these components. It also offers FEAT users a convenient way to attach a formatted textual description to each digraph node. FEAT needs these node descriptions in order to recognize nodes and propagate failures within the digraph. FEAT users store their node descriptions in modelling tables using any word processing or spreadsheet package capable of saving data to an ASCII text file. From within the Digraph Editor they can then interactively attach a properly formatted textual description to each node in a digraph. Once descriptions are attached to them, a selected set of nodes can be

  3. Logical Modeling and Dynamical Analysis of Cellular Networks.

    Science.gov (United States)

    Abou-Jaoudé, Wassim; Traynard, Pauline; Monteiro, Pedro T; Saez-Rodriguez, Julio; Helikar, Tomáš; Thieffry, Denis; Chaouiya, Claudine

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.

  4. Classification and Analysis of Computer Network Traffic

    DEFF Research Database (Denmark)

    Bujlow, Tomasz

    2014-01-01

    for traffic classification, which can be used for nearly real-time processing of big amounts of data using affordable CPU and memory resources. Other questions are related to methods for real-time estimation of the application Quality of Service (QoS) level based on the results obtained by the traffic......Traffic monitoring and analysis can be done for multiple different reasons: to investigate the usage of network resources, assess the performance of network applications, adjust Quality of Service (QoS) policies in the network, log the traffic to comply with the law, or create realistic models...... classifier. This thesis is focused on topics connected with traffic classification and analysis, while the work on methods for QoS assessment is limited to defining the connections with the traffic classification and proposing a general algorithm. We introduced the already known methods for traffic...

  5. Bandwidth Analysis of Smart Meter Network Infrastructure

    DEFF Research Database (Denmark)

    Balachandran, Kardi; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup

    2014-01-01

    Advanced Metering Infrastructure (AMI) is a net-work infrastructure in Smart Grid, which links the electricity customers to the utility company. This network enables smart services by making it possible for the utility company to get an overview of their customers power consumption and also control...... to utilize smart meters and which existing broadband network technologies can facilitate this smart meter service. Initially, scenarios for smart meter infrastructure are identified. The paper defines abstraction models which cover the AMI scenarios. When the scenario has been identified a general overview...... of the bandwidth requirements are analysed. For this analysis the assumptions and limitations are defined. The results obtained by the analysis show, that the amount of data collected and transferred by a smart meter is very low compared to the available bandwidth of most internet connections. The results show...

  6. Statistical methods for the forensic analysis of striated tool marks

    Energy Technology Data Exchange (ETDEWEB)

    Hoeksema, Amy Beth [Iowa State Univ., Ames, IA (United States)

    2013-01-01

    In forensics, fingerprints can be used to uniquely identify suspects in a crime. Similarly, a tool mark left at a crime scene can be used to identify the tool that was used. However, the current practice of identifying matching tool marks involves visual inspection of marks by forensic experts which can be a very subjective process. As a result, declared matches are often successfully challenged in court, so law enforcement agencies are particularly interested in encouraging research in more objective approaches. Our analysis is based on comparisons of profilometry data, essentially depth contours of a tool mark surface taken along a linear path. In current practice, for stronger support of a match or non-match, multiple marks are made in the lab under the same conditions by the suspect tool. We propose the use of a likelihood ratio test to analyze the difference between a sample of comparisons of lab tool marks to a field tool mark, against a sample of comparisons of two lab tool marks. Chumbley et al. (2010) point out that the angle of incidence between the tool and the marked surface can have a substantial impact on the tool mark and on the effectiveness of both manual and algorithmic matching procedures. To better address this problem, we describe how the analysis can be enhanced to model the effect of tool angle and allow for angle estimation for a tool mark left at a crime scene. With sufficient development, such methods may lead to more defensible forensic analyses.

  7. How to Generate Personal Networks: Issues and Tools for a Sociological Perspective

    OpenAIRE

    Bidart, Claire; Charbonneau, Johanne

    2012-01-01

    Document de travail, à paraître dans la revue "Field Methods" en Août 2011; Each name generator produces its own type of personal network and has its own assumptions and boundaries. Following a quick review of these tools and their distinctive characteristics, we propose a new name generator to study the link between sociability and socialization. The sociological point of view leads to building large networks rooted in the social contexts of everyday life rather than networks focused on spec...

  8. Simulation technologies in networking and communications selecting the best tool for the test

    CERN Document Server

    Pathan, Al-Sakib Khan; Khan, Shafiullah

    2014-01-01

    Simulation is a widely used mechanism for validating the theoretical models of networking and communication systems. Although the claims made based on simulations are considered to be reliable, how reliable they really are is best determined with real-world implementation trials.Simulation Technologies in Networking and Communications: Selecting the Best Tool for the Test addresses the spectrum of issues regarding the different mechanisms related to simulation technologies in networking and communications fields. Focusing on the practice of simulation testing instead of the theory, it presents

  9. A statistical framework for differential network analysis from microarray data

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

    underlying biochemical pathways. Differential network analysis with appropriate connectivity scores is a useful tool in exploring changes in network structures under different biological conditions. An R package of our tests can be downloaded from the supplementary website http://www.somnathdatta.org/Supp/DNA.

  10. Diversity Performance Analysis on Multiple HAP Networks

    Directory of Open Access Journals (Sweden)

    Feihong Dong

    2015-06-01

    Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.

  11. Social Network Analysis Reveals the Negative Effects of Attention-Deficit/Hyperactivity Disorder (ADHD) Symptoms on Friend-Based Student Networks

    OpenAIRE

    Jun Won Kim; Bung-Nyun Kim; Johanna Inhyang Kim; Young Sik Lee; Kyung Joon Min; Hyun-Jin Kim; Jaewon Lee

    2015-01-01

    Introduction Social network analysis has emerged as a promising tool in modern social psychology. This method can be used to examine friend-based social relationships in terms of network theory, with nodes representing individual students and ties representing relationships between students (e.g., friendships and kinships). Using social network analysis, we investigated whether greater severity of ADHD symptoms is correlated with weaker peer relationships among elementary school students. Met...

  12. Source Code Review Using Static Analysis Tools

    OpenAIRE

    Moiras, Stavros; Lüders, Stefan; Tsouvelekakis, Aimilios

    2015-01-01

    Abstract Many teams at CERN, develop their own software to solve their tasks. This software may be public or it may be used for internal purposes. It is of major importance for developers to know that their software is secure. Humans are able to detect bugs and vulnerabilities but it is impossible to discover everything when they need to read hundreds’ lines of code. As a result, computer scientists have developed tools which complete efficiently and within minut...

  13. Graphical Acoustic Liner Design and Analysis Tool

    Science.gov (United States)

    Howerton, Brian M. (Inventor); Jones, Michael G. (Inventor)

    2016-01-01

    An interactive liner design and impedance modeling tool comprises software utilized to design acoustic liners for use in constrained spaces, both regularly and irregularly shaped. A graphical user interface allows the acoustic channel geometry to be drawn in a liner volume while the surface impedance calculations are updated and displayed in real-time. A one-dimensional transmission line model may be used as the basis for the impedance calculations.

  14. An Integrated Tool for System Analysis of Sample Return Vehicles

    Science.gov (United States)

    Samareh, Jamshid A.; Maddock, Robert W.; Winski, Richard G.

    2012-01-01

    The next important step in space exploration is the return of sample materials from extraterrestrial locations to Earth for analysis. Most mission concepts that return sample material to Earth share one common element: an Earth entry vehicle. The analysis and design of entry vehicles is multidisciplinary in nature, requiring the application of mass sizing, flight mechanics, aerodynamics, aerothermodynamics, thermal analysis, structural analysis, and impact analysis tools. Integration of a multidisciplinary problem is a challenging task; the execution process and data transfer among disciplines should be automated and consistent. This paper describes an integrated analysis tool for the design and sizing of an Earth entry vehicle. The current tool includes the following disciplines: mass sizing, flight mechanics, aerodynamics, aerothermodynamics, and impact analysis tools. Python and Java languages are used for integration. Results are presented and compared with the results from previous studies.

  15. Mixed Methods Analysis of Enterprise Social Networks

    DEFF Research Database (Denmark)

    Behrendt, Sebastian; Richter, Alexander; Trier, Matthias

    2014-01-01

    The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate...

  16. Nonlinear Time Series Analysis via Neural Networks

    Science.gov (United States)

    Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin

    This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.

  17. Combining morphological analysis and Bayesian networks for ...

    African Journals Online (AJOL)

    Morphological analysis (MA) and Bayesian networks (BN) are two closely related modelling methods, each of which has its advantages and disadvantages for strategic decision support modelling. MA is a method for defining, linking and evaluating problem spaces. BNs are graphical models which consist of a qualitative ...

  18. PerfAndPubToolsTools for Software Performance Analysis and Publishing of Results

    Directory of Open Access Journals (Sweden)

    Nuno Fachada

    2016-05-01

    Full Text Available PerfAndPubTools consists of a set of MATLAB/Octave functions for the post-processing and analysis of software performance benchmark data and producing associated publication quality materials.

  19. The value of the participatory network mapping tool to facilitate and evaluate coordinated action in health promotion networks: two Dutch case studies.

    Science.gov (United States)

    Wijenberg, Evianne; Wagemakers, Annemarie; Herens, Marion; Hartog, Franciska den; Koelen, Maria

    2017-08-01

    Facilitating processes for coordinated action in the field of health promotion is a challenge. Poorthuis and Bijl's (2006) Participatory Network Mapping Tool (PNMT) uses visualization and discussion to map the positions and roles of network actors, stimulate learning processes, and elicit actionable knowledge. This article describes the results from the application of the PNMT in networks of two Dutch health promotion programmes (Health Race and BeweegKuur) with the aim of determining the value of the PNMT to partners in health promotions networks. A qualitative secondary analysis (QSA) was conducted to clarify positions and roles, learning processes, and actionable knowledge of network actors in existing data sets including five group interviews of the Health Race programme and 16 individual interviews and 15 group interviews of the BeweegKuur programme. The PNMT maps both positions and roles of (missing) actors and makes successes (e.g. knowing each other) and challenges (e.g. implementing new activities) visible. Thus, the PNMT provides a starting point for discussion and reflection and eliciting actionable knowledge such as involving new actors and target populations in the programme. The PNMT contributes to the facilitation of coordinated action in health promotion networks by making positions and roles of network partners visible. In combination with dialogue and reflection the PNMT helps to elucidate factors influencing coordinated action and outcomes. The PNMT is valuable in grasping intangible aspects between actors by stimulating collective learning. These insights can be used by researchers and network actors to achieve more successful coordinated action for health promotion.

  20. Models of network reliability analysis, combinatorics, and Monte Carlo

    CERN Document Server

    Gertsbakh, Ilya B

    2009-01-01

    Unique in its approach, Models of Network Reliability: Analysis, Combinatorics, and Monte Carlo provides a brief introduction to Monte Carlo methods along with a concise exposition of reliability theory ideas. From there, the text investigates a collection of principal network reliability models, such as terminal connectivity for networks with unreliable edges and/or nodes, network lifetime distribution in the process of its destruction, network stationary behavior for renewable components, importance measures of network elements, reliability gradient, and network optimal reliability synthesis

  1. Social network analysis: Applied tool to enhance effective collaboration between child protection organisations by revealing and strengthening work relationships/Netzwerkanalyse: eine angewandte methode fur die effektive zusammenarbeit von kinderschutzorganisationen/Analiza mreze odnosa: primijenjena metoda za ucinkovitu suradnju organizacija za zastitu djece

    National Research Council Canada - National Science Library

    David, Beata

    2013-01-01

    .... The qualitative approach was complemented by social network analysis. Revealing the mechanism based on the actors' perception on how the child protection network operates, we identified and named the strengths and weaknesses of its structure...

  2. Timescale analysis of rule-based biochemical reaction networks.

    Science.gov (United States)

    Klinke, David J; Finley, Stacey D

    2012-01-01

    The flow of information within a cell is governed by a series of protein-protein interactions that can be described as a reaction network. Mathematical models of biochemical reaction networks can be constructed by repetitively applying specific rules that define how reactants interact and what new species are formed on reaction. To aid in understanding the underlying biochemistry, timescale analysis is one method developed to prune the size of the reaction network. In this work, we extend the methods associated with timescale analysis to reaction rules instead of the species contained within the network. To illustrate this approach, we applied timescale analysis to a simple receptor-ligand binding model and a rule-based model of interleukin-12 (IL-12) signaling in naïve CD4+ T cells. The IL-12 signaling pathway includes multiple protein-protein interactions that collectively transmit information; however, the level of mechanistic detail sufficient to capture the observed dynamics has not been justified based on the available data. The analysis correctly predicted that reactions associated with Janus Kinase 2 and Tyrosine Kinase 2 binding to their corresponding receptor exist at a pseudo-equilibrium. By contrast, reactions associated with ligand binding and receptor turnover regulate cellular response to IL-12. An empirical Bayesian approach was used to estimate the uncertainty in the timescales. This approach complements existing rank- and flux-based methods that can be used to interrogate complex reaction networks. Ultimately, timescale analysis of rule-based models is a computational tool that can be used to reveal the biochemical steps that regulate signaling dynamics. Copyright © 2011 American Institute of Chemical Engineers (AIChE).

  3. Large-Scale Road Network Vulnerability Analysis

    OpenAIRE

    Jenelius, Erik

    2010-01-01

    Disruptions in the transport system can have severe impacts for affected individuals, businesses and the society as a whole. In this research, vulnerability is seen as the risk of unplanned system disruptions, with a focus on large, rare events. Vulnerability analysis aims to provide decision support regarding preventive and restorative actions, ideally as an integrated part of the planning process.The thesis specifically develops the methodology for vulnerability analysis of road networks an...

  4. Computer methods in electric network analysis

    Energy Technology Data Exchange (ETDEWEB)

    Saver, P.; Hajj, I.; Pai, M.; Trick, T.

    1983-06-01

    The computational algorithms utilized in power system analysis have more than just a minor overlap with those used in electronic circuit computer aided design. This paper describes the computer methods that are common to both areas and highlights the differences in application through brief examples. Recognizing this commonality has stimulated the exchange of useful techniques in both areas and has the potential of fostering new approaches to electric network analysis through the interchange of ideas.

  5. Social network analysis for startups finding connections on the social web

    CERN Document Server

    Tsvetovat, Maksim

    2011-01-01

    Does your startup rely on social network analysis? This concise guide provides a statistical framework to help you identify social processes hidden among the tons of data now available. Social network analysis (SNA) is a discipline that predates Facebook and Twitter by 30 years. Through expert SNA researchers, you''ll learn concepts and techniques for recognizing patterns in social media, political groups, companies, cultural trends, and interpersonal networks. You''ll also learn how to use Python and other open source tools-such as NetworkX, NumPy, and Matplotlib-to gather, analyze, and vis

  6. Time series analysis of temporal networks

    Science.gov (United States)

    Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh

    2016-01-01

    A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue

  7. Navigating freely-available software tools for metabolomics analysis.

    Science.gov (United States)

    Spicer, Rachel; Salek, Reza M; Moreno, Pablo; Cañueto, Daniel; Steinbeck, Christoph

    2017-01-01

    The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools. To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics. The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for. A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary. This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.

  8. Social network analysis to cluster sociobibliometric information

    Directory of Open Access Journals (Sweden)

    Jorge Ricardo Vivas

    Full Text Available This paper examines the benefits of using Social Network Analysis in the field of sociobibliometric exploration. There are considered practical and conceptual limits and reaches. The proposal is illustrated through a study about a journals network of behavior modification by Peiró and Carpintero (1981. In this context it is shown the utility of using reticular properties of Density, Centrality, Betweenness, Power and Clusterig as indicators that allow obtaining novel and complementary information to the one extracted by the classic methods of bibliometric exploration.

  9. Capacity analysis of vehicular communication networks

    CERN Document Server

    Lu, Ning

    2013-01-01

    This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is deriv

  10. Historical Network Analysis of the Web

    DEFF Research Database (Denmark)

    Brügger, Niels

    2013-01-01

    of the online web has for a number of years gained currency within Internet studies. However, the combination of these two phenomena—historical network analysis of material in web archives—can at best be characterized as an emerging new area of study. Most of the methodological challenges within this new area...... at the Danish parliamentary elections in 2011, 2007, and 2001. As the Internet grows older historical studies of networks on the web will probably become more widespread and therefore it may be about time to begin debating the methodological challenges within this emerging field....

  11. Surrogate Analysis and Index Developer (SAID) tool

    Science.gov (United States)

    Domanski, Marian M.; Straub, Timothy D.; Landers, Mark N.

    2015-10-01

    The use of acoustic and other parameters as surrogates for suspended-sediment concentrations (SSC) in rivers has been successful in multiple applications across the Nation. Tools to process and evaluate the data are critical to advancing the operational use of surrogates along with the subsequent development of regression models from which real-time sediment concentrations can be made available to the public. Recent developments in both areas are having an immediate impact on surrogate research and on surrogate monitoring sites currently (2015) in operation.

  12. The use of social networking tools for innovative service delivery at ...

    African Journals Online (AJOL)

    Social networking tools are impacting on the scholarly and research activities of staff and students in the academic environment. The university library has an important part to play in supporting these endeavours and a Web 2.0/Library 2.0 strategy has been in place in the University of Pretoria Library for a number of years.

  13. Social Networking as an Admission Tool: A Case Study in Success

    Science.gov (United States)

    Hayes, Thomas J.; Ruschman, Doug; Walker, Mary M.

    2009-01-01

    The concept of social networking, the focus of this article, targets the development of online communities in higher education, and in particular, as part of the admission process. A successful case study of a university is presented on how one university has used this tool to compete for students. A discussion including suggestions on how to…

  14. Integrating Social Networking Tools into ESL Writing Classroom: Strengths and Weaknesses

    Science.gov (United States)

    Yunus, Melor Md; Salehi, Hadi; Chenzi, Chen

    2012-01-01

    With the rapid development of world and technology, English learning has become more important. Teachers frequently use teacher-centered pedagogy that leads to lack of interaction with students. This paper aims to investigate the advantages and disadvantages of integrating social networking tools into ESL writing classroom and discuss the ways to…

  15. Potential Uses of Bayesian Networks as Tools for Synthesis of Systematic Reviews of Complex Interventions

    Science.gov (United States)

    Stewart, G. B.; Mengersen, K.; Meader, N.

    2014-01-01

    Bayesian networks (BNs) are tools for representing expert knowledge or evidence. They are especially useful for synthesising evidence or belief concerning a complex intervention, assessing the sensitivity of outcomes to different situations or contextual frameworks and framing decision problems that involve alternative types of intervention.…

  16. Social Networking as a Tool for Lifelong Learning with Orthopedically Impaired Learners

    Science.gov (United States)

    Ersoy, Metin; Güneyli, Ahmet

    2016-01-01

    This paper discusses how Turkish Cypriot orthopedically impaired learners who are living in North Cyprus use social networking as a tool for leisure and education, and to what extent they satisfy their personal development needs by means of these digital platforms. The case study described, conducted in North Cyprus in 2015 followed a qualitative…

  17. Homonyms's complex networks to semantic analysis textual

    Directory of Open Access Journals (Sweden)

    Jadson da Silva Santos

    2017-04-01

    Full Text Available Introduction: Study centres in natural language processing already spread and the study have several applications. Relate with this research area, it is common the use technic for manipulation a text. These technic is be able to determine the word morphology and the word syntax. There are tools that do this work, however adding engines for semantic identification of the words is essential for increase the automatic understanding the used language. Objective: On the basis of that, This paper present the process of using complex networks as a comparative database to determine by context the meaning of words that express different positions. Moreover, they are classified as same morphology and syntax , as with some homonyms. Methodology: Through of a experimental methodology, the model proposed it is based in consolidate researches in Natural Language Processing for building a Complex Network that receives as vertices the words of a certain text and establishes its connections from the occurrence of adjacency between these terms. Therefore, observing the variations of network, it is identified how to textual namesakes are related and through an context analyzed how if be there, check whether it is used to express more than one meaning. Results: A generic process with stages of preprocessing, building of a Complex Network used to Natural Language Processing for the building of a network homonyms to extract semantic information textual. Conclusions: The analyze of homonyms selected and labeled is the process not only morphosyntatic, adding semantic in the phrase, paragraph or text where the words are applied. However, with Natural Language Processing an events and philosophical facts can be better analyzed through of a world written textually, for example, the power of argument and the writing of an author profile.

  18. Software Tool for Real-Time Power Quality Analysis

    OpenAIRE

    CZIKER, A. C.; CHINDRIS, M. D.; Miron, A

    2013-01-01

    A software tool dedicated for the analysis of power signals containing harmonic and interharmonic components, unbalance, voltage dips and voltage swells is presented. The software tool is a virtual instrument, which uses innovative algorithms based on time and frequency domains analysis to process power signals. In order to detect the temporary disturbances, edge detection is proposed, whereas for the harmonic analysis Gaussian filter banks are implemented. Considering that a signal recov...

  19. Analysis of neural networks in terms of domain functions

    NARCIS (Netherlands)

    van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, Lambert

    Despite their success-story, artificial neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more as a

  20. Analysis of core–periphery organization in protein contact networks ...

    Indian Academy of Sciences (India)

    The representation of proteins as networks of interacting amino acids, referred to as protein contact networks (PCN), and their subsequent analyses using graph theoretic tools, can provide novel insights into the key functional roles of specific groups of residues. We have characterized the networks corresponding to the ...

  1. GEOMORPHOLOGIC ANALYSIS OF DRAINAGE NETWORKS ON MARS

    Directory of Open Access Journals (Sweden)

    KERESZTURI ÁKOS

    2012-06-01

    Full Text Available Altogether 327 valleys and their 314 cross-sectional profiles were analyzed on Mars, including width, depth, length, eroded volume, drainage and spatial density, as well as the network structure.According to this systematic analysis, five possible drainage network types were identified such as (a small valleys, (b integrated small valleys, (c individual, medium-sized valleys, (d unconfined,anastomosing outflow valleys, and (e confined outflow valleys. Measuring their various morphometric parameters, these five networks differ from each other in terms of parameters of the eroded volume, drainage density and depth values. This classification is more detailed than those described in the literature previously and correlated to several numerical parameters for the first time.These different types were probably formed during different periods of the evolution of Mars, and sprung from differently localized water sources, and they could be correlated to similar fluvialnetwork types from the Earth.

  2. A network analysis of Sibiu County, Romania

    CERN Document Server

    Grama, Cristina-Nicol

    2013-01-01

    Network science methods have proved to be able to provide useful insights from both a theoretical and a practical point of view in that they can better inform governance policies in complex dynamic environments. The tourism research community has provided an increasing number of works that analyse destinations from a network science perspective. However, most of the studies refer to relatively small samples of actors and linkages. With this note we provide a full network study, although at a preliminary stage, that reports a complete analysis of a Romanian destination (Sibiu). Our intention is to increase the set of similar studies with the aim of supporting the investigations in structural and dynamical characteristics of tourism destinations.

  3. Estimation of tool wear during CNC milling using neural network-based sensor fusion

    Science.gov (United States)

    Ghosh, N.; Ravi, Y. B.; Patra, A.; Mukhopadhyay, S.; Paul, S.; Mohanty, A. R.; Chattopadhyay, A. B.

    2007-01-01

    Cutting tool wear degrades the product quality in manufacturing processes. Monitoring tool wear value online is therefore needed to prevent degradation in machining quality. Unfortunately there is no direct way of measuring the tool wear online. Therefore one has to adopt an indirect method wherein the tool wear is estimated from several sensors measuring related process variables. In this work, a neural network-based sensor fusion model has been developed for tool condition monitoring (TCM). Features extracted from a number of machining zone signals, namely cutting forces, spindle vibration, spindle current, and sound pressure level have been fused to estimate the average flank wear of the main cutting edge. Novel strategies such as, signal level segmentation for temporal registration, feature space filtering, outlier removal, and estimation space filtering have been proposed. The proposed approach has been validated by both laboratory and industrial implementations.

  4. Landslide susceptibility analysis using an artificial neural network model

    Science.gov (United States)

    Mansor, Shattri; Pradhan, Biswajeet; Daud, Mohamed; Jamaludin, Normalina; Khuzaimah, Zailani

    2007-10-01

    This paper deals with landslide susceptibility analysis using an artificial neural network model for Cameron Highland, Malaysia. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys. Topographical/geological data and satellite images were collected and processed using GIS and image processing tools. There are ten landslide inducing parameters which are considered for the landslide hazards. These parameters are topographic slope, aspect, curvature and distance from drainage, all derived from the topographic database; geology and distance from lineament, derived from the geologic database; landuse from Landsat satellite images; soil from the soil database; precipitation amount, derived from the rainfall database; and the vegetation index value from SPOT satellite images. Landslide hazard was analyzed using landslide occurrence factors employing the logistic regression model. The results of the analysis were verified using the landslide location data and compared with logistic regression model. The accuracy of hazard map observed was 85.73%. The qualitative landslide susceptibility analysis was carried out using an artificial neural network model by doing map overlay analysis in GIS environment. This information could be used to estimate the risk to population, property and existing infrastructure like transportation network.

  5. 3D Network Analysis for Indoor Space Applications

    Science.gov (United States)

    Tsiliakou, E.; Dimopoulou, E.

    2016-10-01

    Indoor space differs from outdoor environments, since it is characterized by a higher level of structural complexity, geometry, as well as topological relations. Indoor space can be considered as the most important component in a building's conceptual modelling, on which applications such as indoor navigation, routing or analysis are performed. Therefore, the conceptual meaning of sub spaces or the activities taking place in physical building boundaries (e.g. walls), require the comprehension of the building's indoor hierarchical structure. The scope of this paper is to perform 3D network analysis in a building's interior and is structured as follows: In Section 1 the definition of indoor space is provided and indoor navigation requirements are analysed. Section 2 describes the processes of indoor space modeling, as well as routing applications. In Section 3, a case study is examined involving a 3D building model generated in CityEngine (exterior shell) and ArcScene (interior parts), in which the use of commercially available software tools (ArcGIS, ESRI), in terms of indoor routing and 3D network analysis, are explored. The fundamentals of performing 3D analysis with the ArcGIS Network Analyst extension were tested. Finally a geoprocessing model was presented, which was specifically designed to be used to interactively find the best route in ArcScene. The paper ends with discussion and concluding remarks on Section 4.

  6. 3D NETWORK ANALYSIS FOR INDOOR SPACE APPLICATIONS

    Directory of Open Access Journals (Sweden)

    E. Tsiliakou

    2016-10-01

    Full Text Available Indoor space differs from outdoor environments, since it is characterized by a higher level of structural complexity, geometry, as well as topological relations. Indoor space can be considered as the most important component in a building’s conceptual modelling, on which applications such as indoor navigation, routing or analysis are performed. Therefore, the conceptual meaning of sub spaces or the activities taking place in physical building boundaries (e.g. walls, require the comprehension of the building’s indoor hierarchical structure. The scope of this paper is to perform 3D network analysis in a building’s interior and is structured as follows: In Section 1 the definition of indoor space is provided and indoor navigation requirements are analysed. Section 2 describes the processes of indoor space modeling, as well as routing applications. In Section 3, a case study is examined involving a 3D building model generated in CityEngine (exterior shell and ArcScene (interior parts, in which the use of commercially available software tools (ArcGIS, ESRI, in terms of indoor routing and 3D network analysis, are explored. The fundamentals of performing 3D analysis with the ArcGIS Network Analyst extension were tested. Finally a geoprocessing model was presented, which was specifically designed to be used to interactively find the best route in ArcScene. The paper ends with discussion and concluding remarks on Section 4.

  7. Network Computing Infrastructure to Share Tools and Data in Global Nuclear Energy Partnership

    Science.gov (United States)

    Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

    CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer-Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP.

  8. Micro-macro analysis of complex networks.

    Science.gov (United States)

    Marchiori, Massimo; Possamai, Lino

    2015-01-01

    Complex systems have attracted considerable interest because of their wide range of applications, and are often studied via a "classic" approach: study a specific system, find a complex network behind it, and analyze the corresponding properties. This simple methodology has produced a great deal of interesting results, but relies on an often implicit underlying assumption: the level of detail on which the system is observed. However, in many situations, physical or abstract, the level of detail can be one out of many, and might also depend on intrinsic limitations in viewing the data with a different level of abstraction or precision. So, a fundamental question arises: do properties of a network depend on its level of observability, or are they invariant? If there is a dependence, then an apparently correct network modeling could in fact just be a bad approximation of the true behavior of a complex system. In order to answer this question, we propose a novel micro-macro analysis of complex systems that quantitatively describes how the structure of complex networks varies as a function of the detail level. To this extent, we have developed a new telescopic algorithm that abstracts from the local properties of a system and reconstructs the original structure according to a fuzziness level. This way we can study what happens when passing from a fine level of detail ("micro") to a different scale level ("macro"), and analyze the corresponding behavior in this transition, obtaining a deeper spectrum analysis. The obtained results show that many important properties are not universally invariant with respect to the level of detail, but instead strongly depend on the specific level on which a network is observed. Therefore, caution should be taken in every situation where a complex network is considered, if its context allows for different levels of observability.

  9. A new tool for quality of multimedia estimation based on network behaviour

    Directory of Open Access Journals (Sweden)

    Jaroslav Frnda

    2016-03-01

    Full Text Available In this paper, we present a software tool capable of predicting the final quality of triple play services by using the most common assessment metrics. The quality of speech and video in network environment is a growing concern of all the internet service providers to carry the multimedia traffic without the excessive delays and losses, which degrade the quality of multimedia as it is perceived by the end users. Prediction mathematical model is based on results obtained from many performed testing scenarios simulating real behavior in the network. Based on the proposed model, speech or video quality is calculated with regard to policies applied for packet processing by routers and to the level of total network utilization. The application cannot only predict QoS parameters but also generate the source code of particular QoS policy setting according to the user interaction and apply the policy to the routers in the network. Contribution of the work consists of a new software tool enables network administrators and designers to improve and optimize network traffic efficiently.

  10. Dynamic Characteristics Analysis of a Micro Grinding Machine Tool

    OpenAIRE

    Li Wei; Li Beizhi; Yang Jianguo

    2017-01-01

    Developing miniaturizedultraprecision machine tools (MUMTs) is a rational approach to manufacture micro/mesoscale mechanical components. The dynamic characteristics of MUMTs can be different from that of conventional machine tools, because of its miniaturized structure, downsized components and more flexible assembly. Their dynamics behaviorneeds to be studied. In this paper, the dynamic characteristics of a verticalultraprecisionmicro grinding machine tool were analyzed. An analysis model wa...

  11. Analysis of cascading failure in gene networks

    Directory of Open Access Journals (Sweden)

    Shudong eWang

    2012-12-01

    Full Text Available It is an important subject to research the functional mechanism of cancer-related genes make in formation and development of cancers. The modern methodology of data analysis plays a very important role for deducing the relationship between cancers and cancer-related genes and analyzing functional mechanism of genome. In this research, we construct mutual information networks using gene expression profiles of glioblast and renal in normal condition and cancer conditions. We investigate the relationship between structure and robustness in gene networks of the two tissues using a cascading failure model based on betweenness centrality. Define some important parameters such as the percentage of failure nodes of the network, the average size-ratio of cascading failure and the cumulative probability of size-ratio of cascading failure to measure the robustness of the networks. By comparing control group and experiment groups, we find that the networks of experiment groups are more robust than that of control group. The gene that can cause large scale failure is called structural key gene (SKG. Some of them have been confirmed to be closely related to the formation and development of glioma and renal cancer respectively. Most of them are predicted to play important roles during the formation of glioma and renal cancer, maybe the oncogenes, suppressor genes, and other cancer candidate genes in the glioma and renal cancer cells. However, these studies provide little information about the detailed roles of identified cancer genes.

  12. Positive and negative forms of replicability in gene network analysis.

    Science.gov (United States)

    Verleyen, W; Ballouz, S; Gillis, J

    2016-04-01

    Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility that this may lead to overfitting in the field as a whole. We construct a model of 'research communities' sampling from real gene network data and machine learning methods to characterize performance trends. Our analysis reveals an important principle limiting the value of replication, namely that targeting it directly causes 'easy' or uninformative replication to dominate analyses. We find that when sampling across network data and algorithms with similar variability, the relationship between replicability and accuracy is positive (Spearman's correlation, rs ∼0.33) but where no such constraint is imposed, the relationship becomes negative for a given gene function (rs ∼ -0.13). We predict factors driving replicability in some prior analyses of gene networks and show that they are unconnected with the correctness of the original result, instead reflecting replicable biases. Without these biases, the original results also vanish replicably. We show these effects can occur quite far upstream in network data and that there is a strong tendency within protein-protein interaction data for highly replicable interactions to be associated with poor quality control. Algorithms, network data and a guide to the code available at: https://github.com/wimverleyen/AggregateGeneFunctionPrediction jgillis@cshl.edu Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  13. The brain as a complex system: using network science as a tool for understanding the brain.

    Science.gov (United States)

    Telesford, Qawi K; Simpson, Sean L; Burdette, Jonathan H; Hayasaka, Satoru; Laurienti, Paul J

    2011-01-01

    Although graph theory has been around since the 18th century, the field of network science is more recent and continues to gain popularity, particularly in the field of neuroimaging. The field was propelled forward when Watts and Strogatz introduced their small-world network model, which described a network that provided regional specialization with efficient global information transfer. This model is appealing to the study of brain connectivity, as the brain can be viewed as a system with various interacting regions that produce complex behaviors. In practice, graph metrics such as clustering coefficient, path length, and efficiency measures are often used to characterize system properties. Centrality metrics such as degree, betweenness, closeness, and eigenvector centrality determine critical areas within the network. Community structure is also essential for understanding network organization and topology. Network science has led to a paradigm shift in the neuroscientific community, but it should be viewed as more than a simple "tool du jour." To fully appreciate the utility of network science, a greater understanding of how network models apply to the brain is needed. An integrated appraisal of multiple network analyses should be performed to better understand network structure rather than focusing on univariate comparisons to find significant group differences; indeed, such comparisons, popular with traditional functional magnetic resonance imaging analyses, are arguably no longer relevant with graph-theory based approaches. These methods necessitate a philosophical shift toward complexity science. In this context, when correctly applied and interpreted, network scientific methods have a chance to revolutionize the understanding of brain function.

  14. Dynamic Characteristics Analysis of a Micro Grinding Machine Tool

    Directory of Open Access Journals (Sweden)

    Li Wei

    2017-01-01

    Full Text Available Developing miniaturizedultraprecision machine tools (MUMTs is a rational approach to manufacture micro/mesoscale mechanical components. The dynamic characteristics of MUMTs can be different from that of conventional machine tools, because of its miniaturized structure, downsized components and more flexible assembly. Their dynamics behaviorneeds to be studied. In this paper, the dynamic characteristics of a verticalultraprecisionmicro grinding machine tool were analyzed. An analysis model was established based on finite element method(FEM. Modal analysis was then conducted to obtain vibration mode characteristics of the machine tool, and then the harmonic response analysis was applied to machine tool for verifying its mechanical behaviour. This work helps MUMT developers make a better product at the early design stage with lower cost and development time

  15. Using Epistemic Network Analysis to understand core topics as planned learning objectives

    DEFF Research Database (Denmark)

    Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

    Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

  16. New Tools in Nonlinear System Analysis

    National Research Council Canada - National Science Library

    Megretski, Alexandre

    2003-01-01

    This project was aimed at developing novel theories for the analysis and design of systems exhibiting essentially nonlinear behavior, such as systems utilizing quantized decision making, periodic orbits, switching, etc...

  17. Communities detection as a tool to assess a reform of the Italian interlocking directorship network

    Science.gov (United States)

    Drago, Carlo; Ricciuti, Roberto

    2017-01-01

    Interlocking directorships are important communication channels among companies and may have anticompetitive effect. A corporate governance reform was introduced in 2011 to prevent interlocking directorships in the financial sector. We apply community detection techniques to the analysis of the networks in 2009 and 2012 to ascertain the effect of such reform on the Italian directorship network. We find that, although the number of interlocking directorships decreases in 2012, the reduction takes place mainly at the periphery of the network. The network core is stable, allowing the most connected companies to keep their strategic position.

  18. Using structural equation modeling for network meta-analysis.

    Science.gov (United States)

    Tu, Yu-Kang; Wu, Yun-Chun

    2017-07-14

    Network meta-analysis overcomes the limitations of traditional pair-wise meta-analysis by incorporating all available evidence into a general statistical framework for simultaneous comparisons of several treatments. Currently, network meta-analyses are undertaken either within the Bayesian hierarchical linear models or frequentist generalized linear mixed models. Structural equation modeling (SEM) is a statistical method originally developed for modeling causal relations among observed and latent variables. As random effect is explicitly modeled as a latent variable in SEM, it is very flexible for analysts to specify complex random effect structure and to make linear and nonlinear constraints on parameters. The aim of this article is to show how to undertake a network meta-analysis within the statistical framework of SEM. We used an example dataset to demonstrate the standard fixed and random effect network meta-analysis models can be easily implemented in SEM. It contains results of 26 studies that directly compared three treatment groups A, B and C for prevention of first bleeding in patients with liver cirrhosis. We also showed that a new approach to network meta-analysis based on the technique of unrestricted weighted least squares (UWLS) method can also be undertaken using SEM. For both the fixed and random effect network meta-analysis, SEM yielded similar coefficients and confidence intervals to those reported in the previous literature. The point estimates of two UWLS models were identical to those in the fixed effect model but the confidence intervals were greater. This is consistent with results from the traditional pairwise meta-analyses. Comparing to UWLS model with common variance adjusted factor, UWLS model with unique variance adjusted factor has greater confidence intervals when the heterogeneity was larger in the pairwise comparison. The UWLS model with unique variance adjusted factor reflects the difference in heterogeneity within each comparison

  19. Wireless sensor networks concepts, applications, experimentation and analysis

    CERN Document Server

    Fahmy, Hossam Mahmoud Ahmad

    2016-01-01

    This book focuses on the principles of wireless sensor networks (WSNs), their applications, and their analysis tools, with meticulous attention paid to definitions and terminology. This book presents the adopted technologies and their manufacturers in detail, making WSNs tangible for the reader. In introductory computer networking books, chapter sequencing follows the bottom-up or top-down architecture of the 7-layer protocol. This book addresses subsequent steps in this process, both horizontally and vertically, thus fostering a clearer and deeper understanding through chapters that elaborate on WSN concepts and issues. With such depth, this book is intended for a wide audience; it is meant to be a helper and motivator for senior undergraduates, postgraduates, researchers, and practitioners. It lays out important concepts and WSN-relate applications; uses appropriate literature to back research and practical issues; and focuses on new trends. Senior undergraduate students can use it to familiarize themselves...

  20. Tools and Algorithms for the Construction and Analysis of Systems

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 10th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2004, held in Barcelona, Spain in March/April 2004. The 37 revised full papers and 6 revised tool demonstration papers presented were car......, and automata techniques....

  1. NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

    Science.gov (United States)

    Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Sand, Olivier; Janky, Rekin's; Vanderstocken, Gilles; Deville, Yves; van Helden, Jacques

    2008-01-01

    The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources. PMID:18524799

  2. Bayesian network as a modelling tool for risk management in agriculture

    DEFF Research Database (Denmark)

    Rasmussen, Svend; Madsen, Anders Læsø; Lund, Mogens

    The importance of risk management increases as farmers become more exposed to risk. But risk management is a difficult topic because income risk is the result of the complex interaction of multiple risk factors combined with the effect of an increasing array of possible risk management tools....... In this paper we use Bayesian networks as an integrated modelling approach for representing uncertainty and analysing risk management in agriculture. It is shown how historical farm account data may be efficiently used to estimate conditional probabilities, which are the core elements in Bayesian network models....... We further show how the Bayesian network model RiBay is used for stochastic simulation of farm income, and we demonstrate how RiBay can be used to simulate risk management at the farm level. It is concluded that the key strength of a Bayesian network is the transparency of assumptions...

  3. Social network analysis and network connectedness analysis for industrial symbiotic systems: model development and case study

    Science.gov (United States)

    Zhang, Yan; Zheng, Hongmei; Chen, Bin; Yang, Naijin

    2013-06-01

    An important and practical pattern of industrial symbiosis is rapidly developing: eco-industrial parks. In this study, we used social network analysis to study the network connectedness (i.e., the proportion of the theoretical number of connections that had been achieved) and related attributes of these hybrid ecological and industrial symbiotic systems. This approach provided insights into details of the network's interior and analyzed the overall degree of connectedness and the relationships among the nodes within the network. We then characterized the structural attributes of the network and subnetwork nodes at two levels (core and periphery), thereby providing insights into the operational problems within each eco-industrial park. We chose ten typical ecoindustrial parks in China and around the world and compared the degree of network connectedness of these systems that resulted from exchanges of products, byproducts, and wastes. By analyzing the density and nodal degree, we determined the relative power and status of the nodes in these networks, as well as other structural attributes such as the core-periphery structure and the degree of sub-network connectedness. The results reveal the operational problems created by the structure of the industrial networks and provide a basis for improving the degree of completeness, thereby increasing their potential for sustainable development and enriching the methods available for the study of industrial symbiosis.

  4. Stochastic analysis of complex reaction networks using binomial moment equations

    Science.gov (United States)

    Barzel, Baruch; Biham, Ofer

    2012-09-01

    The stochastic analysis of complex reaction networks is a difficult problem because the number of microscopic states in such systems increases exponentially with the number of reactive species. Direct integration of the master equation is thus infeasible and is most often replaced by Monte Carlo simulations. While Monte Carlo simulations are a highly effective tool, equation-based formulations are more amenable to analytical treatment and may provide deeper insight into the dynamics of the network. Here, we present a highly efficient equation-based method for the analysis of stochastic reaction networks. The method is based on the recently introduced binomial moment equations [Barzel and Biham, Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.106.150602 106, 150602 (2011)]. The binomial moments are linear combinations of the ordinary moments of the probability distribution function of the population sizes of the interacting species. They capture the essential combinatorics of the reaction processes reflecting their stoichiometric structure. This leads to a simple and transparent form of the equations, and allows a highly efficient and surprisingly simple truncation scheme. Unlike ordinary moment equations, in which the inclusion of high order moments is prohibitively complicated, the binomial moment equations can be easily constructed up to any desired order. The result is a set of equations that enables the stochastic analysis of complex reaction networks under a broad range of conditions. The number of equations is dramatically reduced from the exponential proliferation of the master equation to a polynomial (and often quadratic) dependence on the number of reactive species in the binomial moment equations. The aim of this paper is twofold: to present a complete derivation of the binomial moment equations; to demonstrate the applicability of the moment equations for a representative set of example networks, in which stochastic effects play an important role.

  5. Stochastic analysis of complex reaction networks using binomial moment equations.

    Science.gov (United States)

    Barzel, Baruch; Biham, Ofer

    2012-09-01

    The stochastic analysis of complex reaction networks is a difficult problem because the number of microscopic states in such systems increases exponentially with the number of reactive species. Direct integration of the master equation is thus infeasible and is most often replaced by Monte Carlo simulations. While Monte Carlo simulations are a highly effective tool, equation-based formulations are more amenable to analytical treatment and may provide deeper insight into the dynamics of the network. Here, we present a highly efficient equation-based method for the analysis of stochastic reaction networks. The method is based on the recently introduced binomial moment equations [Barzel and Biham, Phys. Rev. Lett. 106, 150602 (2011)]. The binomial moments are linear combinations of the ordinary moments of the probability distribution function of the population sizes of the interacting species. They capture the essential combinatorics of the reaction processes reflecting their stoichiometric structure. This leads to a simple and transparent form of the equations, and allows a highly efficient and surprisingly simple truncation scheme. Unlike ordinary moment equations, in which the inclusion of high order moments is prohibitively complicated, the binomial moment equations can be easily constructed up to any desired order. The result is a set of equations that enables the stochastic analysis of complex reaction networks under a broad range of conditions. The number of equations is dramatically reduced from the exponential proliferation of the master equation to a polynomial (and often quadratic) dependence on the number of reactive species in the binomial moment equations. The aim of this paper is twofold: to present a complete derivation of the binomial moment equations; to demonstrate the applicability of the moment equations for a representative set of example networks, in which stochastic effects play an important role.

  6. Game data analysis tools and methods

    CERN Document Server

    Coupart, Thibault

    2013-01-01

    This book features an introduction to the basic theoretical tenets of data analysis from a game developer's point of view, as well as a practical guide to performing gameplay analysis on a real-world game.This book is ideal for video game developers who want to try and experiment with the game analytics approach for their own productions. It will provide a good overview of the themes you need to pay attention to, and will pave the way for success. Furthermore, the book also provides a wide range of concrete examples that will be useful for any game data analysts or scientists who want to impro

  7. RNAmute: RNA secondary structure mutation analysis tool

    Directory of Open Access Journals (Sweden)

    Barash Danny

    2006-04-01

    Full Text Available Abstract Background RNAMute is an interactive Java application that calculates the secondary structure of all single point mutations, given an RNA sequence, and organizes them into categories according to their similarity with respect to the wild type predicted structure. The secondary structure predictions are performed using the Vienna RNA package. Several alternatives are used for the categorization of single point mutations: Vienna's RNAdistance based on dot-bracket representation, as well as tree edit distance and second eigenvalue of the Laplacian matrix based on Shapiro's coarse grain tree graph representation. Results Selecting a category in each one of the processed tables lists all single point mutations belonging to that category. Selecting a mutation displays a graphical drawing of the single point mutation and the wild type, and includes basic information such as associated energies, representations and distances. RNAMute can be used successfully with very little previous experience and without choosing any parameter value alongside the initial RNA sequence. The package runs under LINUX operating system. Conclusion RNAMute is a user friendly tool that can be used to predict single point mutations leading to conformational rearrangements in the secondary structure of RNAs. In several cases of substantial interest, notably in virology, a point mutation may lead to a loss of important functionality such as the RNA virus replication and translation initiation because of a conformational rearrangement in the secondary structure.

  8. Tools and Algorithms for Construction and Analysis of Systems

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 6th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2000, held as part of ETAPS 2000 in Berlin, Germany, in March/April 2000. The 33 revised full papers presented together with one invited...... paper and two short tool descriptions were carefully reviewed and selected from a total of 107 submissions. The papers are organized in topical sections on software and formal methods, formal methods, timed and hybrid systems, infinite and parameterized systems, diagnostic and test generation, efficient...... model checking, model-checking tools, symbolic model checking, visual tools, and verification of critical systems....

  9. Principal component analysis networks and algorithms

    CERN Document Server

    Kong, Xiangyu; Duan, Zhansheng

    2017-01-01

    This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.

  10. Spreadsheet as a tool of engineering analysis

    Energy Technology Data Exchange (ETDEWEB)

    Becker, M.

    1985-11-01

    In engineering analysis, problems tend to be categorized into those that can be done by hand and those that require the computer for solution. The advent of personal computers, and in particular, the advent of spreadsheet software, blurs this distinction, creating an intermediate category of problems appropriate for use with interactive personal computing.

  11. Automatic analysis of attack data from distributed honeypot network

    Science.gov (United States)

    Safarik, Jakub; Voznak, MIroslav; Rezac, Filip; Partila, Pavol; Tomala, Karel

    2013-05-01

    There are many ways of getting real data about malicious activity in a network. One of them relies on masquerading monitoring servers as a production one. These servers are called honeypots and data about attacks on them brings us valuable information about actual attacks and techniques used by hackers. The article describes distributed topology of honeypots, which was developed with a strong orientation on monitoring of IP telephony traffic. IP telephony servers can be easily exposed to various types of attacks, and without protection, this situation can lead to loss of money and other unpleasant consequences. Using a distributed topology with honeypots placed in different geological locations and networks provides more valuable and independent results. With automatic system of gathering information from all honeypots, it is possible to work with all information on one centralized point. Communication between honeypots and centralized data store use secure SSH tunnels and server communicates only with authorized honeypots. The centralized server also automatically analyses data from each honeypot. Results of this analysis and also other statistical data about malicious activity are simply accessible through a built-in web server. All statistical and analysis reports serve as information basis for an algorithm which classifies different types of used VoIP attacks. The web interface then brings a tool for quick comparison and evaluation of actual attacks in all monitored networks. The article describes both, the honeypots nodes in distributed architecture, which monitor suspicious activity, and also methods and algorithms used on the server side for analysis of gathered data.

  12. The environment power system analysis tool development program

    Science.gov (United States)

    Jongeward, Gary A.; Kuharski, Robert A.; Kennedy, Eric M.; Stevens, N. John; Putnam, Rand M.; Roche, James C.; Wilcox, Katherine G.

    1990-01-01

    The Environment Power System Analysis Tool (EPSAT) is being developed to provide space power system design engineers with an analysis tool for determining system performance of power systems in both naturally occurring and self-induced environments. The program is producing an easy to use computer aided engineering (CAE) tool general enough to provide a vehicle for technology transfer from space scientists and engineers to power system design engineers. The results of the project after two years of a three year development program are given. The EPSAT approach separates the CAE tool into three distinct functional units: a modern user interface to present information, a data dictionary interpreter to coordinate analysis; and a data base for storing system designs and results of analysis.

  13. Surface Operations Data Analysis and Adaptation Tool Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This effort undertook the creation of a Surface Operations Data Analysis and Adaptation (SODAA) tool to store data relevant to airport surface research and...

  14. Biofuel transportation analysis tool : description, methodology, and demonstration scenarios

    Science.gov (United States)

    2014-01-01

    This report describes a Biofuel Transportation Analysis Tool (BTAT), developed by the U.S. Department of Transportation (DOT) Volpe National Transportation Systems Center (Volpe) in support of the Department of Defense (DOD) Office of Naval Research ...

  15. Generalized Aliasing as a Basis for Program Analysis Tools

    National Research Council Canada - National Science Library

    O'Callahan, Robert

    2000-01-01

    .... This dissertation describes the design of a system, Ajax, that addresses this problem by using semantics-based program analysis as the basis for a number of different tools to aid Java programmers...

  16. Service network analysis for agricultural mental health

    Directory of Open Access Journals (Sweden)

    Fuller Jeffrey D

    2009-05-01

    Full Text Available Abstract Background Farmers represent a subgroup of rural and remote communities at higher risk of suicide attributed to insecure economic futures, self-reliant cultures and poor access to health services. Early intervention models are required that tap into existing farming networks. This study describes service networks in rural shires that relate to the mental health needs of farming families. This serves as a baseline to inform service network improvements. Methods A network survey of mental health related links between agricultural support, health and other human services in four drought declared shires in comparable districts in rural New South Wales, Australia. Mental health links covered information exchange, referral recommendations and program development. Results 87 agencies from 111 (78% completed a survey. 79% indicated that two thirds of their clients needed assistance for mental health related problems. The highest mean number of interagency links concerned information exchange and the frequency of these links between sectors was monthly to three monthly. The effectiveness of agricultural support and health sector links were rated as less effective by the agricultural support sector than by the health sector (p Conclusion Aligning with agricultural agencies is important to build effective mental health service pathways to address the needs of farming populations. Work is required to ensure that these agricultural support agencies have operational and effective links to primary mental health care services. Network analysis provides a baseline to inform this work. With interventions such as local mental health training and joint service planning to promote network development we would expect to see over time an increase in the mean number of links, the frequency in which these links are used and the rated effectiveness of these links.

  17. Network Analysis and Modeling in Systems Biology

    OpenAIRE

    Bosque Chacón, Gabriel

    2017-01-01

    This thesis is dedicated to the study and comprehension of biological networks at the molecular level. The objectives were to analyse their topology, integrate it in a genotype-phenotype analysis, develop richer mathematical descriptions for them, study their community structure and compare different methodologies for estimating their internal fluxes. The work presented in this document moves around three main axes. The first one is the biological. Which organisms were studied in this ...

  18. MEL-IRIS: An Online Tool for Audio Analysis and Music Indexing

    Directory of Open Access Journals (Sweden)

    Dimitrios Margounakis

    2009-01-01

    Full Text Available Chroma is an important attribute of music and sound, although it has not yet been adequately defined in literature. As such, it can be used for further analysis of sound, resulting in interesting colorful representations that can be used in many tasks: indexing, classification, and retrieval. Especially in Music Information Retrieval (MIR, the visualization of the chromatic analysis can be used for comparison, pattern recognition, melodic sequence prediction, and color-based searching. MEL-IRIS is the tool which has been developed in order to analyze audio files and characterize music based on chroma. The tool implements specially designed algorithms and a unique way of visualization of the results. The tool is network-oriented and can be installed in audio servers, in order to manipulate large music collections. Several samples from world music have been tested and processed, in order to demonstrate the possible uses of such an analysis.

  19. A user’s guide to network analysis in R

    CERN Document Server

    Luke, Douglas

    2015-01-01

    Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

  20. The Tracking Meteogram, an AWIPS II Tool for Time-Series Analysis

    Science.gov (United States)

    Burks, Jason Eric; Sperow, Ken

    2015-01-01

    A new tool has been developed for the National Weather Service (NWS) Advanced Weather Interactive Processing System (AWIPS) II through collaboration between NASA's Short-term Prediction Research and Transition (SPoRT) and the NWS Meteorological Development Laboratory (MDL). Referred to as the "Tracking Meteogram", the tool aids NWS forecasters in assessing meteorological parameters associated with moving phenomena. The tool aids forecasters in severe weather situations by providing valuable satellite and radar derived trends such as cloud top cooling rates, radial velocity couplets, reflectivity, and information from ground-based lightning networks. The Tracking Meteogram tool also aids in synoptic and mesoscale analysis by tracking parameters such as the deepening of surface low pressure systems, changes in surface or upper air temperature, and other properties. The tool provides a valuable new functionality and demonstrates the flexibility and extensibility of the NWS AWIPS II architecture. In 2014, the operational impact of the tool was formally evaluated through participation in the NOAA/NWS Operations Proving Ground (OPG), a risk reduction activity to assess performance and operational impact of new forecasting concepts, tools, and applications. Performance of the Tracking Meteogram Tool during the OPG assessment confirmed that it will be a valuable asset to the operational forecasters. This presentation reviews development of the Tracking Meteogram tool, performance and feedback acquired during the OPG activity, and future goals for continued support and extension to other application areas.

  1. Tools for Texts Monitoring and Analysis Aimed at the Field of Social Disasters, Catastrophes, and Terrorism

    Directory of Open Access Journals (Sweden)

    Svetlana Cojocaru

    2016-08-01

    Full Text Available Throughout its life mankind faces various disasters and catastrophes: natural, technogenic, social. One of the important sources of information for these situations is the huge volume of unstructured data available in the global information networks. In this study, we describe a tool set that includes methods for extracting relevant texts from the networks, their classification and analysis. Two stages are described: preparatory and processing. The first one deals with patterns (texts and keywords creation, during the second phase news texts are processed using database and controlled vocabulary.

  2. The new alchemy: Online networking, data sharing and research activity distribution tools for scientists.

    Science.gov (United States)

    Williams, Antony J; Peck, Lou; Ekins, Sean

    2017-01-01

    There is an abundance of free online tools accessible to scientists and others that can be used for online networking, data sharing and measuring research impact. Despite this, few scientists know how these tools can be used or fail to take advantage of using them as an integrated pipeline to raise awareness of their research outputs. In this article, the authors describe their experiences with these tools and how they can make best use of them to make their scientific research generally more accessible, extending its reach beyond their own direct networks, and communicating their ideas to new audiences. These efforts have the potential to drive science by sparking new collaborations and interdisciplinary research projects that may lead to future publications, funding and commercial opportunities. The intent of this article is to: describe some of these freely accessible networking tools and affiliated products; demonstrate from our own experiences how they can be utilized effectively; and, inspire their adoption by new users for the benefit of science.

  3. New analysis tools for observational studies.

    Science.gov (United States)

    Landewé, R B M

    2015-03-01

    Observational studies, which are very common in rheumatology, usually follow a selected group of patients for a predetermined period of time, or infinitely, with regard to a certain outcome. Such an outcome could be a "score" reflecting an important aspect of the disease (e.g., a disease activity score), or an "event" (e.g., myocardial infarction). Rather than investigating the efficacy of a particular treatment, observational studies serve to investigate clinical associations between different (outcome) variables. Confounding, which may spuriously inflate or reduce the magnitude of a particular association, is an inherent risk in observational studies. The modern analytical approach of an observational study depends on the study question, the study design, and on how the outcome of interest has been assessed. The current article discusses several aspects of the analytical approach and requirements of the database. The focus is on longitudinal analysis, subgroup analysis, and adjustment for confounding. It is concluded that the appropriate analysis of an observational study should be a close collaboration between the clinical researcher with sufficient epidemiological knowledge and the expert statistician with sufficient interest in clinical questions.

  4. Network value and optimum analysis on the mode of networked marketing in TV media

    Directory of Open Access Journals (Sweden)

    Xiao Dongpo

    2012-12-01

    Full Text Available Purpose: With the development of the networked marketing in TV media, it is important to do the research on network value and optimum analysis in this field.Design/methodology/approach: According to the research on the mode of networked marketing in TV media and Correlation theory, the essence of media marketing is creating, spreading and transferring values. The Participants of marketing value activities are in network, and value activities proceed in networked form. Network capability is important to TV media marketing activities.Findings: This article raises the direction of research of analysis and optimization about network based on the mode of networked marketing in TV media by studying TV media marketing Development Mechanism , network analysis and network value structure.

  5. Syphilis Networks in Louisiana: An Analysis of Network Configuration and Disease Transmission

    Science.gov (United States)

    Desmarais, Catherine Theresa

    Background: In 2009, Louisiana had the highest rate of primary and secondary syphilis in the country. Recent partner notification approaches have been insufficient in addressing Louisiana's deeply entrenched areas of syphilis infection. Prior researchers have suggested that surveillance systems may benefit from utilizing social and spatial network analysis in syphilis control efforts. Objective: To expand the understanding of the spread of syphilis in Louisiana, and to add new tools to the state's case finding resources through the description of the characteristics of cases of early syphilis and their partners in Louisiana, the socio-sexual networks of these cases, and the geospatial clustering of cases and partners. Methods: Utilizing state surveillance data, all cases of primary, secondary, and early latent syphilis that were diagnosed in 2009 and data on their sexual or needle sharing partners were analyzed using a combination of descriptive, network, and geospatial measures. Results: In 2009, Louisiana experienced a high rate of heterosexual syphilis transmission. Within syphilis transmission networks, 50.8% of all cases were female and 84.2% of all cases were black. The average and median ages of males with reactive syphilis tests were higher than that of females in Louisiana, and in 88.9% of regions, older individuals were more likely to have a syphilis test than no test. A greater proportion of males (11.4%) refused to discuss partners than females (7.4%) and a greater proportion of males (5.5%) refused testing and prophylactic treatment than females (2.8%). No distinct patterns were seen in disease prevalence between regions based upon demographic data. Classic summary network measures such as density, degree, centrality, and betweenness provided little information on similarities and differences between the different regions in Louisiana. All measures indicated low density and extreme fragmentation of networks in Louisiana. The majority of network

  6. The Application of Social Network Analysis to Team Sports

    Science.gov (United States)

    Lusher, Dean; Robins, Garry; Kremer, Peter

    2010-01-01

    This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…

  7. Determination of oil well production performance using artificial neural network (ANN linked to the particle swarm optimization (PSO tool

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Ahmadi

    2015-06-01

    In this work, novel and rigorous methods based on two different types of intelligent approaches including the artificial neural network (ANN linked to the particle swarm optimization (PSO tool are developed to precisely forecast the productivity of horizontal wells under pseudo-steady-state conditions. It was found that there is very good match between the modeling output and the real data taken from the literature, so that a very low average absolute error percentage is attained (e.g., <0.82%. The developed techniques can be also incorporated in the numerical reservoir simulation packages for the purpose of accuracy improvement as well as better parametric sensitivity analysis.

  8. Analysis of deterministic cyclic gene regulatory network models with delays

    CERN Document Server

    Ahsen, Mehmet Eren; Niculescu, Silviu-Iulian

    2015-01-01

    This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. An introductory chapter provides some insights into molecular biology and GRNs. The mathematical tools necessary for studying the GRN model are then reviewed, in particular Hill functions and Schwarzian derivatives. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered. Asymptotic stability analysis of GRNs under positive feedback is then considered in a separate chapter, in which conditions leading to bi-stability are derived. Graduate and advanced undergraduate students and researchers in control engineering, applied mathematics, systems biology and synthetic biology will find this brief to be a clear and concise introduction to the modeling and analysis of GRNs.

  9. The Algerian Seismic Network: Performance from data quality analysis

    Science.gov (United States)

    Yelles, Abdelkarim; Allili, Toufik; Alili, Azouaou

    2013-04-01

    Seismic monitoring in Algeria has seen a great change after the Boumerdes earthquake of May 21st, 2003. Indeed the installation of a New Digital seismic network (ADSN) upgrade drastically the previous analog telemetry network. During the last four years, the number of stations in operation has greatly increased to 66 stations with 15 Broad Band, 02 Very Broad band, 47 Short period and 21 accelerometers connected in real time using various mode of transmission ( VSAT, ADSL, GSM, ...) and managed by Antelope software. The spatial distribution of these stations covers most of northern Algeria from east to west. Since the operation of the network, significant number of local, regional and tele-seismic events was located by the automatic processing, revised and archived in databases. This new set of data is characterized by the accuracy of the automatic location of local seismicity and the ability to determine its focal mechanisms. Periodically, data recorded including earthquakes, calibration pulse and cultural noise are checked using PSD (Power Spectral Density) analysis to determine the noise level. ADSN Broadband stations data quality is controlled in quasi real time using the "PQLX" software by computing PDFs and PSDs of the recordings. Some other tools and programs allow the monitoring and the maintenance of the entire electronic system for example to check the power state of the system, the mass position of the sensors and the environment conditions (Temperature, Humidity, Air Pressure) inside the vaults. The new design of the network allows management of many aspects of real time seismology: seismic monitoring, rapid determination of earthquake, message alert, moment tensor estimation, seismic source determination, shakemaps calculation, etc. The international standards permit to contribute in regional seismic monitoring and the Mediterranean warning system. The next two years with the acquisition of new seismic equipment to reach 50 new BB stations led to

  10. Data Analysis with Open Source Tools

    CERN Document Server

    Janert, Philipp

    2010-01-01

    Collecting data is relatively easy, but turning raw information into something useful requires that you know how to extract precisely what you need. With this insightful book, intermediate to experienced programmers interested in data analysis will learn techniques for working with data in a business environment. You'll learn how to look at data to discover what it contains, how to capture those ideas in conceptual models, and then feed your understanding back into the organization through business plans, metrics dashboards, and other applications. Along the way, you'll experiment with conce

  11. Analysis and visualization of citation networks

    CERN Document Server

    Zhao, Dangzhi

    2015-01-01

    Citation analysis-the exploration of reference patterns in the scholarly and scientific literature-has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval.Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest

  12. Match Analysis an undervalued coaching tool

    CERN Document Server

    Sacripanti, Attilio

    2010-01-01

    From a Biomechanical point of view, Judo competition is an intriguing complex nonlinear system, with many chaotic and fractals aspects, It is also the test bed in which all coaching capabilities and athlete's performances are evaluated and put to the test. Competition is the moment of truth of all conditioning time, preparation and technical work, before developed, and it is also the climax of the teaching point of view. Furthermore, it is the most important source of technical assessment. Studying it is essential to the coaches because they can obtain useful information for their coaching. Match Analysis could be seen as the master key in all situation sports (dual or team) like Judo, to help in useful way the difficult task of coach or best for National or Olympic coaching equips. In this paper it is presented a short summary of the most important methodological achievement in judo match analysis. It is also presented, at light of the last technological improvement, the first systematization toward new fiel...

  13. Pointer Analysis for JavaScript Programming Tools

    DEFF Research Database (Denmark)

    Feldthaus, Asger

    Tools that can assist the programmer with tasks, such as, refactoring or code navigation, have proven popular for Java, C#, and other programming languages. JavaScript is a widely used programming language, and its users could likewise benefit from such tools, but the dynamic nature of the language...... is an obstacle for the development of these. Because of this, tools for JavaScript have long remained ineffective compared to those for many other programming languages. Static pointer analysis can provide a foundation for more powerful tools, although the design of this analysis is itself a complicated endeavor....... In this work, we explore techniques for performing pointer analysis of JavaScript programs, and we find novel applications of these techniques. In particular, we demonstrate how these can be used for code navigation, automatic refactoring, semi-automatic refactoring of incomplete programs, and checking of type...

  14. Rapid analysis of vessel elements (RAVE): a tool for studying physiologic, pathologic and tumor angiogenesis.

    Science.gov (United States)

    Seaman, Marc E; Peirce, Shayn M; Kelly, Kimberly

    2011-01-01

    Quantification of microvascular network structure is important in a myriad of emerging research fields including microvessel remodeling in response to ischemia and drug therapy, tumor angiogenesis, and retinopathy. To mitigate analyst-specific variation in measurements and to ensure that measurements represent actual changes in vessel network structure and morphology, a reliable and automatic tool for quantifying microvascular network architecture is needed. Moreover, an analysis tool capable of acquiring and processing large data sets will facilitate advanced computational analysis and simulation of microvascular growth and remodeling processes and enable more high throughput discovery. To this end, we have produced an automatic and rapid vessel detection and quantification system using a MATLAB graphical user interface (GUI) that vastly reduces time spent on analysis and greatly increases repeatability. Analysis yields numerical measures of vessel volume fraction, vessel length density, fractal dimension (a measure of tortuosity), and radii of murine vascular networks. Because our GUI is open sourced to all, it can be easily modified to measure parameters such as percent coverage of non-endothelial cells, number of loops in a vascular bed, amount of perfusion and two-dimensional branch angle. Importantly, the GUI is compatible with standard fluorescent staining and imaging protocols, but also has utility analyzing brightfield vascular images, obtained, for example, in dorsal skinfold chambers. A manually measured image can be typically completed in 20 minutes to 1 hour. In stark comparison, using our GUI, image analysis time is reduced to around 1 minute. This drastic reduction in analysis time coupled with increased repeatability makes this tool valuable for all vessel research especially those requiring rapid and reproducible results, such as anti-angiogenic drug screening.

  15. Rapid analysis of vessel elements (RAVE: a tool for studying physiologic, pathologic and tumor angiogenesis.

    Directory of Open Access Journals (Sweden)

    Marc E Seaman

    Full Text Available Quantification of microvascular network structure is important in a myriad of emerging research fields including microvessel remodeling in response to ischemia and drug therapy, tumor angiogenesis, and retinopathy. To mitigate analyst-specific variation in measurements and to ensure that measurements represent actual changes in vessel network structure and morphology, a reliable and automatic tool for quantifying microvascular network architecture is needed. Moreover, an analysis tool capable of acquiring and processing large data sets will facilitate advanced computational analysis and simulation of microvascular growth and remodeling processes and enable more high throughput discovery. To this end, we have produced an automatic and rapid vessel detection and quantification system using a MATLAB graphical user interface (GUI that vastly reduces time spent on analysis and greatly increases repeatability. Analysis yields numerical measures of vessel volume fraction, vessel length density, fractal dimension (a measure of tortuosity, and radii of murine vascular networks. Because our GUI is open sourced to all, it can be easily modified to measure parameters such as percent coverage of non-endothelial cells, number of loops in a vascular bed, amount of perfusion and two-dimensional branch angle. Importantly, the GUI is compatible with standard fluorescent staining and imaging protocols, but also has utility analyzing brightfield vascular images, obtained, for example, in dorsal skinfold chambers. A manually measured image can be typically completed in 20 minutes to 1 hour. In stark comparison, using our GUI, image analysis time is reduced to around 1 minute. This drastic reduction in analysis time coupled with increased repeatability makes this tool valuable for all vessel research especially those requiring rapid and reproducible results, such as anti-angiogenic drug screening.

  16. A Microsoft-Excel-based tool for running and critically appraising network meta-analyses--an overview and application of NetMetaXL.

    Science.gov (United States)

    Brown, Stephen; Hutton, Brian; Clifford, Tammy; Coyle, Doug; Grima, Daniel; Wells, George; Cameron, Chris

    2014-09-29

    The use of network meta-analysis has increased dramatically in recent years. WinBUGS, a freely available Bayesian software package, has been the most widely used software package to conduct network meta-analyses. However, the learning curve for WinBUGS can be daunting, especially for new users. Furthermore, critical appraisal of network meta-analyses conducted in WinBUGS can be challenging given its limited data manipulation capabilities and the fact that generation of graphical output from network meta-analyses often relies on different software packages than the analyses themselves. We developed a freely available Microsoft-Excel-based tool called NetMetaXL, programmed in Visual Basic for Applications, which provides an interface for conducting a Bayesian network meta-analysis using WinBUGS from within Microsoft Excel. . This tool allows the user to easily prepare and enter data, set model assumptions, and run the network meta-analysis, with results being automatically displayed in an Excel spreadsheet. It also contains macros that use NetMetaXL's interface to generate evidence network diagrams, forest plots, league tables of pairwise comparisons, probability plots (rankograms), and inconsistency plots within Microsoft Excel. All figures generated are publication quality, thereby increasing the efficiency of knowledge transfer and manuscript preparation. We demonstrate the application of NetMetaXL using data from a network meta-analysis published previously which compares combined resynchronization and implantable defibrillator therapy in left ventricular dysfunction. We replicate results from the previous publication while demonstrating result summaries generated by the software. Use of the freely available NetMetaXL successfully demonstrated its ability to make running network meta-analyses more accessible to novice WinBUGS users by allowing analyses to be conducted entirely within Microsoft Excel. NetMetaXL also allows for more efficient and transparent

  17. Hydrogen Financial Analysis Scenario Tool (H2FAST). Web Tool User's Manual

    Energy Technology Data Exchange (ETDEWEB)

    Bush, B. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Penev, M. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Melaina, M. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zuboy, J. [Independent Consultant, Golden, CO (United States)

    2015-05-11

    The Hydrogen Financial Analysis Scenario Tool (H2FAST) provides a quick and convenient indepth financial analysis for hydrogen fueling stations. This manual describes how to use the H2FAST web tool, which is one of three H2FAST formats developed by the National Renewable Energy Laboratory (NREL). Although all of the formats are based on the same financial computations and conform to generally accepted accounting principles (FASAB 2014, Investopedia 2014), each format provides a different level of complexity and user interactivity.

  18. Ensemble approach to the analysis of weighted networks

    Science.gov (United States)

    Ahnert, S. E.; Garlaschelli, D.; Fink, T. M. A.; Caldarelli, G.

    2007-07-01

    We present an approach to the analysis of weighted networks, by providing a straightforward generalization of any network measure defined on unweighted networks, such as the average degree of the nearest neighbors, the clustering coefficient, the “betweenness,” the distance between two nodes, and the diameter of a network. All these measures are well established for unweighted networks but have hitherto proven difficult to define for weighted networks. Our approach is based on the translation of a weighted network into an ensemble of edges. Further introducing this approach we demonstrate its advantages by applying the clustering coefficient constructed in this way to two real-world weighted networks.

  19. Hearing health network: a spatial analysis

    Directory of Open Access Journals (Sweden)

    Camila Ferreira de Rezende

    2015-06-01

    Full Text Available INTRODUCTION: In order to meet the demands of the patient population with hearing impairment, the Hearing Health Care Network was created, consisting of primary care actions of medium and high complexity. Spatial analysis through geoprocessing is a way to understand the organization of such services. OBJECTIVE: To analyze the organization of the Hearing Health Care Network of the State of Minas Gerais. METHODS: Cross-sectional analytical study using geoprocessing techniques. The absolute frequency and the frequency per 1000 inhabitants of the following variables were analyzed: assessment and diagnosis, selection and adaptation of hearing aids, follow-up, and speech therapy. The spatial analysis unit was the health micro-region. RESULTS: The assessment and diagnosis, selection, and adaptation of hearing aids and follow-up had a higher absolute number in the micro-regions with hearing health services. The follow-up procedure showed the lowest occurrence. Speech therapy showed higher occurrence in the state, both in absolute numbers, as well as per population. CONCLUSION: The use of geoprocessing techniques allowed the identification of the care flow as a function of the procedure performance frequency, population concentration, and territory distribution. All procedures offered by the Hearing Health Care Network are performed for users of all micro-regions of the state.

  20. Design Criteria For Networked Image Analysis System

    Science.gov (United States)

    Reader, Cliff; Nitteberg, Alan

    1982-01-01

    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  1. MORPHIN: a web tool for human disease research by projecting model organism biology onto a human integrated gene network.

    Science.gov (United States)

    Hwang, Sohyun; Kim, Eiru; Yang, Sunmo; Marcotte, Edward M; Lee, Insuk

    2014-07-01

    Despite recent advances in human genetics, model organisms are indispensable for human disease research. Most human disease pathways are evolutionally conserved among other species, where they may phenocopy the human condition or be associated with seemingly unrelated phenotypes. Much of the known gene-to-phenotype association information is distributed across diverse databases, growing rapidly due to new experimental techniques. Accessible bioinformatics tools will therefore facilitate translation of discoveries from model organisms into human disease biology. Here, we present a web-based discovery tool for human disease studies, MORPHIN (model organisms projected on a human integrated gene network), which prioritizes the most relevant human diseases for a given set of model organism genes, potentially highlighting new model systems for human diseases and providing context to model organism studies. Conceptually, MORPHIN investigates human diseases by an orthology-based projection of a set of model organism genes onto a genome-scale human gene network. MORPHIN then prioritizes human diseases by relevance to the projected model organism genes using two distinct methods: a conventional overlap-based gene set enrichment analysis and a network-based measure of closeness between the query and disease gene sets capable of detecting associations undetectable by the conventional overlap-based methods. MORPHIN is freely accessible at http://www.inetbio.org/morphin. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  2. Capacity analysis of wireless mesh networks | Gumel | Nigerian ...

    African Journals Online (AJOL)

    The next generation wireless· netWorks experienced agreat development with emergence of wireless mesh networks (WMNs), which can be regarded as a realistic solution that provides wireless broadband access. The limited available bandwidth makes capacity analysis of the network very essential. While the network ...

  3. Modelling Social Mobilisation – An interdisciplinary exploration of Twitter as a mediating tool for social acts and information networks

    Directory of Open Access Journals (Sweden)

    James D Amor

    2013-10-01

    Full Text Available In recent years, researchers, social commentators and the mass media have turned their attention to shifts in the use of social media for political and social action. This article provides an overview of the recent discussions focusing on how Twitter specifically functions as a mediating tool for social acts. We present findings from a recent pilot project exploring the mechanics of disseminating information via Twitter across a dynamic human network in order to contribute to an understanding of how people use social media to share information and prompt others into action, and outline some approaches for performing this analysis. Taking the perspective of communities of users operating in hybrid spaces, we make recommendations for further research in this field. Key words: Twitter, hybrid spaces, social networks, social acts, information flow

  4. Clustering Financial Time Series by Network Community Analysis

    Science.gov (United States)

    Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

    In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

  5. Activity Recognition Using Complex Network Analysis.

    Science.gov (United States)

    Jalloul, Nahed; Poree, Fabienne; Viardot, Geoffrey; L'Hostis, Phillipe; Carrault, Guy

    2017-10-12

    In this paper, we perform complex network analysis on a connectivity dataset retrieved from a monitoring system in order to classify simple daily activities. The monitoring system is composed of a set of wearable sensing modules positioned on the subject's body and the connectivity data consists of the correlation between each pair of modules. A number of network measures are then computed followed by the application of statistical significance and feature selection methods. These methods were implemented for the purpose of reducing the total number of modules in the monitoring system required to provide accurate activity classification. The obtained results show that an overall accuracy of 84.6% for activity classification is achieved, using a Random Forest (RF) classifier, and when considering a monitoring system composed of only two modules positioned at the Neck and Thigh of the subject's body.

  6. Social networks as a new tool of information warfare in the modern world

    Directory of Open Access Journals (Sweden)

    B. W. Kovalevych

    2014-03-01

    Full Text Available With the rapid development of information technologies, especially the Internet, people are becoming increasingly dependent on information that surrounds them. And social networks, where a person spends most of their time, become the ideal instruments of influence on the people consciousness and information warfare. Due to psychological factors ( such as ‘spiral of silence’, the herd instinct, the entire credibility of published information, opinion leaders, the desire for self­realization or replacement of reality that influence the human behavior in the network and the use of models of influence (model of network attack, model of involving users as volunteers, total block model, social networks become a platform for the dissemination of political ideas, ideologies and implementation of the ‘color revolutions’. However, social media play a positive role, especially in the establishment of civil society and the free flow of information. Positive or negative impact of networks primary depends on the purpose of use of social networking tools.

  7. Integrated Adaptive Analysis and Visualization of Satellite Network Data Project

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop a system that enables integrated and adaptive analysis and visualization of satellite network management data. Integrated analysis and...

  8. Analysis of Ego Network Structure in Online Social Networks

    OpenAIRE

    Arnaboldi, Valerio; Conti, Marco; Passarella, Andrea; Pezzoni, Fabio

    2012-01-01

    Results about offline social networks demonstrated that the social relationships that an individual (ego) maintains with other people (alters) can be organised into different groups according to the ego network model. In this model the ego can be seen as the centre of a series of layers of increasing size. Social relationships between ego and alters in layers close to ego are stronger than those belonging to more external layers. Online Social Networks are becoming a fundamental medium for hu...

  9. Understanding resilience in industrial symbiosis networks: insights from network analysis.

    Science.gov (United States)

    Chopra, Shauhrat S; Khanna, Vikas

    2014-08-01

    Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks. Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. FastGCN: a GPU accelerated tool for fast gene co-expression networks.

    Directory of Open Access Journals (Sweden)

    Meimei Liang

    Full Text Available Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

  11. FastGCN: a GPU accelerated tool for fast gene co-expression networks.

    Science.gov (United States)

    Liang, Meimei; Zhang, Futao; Jin, Gulei; Zhu, Jun

    2015-01-01

    Gene co-expression networks comprise one type of valuable biological networks. Many methods and tools have been published to construct gene co-expression networks; however, most of these tools and methods are inconvenient and time consuming for large datasets. We have developed a user-friendly, accelerated and optimized tool for constructing gene co-expression networks that can fully harness the parallel nature of GPU (Graphic Processing Unit) architectures. Genetic entropies were exploited to filter out genes with no or small expression changes in the raw data preprocessing step. Pearson correlation coefficients were then calculated. After that, we normalized these coefficients and employed the False Discovery Rate to control the multiple tests. At last, modules identification was conducted to construct the co-expression networks. All of these calculations were implemented on a GPU. We also compressed the coefficient matrix to save space. We compared the performance of the GPU implementation with those of multi-core CPU implementations with 16 CPU threads, single-thread C/C++ implementation and single-thread R implementation. Our results show that GPU implementation largely outperforms single-thread C/C++ implementation and single-thread R implementation, and GPU implementation outperforms multi-core CPU implementation when the number of genes increases. With the test dataset containing 16,000 genes and 590 individuals, we can achieve greater than 63 times the speed using a GPU implementation compared with a single-thread R implementation when 50 percent of genes were filtered out and about 80 times the speed when no genes were filtered out.

  12. MonaLisa--visualization and analysis of functional modules in biochemical networks.

    Science.gov (United States)

    Einloft, Jens; Ackermann, Jörg; Nöthen, Joachim; Koch, Ina

    2013-06-01

    Structural modeling of biochemical networks enables qualitative as well as quantitative analysis of those networks. Automated network decomposition into functional modules is a crucial point in network analysis. Although there exist approaches for the analysis of networks, there is no open source tool available that combines editing, visualization and the computation of steady-state functional modules. We introduce a new tool called MonaLisa, which combines computation and visualization of functional modules as well as an editor for biochemical Petri nets. The analysis techniques allow for network decomposition into functional modules, for example t-invariants (elementary modes), maximal common transition sets, minimal cut sets and t-clusters. The graphical user interface provides various functionalities to construct and modify networks as well as to visualize the results of the analysis. MonaLisa is licensed under the Artistic License 2.0. It is freely available at http://www.bioinformatik.uni-frankfurt.de/software.html. MonaLisa requires at least Java 6 and runs under Linux, Microsoft Windows and Mac OS.

  13. Social networks as a tool for science communication and public engagement: focus on Twitter.

    Science.gov (United States)

    López-Goñi, Ignacio; Sánchez-Angulo, Manuel

    2018-02-01

    Social networks have been used to teach and engage people about the importance of science. The integration of social networks in the daily routines of faculties and scientists is strongly recommended to increase their personal brand, improve their skills, enhance their visibility, share and communicate science to society, promote scientific culture, and even as a tool for teaching and learning. Here we review the use of Twitter in science and comment on our previous experience of using this social network as a platform for a Massive Online Open Course (MOOC) in Spain and Latin America. We propose to extend this strategy to a pan-European Microbiology MOOC in the near future. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  14. Speech Recognizing for Presentation Tool Navigation Using Back Propagation Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Hasanah Nur

    2016-01-01

    Full Text Available Backpropagation Artificial Neural Network (ANN is a well known branch of Artificial Intelligence and has been proven to solve various problems of complex speech recognizing in health [1], [2], education [4] and engineering [3]. Today, many kinds of presentation tools are used by society. One popular example is MsPowerpoint. The transition process between slides in presentation tools will be more easily done through speech, the sound emitted directly by the user during the presentation. This study uses research and development to create a simulation using Backpropagation ANN for speech recognition from number one to five to navigate slides of the presentation tool. The Backpropagation ANN consists of one input layer, one hidden layer with 100 neurons and one output layer. The simulation is built by using a Neural Network Toolbox Matlab R2014a. Speech samples were taken from five different people with wav format. This research shows that the Backpropagation ANN can be used as navigation through speech with 96% accuracy rate based on the network training result. Thesimulation can produce 63% accuracy based on 100 new speech samples from various sources.

  15. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    Up to now, many network models on synchronization have been put forward, such as, the small-world network, directed network, neural network etc. Previous efforts were mainly to study the outer relationship between the nodes. But, the inner interaction is always overlooked. Afterwards, the coloured network model has ...

  16. On-line manipulator tool condition monitoring based on vibration analysis

    Science.gov (United States)

    Gierlak, Piotr; Burghardt, Andrzej; Szybicki, Dariusz; Szuster, Marcin; Muszyńska, Magdalena

    2017-05-01

    This article presents a method of processing and analyzing the measurement signals used in the problem of diagnosing the state of a manipulator's tool. The analysis of the signals was performed within the domain of time and frequency. The signals utilized in the analysis were the mechanical vibrations and the rotation speed of the tool. The database for analysis was obtained in a research environment and it includes the instances of the functioning of the system with tool in good technical state as well as instances with a damaged tool. With the intent at reducing the data, the registered signals are represented with the use of selected features. The preliminary selection of the significant features of the signals is made with the use of the sequential feature selection procedure. The reduced set of features is used for the creation of a tool condition classifier, which has a form of an artificial neural network. The obtained classifier operates on-line on robotized system and generates diagnostic information on the state of the tool.

  17. The AttentionTrip: A game-like tool for measuring the networks of attention.

    Science.gov (United States)

    Klein, Raymond M; Hassan, Tariq; Wilson, Graham; Ishigami, Yoko; Mulle, Jonathan

    2017-09-01

    Recognizing that attention is not a unitary system, the Attention Network Test (ANT) and its variants were developed to measure the efficacy of the multiple components of attention. One potential weakness of these tests (ANTs) is that they are unengaging. This poses a problem when particular groups are tested (e.g., young children), when more stable measures of performance are desirable (and can only be achieved in longer testing sessions) and when repeated testing is necessary. Here we describe the evolution of a game-like tool, which we call the AttentionTrip©, that is suitable for investigating three isolable attentional networks (alerting, orienting, and executive functions). Utilizing this tool we were able to generate reasonable network scores for alerting, executive control (from both the flanker and Simon effects), endogenous orienting and, after some motivated modifications, exogenous orienting. Split-half reliabilities of the alerting and executive (flanker) network scores were considerably higher than those reported by MacLeod et al. (2010) in their psychometric review of the ANT. Informal observations (e.g., some participants asking if they could keep doing the task when their session was over) suggesting that the AttentionTrip is considerably more engaging than the traditional ANT have been confirmed in a head-to-head comparison (Vallis & Klein, 2016). The AttentionTrip@ is available now for research purposes. A tablet version, which will have greater clinical utility, is under development. Copyright © 2017 Elsevier B.V. All rights reserved.

  18. Hybrid Neural Network Approach Based Tool for the Modelling of Photovoltaic Panels

    Directory of Open Access Journals (Sweden)

    Antonino Laudani

    2015-01-01

    Full Text Available A hybrid neural network approach based tool for identifying the photovoltaic one-diode model is presented. The generalization capabilities of neural networks are used together with the robustness of the reduced form of one-diode model. Indeed, from the studies performed by the authors and the works present in the literature, it was found that a direct computation of the five parameters via multiple inputs and multiple outputs neural network is a very difficult task. The reduced form consists in a series of explicit formulae for the support to the neural network that, in our case, is aimed at predicting just two parameters among the five ones identifying the model: the other three parameters are computed by reduced form. The present hybrid approach is efficient from the computational cost point of view and accurate in the estimation of the five parameters. It constitutes a complete and extremely easy tool suitable to be implemented in a microcontroller based architecture. Validations are made on about 10000 PV panels belonging to the California Energy Commission database.

  19. PLIO: a generic tool for real-time operational predictive optimal control of water networks.

    Science.gov (United States)

    Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M

    2011-01-01

    This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation).

  20. A computer aided tolerancing tool, II: tolerance analysis

    NARCIS (Netherlands)

    Salomons, O.W.; Haalboom, F.J.; Jonge poerink, H.J.; van Slooten, F.; van Slooten, F.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

    1996-01-01

    A computer aided tolerance analysis tool is presented that assists the designer in evaluating worst case quality of assembly after tolerances have been specified. In tolerance analysis calculations, sets of equations are generated. The number of equations can be restricted by using a minimum number

  1. Gender analysis of use of participatory tools among extension ...

    African Journals Online (AJOL)

    (c2 = 0.833, p = 0.361; t = 0.737, p = 0.737, CC = 0.396) Participatory tools used by both male and female extension personnel include resource map, mobility map, transect map, focus group discussion, venn diagram, seasonal calendar, SWOT analysis, semistructured interview, daily activity schedule, resource analysis, ...

  2. LTE, WiMAX and WLAN network design, optimization and performance analysis

    CERN Document Server

    Korowajczuk, Leonhard

    2011-01-01

    A technological overview of LTE and WiMAX LTE, WiMAX and WLAN Network Design, Optimization and Performance Analysis provides a practical guide to LTE and WiMAX technologies introducing various tools and concepts used within. In addition, topics such as traffic modelling of IP-centric networks, RF propagation, fading, mobility, and indoor coverage are explored; new techniques which increase throughput such as MIMO and AAS technology are highlighted; and simulation, network design and performance analysis are also examined. Finally, in the latter part of the book Korowajczuk gives a step-by-step

  3. Designed tools for analysis of lithography patterns and nanostructures

    Science.gov (United States)

    Dervillé, Alexandre; Baderot, Julien; Bernard, Guilhem; Foucher, Johann; Grönqvist, Hanna; Labrosse, Aurélien; Martinez, Sergio; Zimmermann, Yann

    2017-03-01

    We introduce a set of designed tools for the analysis of lithography patterns and nano structures. The classical metrological analysis of these objects has the drawbacks of being time consuming, requiring manual tuning and lacking robustness and user friendliness. With the goal of improving the current situation, we propose new image processing tools at different levels: semi automatic, automatic and machine-learning enhanced tools. The complete set of tools has been integrated into a software platform designed to transform the lab into a virtual fab. The underlying idea is to master nano processes at the research and development level by accelerating the access to knowledge and hence speed up the implementation in product lines.

  4. UDAT: A multi-purpose data analysis tool

    Science.gov (United States)

    Shamir, Lior

    2017-04-01

    UDAT is a pattern recognition tool for mass analysis of various types of data, including image and audio. Based on its WND-CHARM (ascl:1312.002) prototype, UDAT computed a large set of numerical content descriptors from each file it analyzes, and selects the most informative features using statistical analysis. The tool can perform automatic classification of galaxy images by training with annotated galaxy images. It also has unsupervised learning capabilities, such as query-by-example of galaxies based on morphology. That is, given an input galaxy image of interest, the tool can search through a large database of images to retrieve the galaxies that are the most similar to the query image. The downside of the tool is its computational complexity, which in most cases will require a small or medium cluster.

  5. Analysis of Alternatives for Risk Assessment Methodologies and Tools

    Energy Technology Data Exchange (ETDEWEB)

    Nachtigal, Noel M. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). System Analytics; Fruetel, Julia A. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Gleason, Nathaniel J. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Helms, Jovana [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Imbro, Dennis Raymond [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis; Sumner, Matthew C. [Sandia National Lab. (SNL-CA), Livermore, CA (United States). Systems Research and Analysis

    2013-10-01

    The purpose of this document is to provide a basic overview and understanding of risk assessment methodologies and tools from the literature and to assess the suitability of these methodologies and tools for cyber risk assessment. Sandia National Laboratories (SNL) performed this review in support of risk modeling activities performed for the Stakeholder Engagement and Cyber Infrastructure Resilience (SECIR) division of the Department of Homeland Security (DHS) Office of Cybersecurity and Communications (CS&C). The set of methodologies and tools covered in this document is not intended to be exhaustive; instead, it focuses on those that are commonly used in the risk assessment community. The classification of methodologies and tools was performed by a group of analysts with experience in risk analysis and cybersecurity, and the resulting analysis of alternatives has been tailored to address the needs of a cyber risk assessment.

  6. Network meta-analysis: an introduction for clinicians.

    Science.gov (United States)

    Rouse, Benjamin; Chaimani, Anna; Li, Tianjing

    2017-02-01

    Network meta-analysis is a technique for comparing multiple treatments simultaneously in a single analysis by combining direct and indirect evidence within a network of randomized controlled trials. Network meta-analysis may assist assessing the comparative effectiveness of different treatments regularly used in clinical practice and, therefore, has become attractive among clinicians. However, if proper caution is not taken in conducting and interpreting network meta-analysis, inferences might be biased. The aim of this paper is to illustrate the process of network meta-analysis with the aid of a working example on first-line medical treatment for primary open-angle glaucoma. We discuss the key assumption of network meta-analysis, as well as the unique considerations for developing appropriate research questions, conducting the literature search, abstracting data, performing qualitative and quantitative synthesis, presenting results, drawing conclusions, and reporting the findings in a network meta-analysis.

  7. Applications of social media and social network analysis

    CERN Document Server

    Kazienko, Przemyslaw

    2015-01-01

    This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun

  8. Importance and performance evaluation tools for small and medium companies: critical analysis of national versus international literature

    Directory of Open Access Journals (Sweden)

    Sandro César Bortoluzzi

    2015-12-01

    Full Text Available The research aims to map the importance and performance evaluation tools for small and medium companies. This descriptive and qualitative study analyzed 33 national articles and 21 international ones. Regarding the importance of performance evaluation for small and medium companies, the literature highlights: (i it increases the success of the network; (ii it is useful for management; (iii it strengthens competitiveness; (iv it consolidates cooperation; and, (v it increases trust among partners. Comparing the national versus international literature on the importance of performance evaluation for small and medium companies, it can be noticed similar and complementary aspects, that is, there is not disagreement between the authors. The authors use tools consolidated in the literature, such as Balanced Scorecard; Benchmarking; Performance Prism and tools proposed specifically to evaluate small and medium networks. The main dimensions evaluated are: (i exchange of information; (ii value management in networks; (Iii level of network maturity; (iv benefits of collaboration; (v social capital; (vi collective efficiency; (vii network life cycle; (viii efficiency and inefficiency of the networks; and, (ix existence and intensity of the relationship between partners. The critical analysis regarding the performance evaluation concept adopted in the present study shows that the tools proposed or implemented to evaluate small and medium business networks have gaps in the process to identify criteria, measure ordinal and cardinally, integrate and generate actions of improvement.

  9. Computer Tools for Construction, Modification and Analysis of Petri Nets

    DEFF Research Database (Denmark)

    Jensen, Kurt

    1987-01-01

    The practical use of Petri nets is — just as any other description technique — very dependent on the existence of adequate computer tools, which may assist the user to cope with the many details of a large description. For Petri nets there is a need for tools supporting construction of nets......, as well as modification and analysis. Graphical work stations provide the opportunity to work — not only with textual representations of Petri nets — but also directly with the graphical representations. This paper describes some of the different kinds of tools which are needed in the Petri net area...

  10. Tools and Algorithms for the Construction and Analysis of Systems

    DEFF Research Database (Denmark)

    This book constitutes the refereed proceedings of the 10th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2004, held in Barcelona, Spain in March/April 2004. The 37 revised full papers and 6 revised tool demonstration papers presented were...... carefully reviewed and selected from a total of 162 submissions. The papers are organized in topical sections on theorem proving, probabilistic model checking, testing, tools, explicit state and Petri nets, scheduling, constraint solving, timed systems, case studies, software, temporal logic, abstraction...

  11. Tools and Algorithms for the Construction and Analysis of Systems

    DEFF Research Database (Denmark)

    carefully reviewed and selected from a total of 162 submissions. The papers are organized in topical sections on theorem proving, probabilistic model checking, testing, tools, explicit state and Petri nets, scheduling, constraint solving, timed systems, case studies, software, temporal logic, abstraction......This book constitutes the refereed proceedings of the 10th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2004, held in Barcelona, Spain in March/April 2004. The 37 revised full papers and 6 revised tool demonstration papers presented were...

  12. Tools for voltage stability analysis, including a probabilistic approach

    Energy Technology Data Exchange (ETDEWEB)

    Vieira Filho, X.; Martins, N.; Bianco, A.; Pinto, H.J.C.P. [Centro de Pesquisas de Energia Eletrica (CEPEL), Rio de Janeiro, RJ (Brazil); Pereira, M.V.F. [Power System Research (PSR), Inc., Rio de Janeiro, RJ (Brazil); Gomes, P.; Santos, M.G. dos [ELETROBRAS, Rio de Janeiro, RJ (Brazil)

    1994-12-31

    This paper reviews some voltage stability analysis tools that are being used or envisioned for expansion and operational planning studies in the Brazilian system, as well as, their applications. The paper also shows that deterministic tools can be linked together in a probabilistic framework, so as to provide complementary help to the analyst in choosing the most adequate operation strategies, or the best planning solutions for a given system. (author) 43 refs., 8 figs., 8 tabs.

  13. Social sciences via network analysis and computation

    CERN Document Server

    Kanduc, Tadej

    2015-01-01

    In recent years information and communication technologies have gained significant importance in the social sciences. Because there is such rapid growth of knowledge, methods and computer infrastructure, research can now seamlessly connect interdisciplinary fields such as business process management, data processing and mathematics. This study presents some of the latest results, practices and state-of-the-art approaches in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences. It also covers various real-life examples such as t

  14. Network Analysis and Application Control Software based on Client-Server Architecture

    OpenAIRE

    Mohan, Ramya

    2013-01-01

    This paper outlines a comprehensive model to increase system efficiency, preserve network bandwidth, monitor incoming and outgoing packets, ensure the security of confidential files and reduce power wastage in an organization. This model illustrates the use and potential application of a Network Analysis Tool (NAT) in a multi-computer set-up of any scale. The model is designed to run in the background and not hamper any currently executing applications, while using minimum system resources. I...

  15. Object-Oriented Multi-Disciplinary Design, Analysis, and Optimization Tool

    Science.gov (United States)

    Pak, Chan-gi

    2011-01-01

    An Object-Oriented Optimization (O3) tool was developed that leverages existing tools and practices, and allows the easy integration and adoption of new state-of-the-art software. At the heart of the O3 tool is the Central Executive Module (CEM), which can integrate disparate software packages in a cross platform network environment so as to quickly perform optimization and design tasks in a cohesive, streamlined manner. This object-oriented framework can integrate the analysis codes for multiple disciplines instead of relying on one code to perform the analysis for all disciplines. The CEM was written in FORTRAN and the script commands for each performance index were submitted through the use of the FORTRAN Call System command. In this CEM, the user chooses an optimization methodology, defines objective and constraint functions from performance indices, and provides starting and side constraints for continuous as well as discrete design variables. The structural analysis modules such as computations of the structural weight, stress, deflection, buckling, and flutter and divergence speeds have been developed and incorporated into the O3 tool to build an object-oriented Multidisciplinary Design, Analysis, and Optimization (MDAO) tool.

  16. BISON: bio-interface for the semi-global analysis of network patterns

    Directory of Open Access Journals (Sweden)

    Besemann Christopher

    2006-11-01

    Full Text Available Abstract Background The large amount of genomics data that have accumulated over the past decade require extensive data mining. However, the global nature of data mining, which includes pattern mining, poses difficulties for users who want to study specific questions in a more local environment. This creates a need for techniques that allow a localized analysis of globally determined patterns. Results We developed a tool that determines and evaluates global patterns based on protein property and network information, while providing all the benefits of a perspective that is targeted at biologist users with specific goals and interests. Our tool uses our own data mining techniques, integrated into current visualization and navigation techniques. The functionality of the tool is discussed in the context of the transcriptional network of regulation in the enteric bacterium Escherichia coli. Two biological questions were asked: (i Which functional categories of proteins (identified by hidden Markov models are regulated by a regulator with a specific domain? (ii Which regulators are involved in the regulation of proteins that contain a common hidden Markov model? Using these examples, we explain the gene-centered and pattern-centered analysis that the tool permits. Conclusion In summary, we have a tool that can be used for a wide variety of applications in biology, medicine, or agriculture. The pattern mining engine is global in the way that patterns are determined across the entire network. The tool still permits a localized analysis for users who want to analyze a subportion of the total network. We have named the tool BISON (Bio-Interface for the Semi-global analysis Of Network patterns.

  17. SKYNET: an efficient and robust neural network training tool for machine learning in astronomy

    Science.gov (United States)

    Graff, Philip; Feroz, Farhan; Hobson, Michael P.; Lasenby, Anthony

    2014-06-01

    We present the first public release of our generic neural network training algorithm, called SKYNET. This efficient and robust machine learning tool is able to train large and deep feed-forward neural networks, including autoencoders, for use in a wide range of supervised and unsupervised learning applications, such as regression, classification, density estimation, clustering and dimensionality reduction. SKYNET uses a `pre-training' method to obtain a set of network parameters that has empirically been shown to be close to a good solution, followed by further optimization using a regularized variant of Newton's method, where the level of regularization is determined and adjusted automatically; the latter uses second-order derivative information to improve convergence, but without the need to evaluate or store the full Hessian matrix, by using a fast approximate method to calculate Hessian-vector products. This combination of methods allows for the training of complicated networks that are difficult to optimize using standard backpropagation techniques. SKYNET employs convergence criteria that naturally prevent overfitting, and also includes a fast algorithm for estimating the accuracy of network outputs. The utility and flexibility of SKYNET are demonstrated by application to a number of toy problems, and to astronomical problems focusing on the recovery of structure from blurred and noisy images, the identification of gamma-ray bursters, and the compression and denoising of galaxy images. The SKYNET software, which is implemented in standard ANSI C and fully parallelized using MPI, is available at http://www.mrao.cam.ac.uk/software/skynet/.

  18. Analysis of regulatory networks constructed based on gene ...

    Indian Academy of Sciences (India)

    Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the incidence mechanism of pituitary ...

  19. Analysis of regulatory networks constructed based on gene ...

    Indian Academy of Sciences (India)

    2013-12-09

    Dec 9, 2013 ... Abstract. Gene coexpression patterns can reveal gene collections with functional consistency. This study systematically constructs regulatory networks for pituitary tumours by integrating gene coexpression, transcriptional and posttranscriptional regulation. Through network analysis, we elaborate the ...

  20. Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios

    DEFF Research Database (Denmark)

    Manzano, M.; Marzo, J. L.; Calle, E.

    2012-01-01

    on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....