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Sample records for network analysis sna

  1. 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.

  2. Social Technology and Development in Telêmaco Borba/BRAZIL from the Social Network Analysis (SNA)

    OpenAIRE

    Heloísa de Puppi e Silva; Christian Luiz da Silva; Cleverson Vitorio Andreoli; Cristina Maria Souto Ferigotti

    2013-01-01

    This article observes the relationship among economic activity and local agents, by means of Social Networks Analysis (SNA) and showing the historical aspects on local development of the town of Telêmaco Borba, in the State of Paraná, Brazil. The social network can be understood as a Social Technology shaped by relationships among local agents and mapped by SNA. The relevance is given by the enrichment of knowledge by SNA, focusing on understanding the social technology as the basis of strate...

  3. Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

    Science.gov (United States)

    Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah

    2017-03-01

    Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.

  4. Social Technology and Development in Telêmaco Borba/BRAZIL from the Social Network Analysis (SNA

    Directory of Open Access Journals (Sweden)

    Heloísa de Puppi e Silva

    2013-04-01

    Full Text Available This article observes the relationship among economic activity and local agents, by means of Social Networks Analysis (SNA and showing the historical aspects on local development of the town of Telêmaco Borba, in the State of Paraná, Brazil. The social network can be understood as a Social Technology shaped by relationships among local agents and mapped by SNA. The relevance is given by the enrichment of knowledge by SNA, focusing on understanding the social technology as the basis of strategic formulation for actions to local development. The method used exploratory research and data from primary sources of a structured questionnaire for interviews. The study reveals that the interaction network among agents is elemental to creating capacities to its own identity and innovative solutions for local development. Pulp and paper activity is a cultural landmark and establishes a reference hard link and dependence for local actors.

  5. An investigation of Pierre de Wet’s role in the Afrikaans film industry using social network analysis (SNA

    Directory of Open Access Journals (Sweden)

    Burgert A. Senekal

    2014-02-01

    Full Text Available Although the film industry – like the literary system – can be described as a cultural system or field, systems theory remains largely unexplored in South African film studies, as does the more recent network theory. Systems theory and network theory both emphasise the relationships of an entity within a larger context, arguing that an entity should be studied within the relationships in which it functions. Recently, researchers have suggested that network theory can be integrated with polysystem theory to study the interactions between entities in the literary system. This article illustrates the potential of using social network analysis (SNA as an investigative tool to identify and describe the role of an entity within the context of the film industry by focusing on one of the seminal Afrikaans film makers: Pierre de Wet. Pierre de Wet has been intricately involved with the beginnings of the Afrikaans film industry, collaborating with, amongst others, some of the most prolific film editors, producers,cinematographers and music composers. His major collaborators are highlighted as well as his central position in the Afrikaans film industry, taking into account the entire Afrikaans film industry from its origin to the contemporary period. The article also makes suggestions for further research.

  6. Carcinogenesis and Chemotherapy Viewed from the Perspective of Stoichiometric Network Analysis (SNA: What Can the Biological System of the Elements Contribute to an Understanding of Tumour Induction by Elemental Chemical Noxae (e.g., Ni2+, Cd2+ and to an Understanding of Chemotherapy?

    Directory of Open Access Journals (Sweden)

    Stefan Franzle

    2003-01-01

    Full Text Available The biological application of stoichiometric network analysis (SNA permits an understanding of tumour induction, carcinogenesis, and chemotherapy. Starting from the Biological System of the Elements, which provides a comprehensive treatment of the functions and distributions of chemical (trace elements in biology, an attempt is made to interrelate the essential feature of biology and — regrettably — of tumour genesis by superimposing SNA reasoning on common features of all crucial biological processes. For this purpose, aspects, effects and drawbacks of autocatalysis (identical reproduction which can occur either under control or without control [in tumours] are linked with the known facts about element distributions in living beings and about interference of metals with tumours (in terms of both chemotherapy and carcinogenesis. The essential role of autocatalysis in biology and the drawbacks of either controlled or spontaneous cell division can be used to understand crucial aspects of carcinogenesis and chemotherapy because SNA describes and predicts effects of autocatalysis, including phase effects that may be due to some kind of intervention. The SNA-based classifications of autocatalytic networks in cell biology are outlined here to identify new approaches to chemotherapy.

  7. Methodological proposal for the study of business incubators based on Social Network Analysis (SNA and knowledge networks: the case of the UAEMex Propuesta metodológica para el estudio de incubadoras de empresas a partir de los enfoques Análisis de Redes Sociales (ARS y redes de conocimiento: el caso de las incubadoras de la UAEMex

    Directory of Open Access Journals (Sweden)

    Rosa Azalea Canales García

    2013-05-01

    Full Text Available The rapid changes that have occurred regarding technology and markets have resulted in fostering the development of networks among different agents (individuals, businesses, uni­versities, and governments in an attempt to exchange both tangible (infrastructure and intangible (knowledge resources. The aim of this article is to propose a methodological framework based on Social Network Analysis (SNA and knowledge networks in order to study business incubators as structures that encourage the development of networks and knowledge exchanges. Specifically, this work examines the case of the twelve business in­cubators from the UAEMex, and the relationships that exist between them. A questionnaire was applied to the coordinators of the business incubators as the primary source of informa­tion. A relevant conclusion is that the proposed methodology describes an alternative way to examine business incubators from the point of view of networks and knowledge.Ante los rápidos cambios tecnológicos y en los mercados, la premisa principal ha sido incentivar la configuración de redes entre diversos agentes (individuos, empresas, univer­sidades, gobiernos con la finalidad de intercambiar recursos tangibles (infraestructura e intangibles (conocimiento. El objetivo de este artículo es proponer un marco metodológico a partir de la conjunción de los enfoques Análisis de Redes Sociales (ARS y redes de cono­cimiento con el fin de estudiar las incubadoras de empresas como estructuras que permi­ten conformar redes e intercambiar conocimiento. Específicamente, este trabajo examina el caso de las doce incubadoras de empresas de la Universidad Autónoma del Estado de México (UAEMex y las relaciones que establecen entre ellas. Para obtener información al respecto fue necesario aplicar un cuestionario a los coordinadores de las mismas. Una con­clusión relevante es que la propuesta metodológica describe una manera alternativa para examinar las incubadoras

  8. 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 ...

  9. Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks

    National Research Council Canada - National Science Library

    Kelman, Ilan; Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H; Evers, Yvette; Curran, Marina Martin; Williams, Richard J; Berlow, Eric L

    2016-01-01

    This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics...

  10. Social Network Analysis of a Supply Network Structural Investigation of the South Korean Automotive Industry

    OpenAIRE

    Kim, Jin-Baek

    2015-01-01

    Part 3: Knowledge Based Production Management; International audience; In this paper, we analyzed the structure of the South Korean automotive industry using social network analysis (SNA) metrics. Based on the data collected from 275 companies, a social network model of the supply network was constructed. Centrality measures in the SNA field were used to interpret the result and identify key companies. The results show that SNA metrics can be useful to understand the structure of a supply net...

  11. Towards the integration of social network analysis in an inter-organizational networks perspective

    DEFF Research Database (Denmark)

    Bergenholtz, Carsten; Waldstrøm, Christian

    This conceptual paper deals with the issue of studying inter-organizational networks while applying social network analysis (SNA). SNA is a widely recognized technique in network research, particularly within intra-organizational settings, while there seems to be a significant gap in the inter......-organizational setting. Based on a literature review of both SNA as a methodology and/or theory and the field of inter-organizational networks, the aim is to gain an overview in order to provide a clear setting for SNA in inter-organizational research....

  12. 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

  13. [Social network analysis of animal behavioral ecology: a cross-discipline approach].

    Science.gov (United States)

    Zhang, Peng

    2013-12-01

    Social network analysis (SNA) is a framework used to study the structure of societies. As an umbrella term that encompasses various tools of graph theory and mathematical models to visualize networks, SNA allows researchers to detect and quantify patterns in social networks. Within SNA, individuals are not independent, but are symbiotic or linked with one another in a network. Given its powerful analytical tools, SNA is capable of addressing a range of animal behaviors, and has accordingly become increasingly popular in behavioral ecology studies examining such notions as mate choice/sexual selection, cooperation, information flow and disease transition, behavioral strategies of individuals, fitness consequences of sociality and network stability. Nevertheless, SNA it relatively underutilized among Chinese behavioral ecologists. This study aims at highlighting the benefits of SNA in studying animal behaviors in order to promote greater utilization of SNA within Chinese studies. By first introducing social network theory and demonstrating how social networks can influence individual and collective behaviors, this paper provide a prospective overview of SNA's general utilization for the study of animal behavioral ecology as well as promising directions in the overall use of SNA.

  14. 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...

  15. Social network analysis in healthcare settings: a systematic scoping review.

    Science.gov (United States)

    Chambers, Duncan; Wilson, Paul; Thompson, Carl; Harden, Melissa

    2012-01-01

    Social network analysis (SNA) has been widely used across a range of disciplines but is most commonly applied to help improve the effectiveness and efficiency of decision making processes in commercial organisations. We are utilising SNA to inform the development and implementation of tailored behaviour-change interventions to improve the uptake of evidence into practice in the English National Health Service. To inform this work, we conducted a systematic scoping review to identify and evaluate the use of SNA as part of an intervention to support the implementation of change in healthcare settings. We searched ten bibliographic databases to October 2011. We also searched reference lists, hand searched selected journals and websites, and contacted experts in the field. To be eligible for the review, studies had to describe and report the results of an SNA performed with healthcare professionals (e.g. doctors, nurses, pharmacists, radiographers etc.) and others involved in their professional social networks. We included 52 completed studies, reported in 62 publications. Almost all of the studies were limited to cross sectional descriptions of networks; only one involved using the results of the SNA as part of an intervention to change practice. We found very little evidence for the potential of SNA being realised in healthcare settings. However, it seems unlikely that networks are less important in healthcare than other settings. Future research should seek to go beyond the merely descriptive to implement and evaluate SNA-based interventions.

  16. Social network analysis aided product development project management: IC Substrates case study

    Directory of Open Access Journals (Sweden)

    Yee Min Chen

    2011-04-01

    Full Text Available This paper proposes the social network analysis (SNA, to study interaction among various activities in a product development process (PDP. The implementation of SNA helps to measure the properties of information flow and identifies PDP activities and limitations. The findings of an exploratory research project which explores the potential of SNA, as an improve tool for visually mapping and analyzing the stakeholders relationships found across the IC substrates design/manufacturing’s PDP of the Unimicron Technology Corp. From the findings, the authors prescribe the necessary SNA recommendations to improve the social conditions within the PDP.

  17. Patterns of Discursive Interactions in Primary Classrooms: An Application of Social Network Analysis

    Science.gov (United States)

    Mameli, Consuelo; Mazzoni, Elvis; Molinari, Luisa

    2015-01-01

    This study aimed to investigate whether social network analysis (SNA) is a useful method for identifying different discursive patterns in everyday classroom activities. The material analysed came from 20 teacher-led lessons that were video-recorded in small-size classes in Italian public primary schools. SNA was used to measure classroom relations…

  18. 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.

  19. Bringing the Best of Two Worlds Together for Social Capital Research in Education: Social Network Analysis and Symbolic Interactionism

    Science.gov (United States)

    Lee, Moosung

    2014-01-01

    This article proposes an analytical consideration for social capital research in education by exploring a pragmatic combination of social network analysis (SNA) and symbolic interactionism (SI) as a research method. The article first delineates the theoretical linkages of social capital theory with SNA and SI. The article then discusses how SNA…

  20. Applications of social network analysis for building community disaster resilience: workshop summary

    National Research Council Canada - National Science Library

    Magsino, Sammantha L

    2009-01-01

    "In response to a request by the Department of Homeland Security, the National Research Council formed an ad hoc committee to organize a two-day workshop to discuss the use of social network analysis (SNA...

  1. Social network analysis in the study of nonhuman primates: A historical perspective

    Science.gov (United States)

    Brent, Lauren J.N.; Lehmann, Julia; Ramos-Fernández, Gabriel

    2011-01-01

    Advances over the last fifteen years have made social network analysis (SNA) a powerful tool for the study of nonhuman primate social behavior. Although many SNA-based techniques have been only very recently adopted in primatological research, others have been commonly used by primatologists for decades. The roots of SNA also stem from some of the same conceptual frameworks as the majority of nonhuman primate behavioral research. The rapid development of SNA in recent years has led to questions within the primatological community of where and how SNA fits within this field. We aim to address these questions by providing an overview of the historical relationship between SNA and the study of nonhuman primates. We begin with a brief history of the development of SNA, followed by a detailed description of the network-based visualization techniques, analytical methods and conceptual frameworks which have been employed by primatologists since as early as the 1960s. We also introduce some of the latest advances to SNA, thereby demonstrating that this approach contains novel tools for study of nonhuman primate social behavior which may be used to shed light on questions that cannot be addressed fully using more conventional methods. PMID:21433047

  2. 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.

  3. The stability of the extended model of hypothalamic-pituitary-adrenal axis examined by stoichiometric network analysis

    Science.gov (United States)

    Marković, V. M.; Čupić, Ž.; Ivanović, A.; Kolar-Anić, Lj.

    2011-12-01

    Stoichiometric network analysis (SNA) represents a powerful mathematical tool for stability analysis of complex stoichiometric networks. Recently, the important improvement of the method has been made, according to which instability relations can be entirely expressed via reaction rates, instead of thus far used, in general case undefined, current rates. Such an improved SNA methodology was applied to the determination of exact instability conditions of the extended model of the hypothalamic-pituitary-adrenal (HPA) axis, a neuroendocrinological system, whose hormone concentrations exert complex oscillatory evolution. For emergence of oscillations, the Hopf bifurcation condition was utilized. Instability relations predicted by SNA showed good correlation with numerical simulation data of the HPA axis model.

  4. Using social network analysis to understand actor participation and ...

    African Journals Online (AJOL)

    Sustainable management of wetland is complex due competing interests and require the participation of different actors. However, there is little attention on systematic analysis of actor participation in wetland management. This paper uses Social Network Analysis (SNA) approach to analyse how actors with different ...

  5. Social Network Analyses (SNA) as a method to study the structure of contacts within teams of a school for secondary education

    NARCIS (Netherlands)

    Meijs, Celeste; De Laat, Maarten

    2017-01-01

    This paper reports findings from a study using social network analysis techniques to understand social learning relationships within and between teacher teams in a large secondary school in the Netherlands (n=117 teachers). The findings suggest a relationship between the social structure of a team

  6. 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

  7. Preparation and Properties of Cellulose Laurate (CL/Starch Nanocrystals Acetate (SNA Bio-nanocomposites

    Directory of Open Access Journals (Sweden)

    Feng-Yuan Huang

    2015-07-01

    Full Text Available In the present paper, a series of totally novel bio-nanocomposite films from cellulose laurate (CL and starch nanocrystals acetate (SNA were fabricated, and the properties of nanocomposite films were investigated in detail. SNA was obtained by modifying starch nanocrystals (SNs produced by sulfuric acid hydrolysis of corn starch with acetic anhydride. The favorable dispersity of SNA in chloroform made it ready to convert into nanocomposite films with CL via casting/evaporation method. The transmittance, thermal behavior, mechanical properties, barrier properties and hydrophobicity of CL/SNA nanocomposite films were investigated with UV-vis spectrophotometer, simultaneous thermal analyzer (STA, universal tensile tester/dynamic thermomechanical analysis (DMA, water vapor permeation meter/oxygen permeability tester, and contact angle tester, respectively. The transmittance of nanocomposite films decreased with the increase of SNA content. Thermogravimetric analysis (TGA results showed that the introduction of SNA into CL matrix did not severely decrease the thermal behavior of CL/SNA nanocomposites. Moreover, non-linear and linear mechanical analysis reflected the enhancement of SNA. At lower contents of SNA (<5.0 wt%, the values of Young’s modulus, tensile strength and the elongation at break of nanocomposite films were comparable with those of neat CL. However, with the increase of SNA, the Young’s modulus and tensile strength were improved significantly and were accompanied by the decreased elongation at break. The water vapor permeability (WVP and oxygen permeability (PO2 of CL/SNA nanocomposite films were significantly improved by the addition of SNA.

  8. A Social Network Analysis of Teaching and Research Collaboration in a Teachers' Virtual Learning Community

    Science.gov (United States)

    Lin, Xiaofan; Hu, Xiaoyong; Hu, Qintai; Liu, Zhichun

    2016-01-01

    Analysing the structure of a social network can help us understand the key factors influencing interaction and collaboration in a virtual learning community (VLC). Here, we describe the mechanisms used in social network analysis (SNA) to analyse the social network structure of a VLC for teachers and discuss the relationship between face-to-face…

  9. Making Connections: Using Social Network Analysis for Program Evaluation. Issue Brief. Number 1

    Science.gov (United States)

    Honeycutt, Todd

    2009-01-01

    Social network analysis (SNA) is a methodological approach to measuring and mapping relationships. It can be used to study whole networks, all of the ties within a defined group, or connections that individuals have in their personal communities. The resulting graph-based structures illustrate the composition and effectiveness of networks on a…

  10. Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review

    Science.gov (United States)

    Cela, Karina L.; Sicilia, Miguel Ángel; Sánchez, Salvador

    2015-01-01

    E-learning occupies an increasingly prominent place in education. It provides the learner with a rich virtual network where he or she can exchange ideas and information and create synergies through interactions with other members of the network, whether fellow learners or teachers. Social network analysis (SNA) has proven extremely powerful at…

  11. Applying DNA computation to intractable problems in social network analysis.

    Science.gov (United States)

    Chen, Rick C S; Yang, Stephen J H

    2010-09-01

    From ancient times to the present day, social networks have played an important role in the formation of various organizations for a range of social behaviors. As such, social networks inherently describe the complicated relationships between elements around the world. Based on mathematical graph theory, social network analysis (SNA) has been developed in and applied to various fields such as Web 2.0 for Web applications and product developments in industries, etc. However, some definitions of SNA, such as finding a clique, N-clique, N-clan, N-club and K-plex, are NP-complete problems, which are not easily solved via traditional computer architecture. These challenges have restricted the uses of SNA. This paper provides DNA-computing-based approaches with inherently high information density and massive parallelism. Using these approaches, we aim to solve the three primary problems of social networks: N-clique, N-clan, and N-club. Their accuracy and feasible time complexities discussed in the paper will demonstrate that DNA computing can be used to facilitate the development of SNA. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

  12. Applying Social Network Analysis to Identify the Social Support Needs of Adolescent and Young Adult Cancer Patients and Survivors.

    Science.gov (United States)

    Koltai, Kolina; Walsh, Casey; Jones, Barbara; Berkelaar, Brenda L

    2017-11-06

    This article examines how theoretical and clinical applications of social network analysis (SNA) can inform opportunities for innovation and advancement of social support programming for adolescent and young adult (AYA) cancer patients and survivors. SNA can help address potential barriers and challenges to initiating and sustaining AYA peer support by helping to identify the diverse psychosocial needs among individuals in the AYA age range; find strategic ways to support and connect AYAs at different phases of the cancer trajectory with resources and services; and increase awareness of psychosocial resources and referrals from healthcare providers. Network perspectives on homophily, proximity, and evolution provide a foundational basis to explore the utility of SNA in AYA clinical care and research initiatives. The uniqueness of the AYA oncology community can also provide insight into extending and developing current SNA theories. Using SNA in AYA psychosocial cancer research has the potential to create new ideas and pathways for supporting AYAs across the continuum of care, while also extending theories of SNA. SNA may also prove to be a useful tool for examining social support resources for AYAs with various chronic health conditions and other like groups.

  13. [Social network analysis: a method to improve safety in healthcare organizations].

    Science.gov (United States)

    Marqués Sánchez, Pilar; González Pérez, Marta Eva; Agra Varela, Yolanda; Vega Núñez, Jorge; Pinto Carral, Arrate; Quiroga Sánchez, Enedina

    2013-01-01

    Patient safety depends on the culture of the healthcare organization involving relationships between professionals. This article proposes that the study of these relations should be conducted from a network perspective and using a methodology called Social Network Analysis (SNA). This methodology includes a set of mathematical constructs grounded in Graph Theory. With the SNA we can know aspects of the individual's position in the network (centrality) or cohesion among team members. Thus, the SNA allows to know aspects related to security such as the kind of links that can increase commitment among professionals, how to build those links, which nodes have more prestige in the team in generating confidence or collaborative network, which professionals serve as intermediaries between the subgroups of a team to transmit information or smooth conflicts, etc. Useful aspects in stablishing a safety culture. The SNA would analyze the relations among professionals, their level of communication to communicate errors and spontaneously seek help and coordination between departments to participate in projects that enhance safety. Thus, they related through a network, using the same language, a fact that helps to build a culture. In summary, we propose an approach to safety culture from a SNA perspective that would complement other commonly used methods.

  14. 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.

  15. Social Learning Network Analysis Model to Identify Learning Patterns Using Ontology Clustering Techniques and Meaningful Learning

    Science.gov (United States)

    Firdausiah Mansur, Andi Besse; Yusof, Norazah

    2013-01-01

    Clustering on Social Learning Network still not explored widely, especially when the network focuses on e-learning system. Any conventional methods are not really suitable for the e-learning data. SNA requires content analysis, which involves human intervention and need to be carried out manually. Some of the previous clustering techniques need…

  16. Time for a real shift to relations: appraisal of Social Network Analysis applications in the UK construction industry

    Directory of Open Access Journals (Sweden)

    Ximing Ruan

    2013-03-01

    Full Text Available The Social Network Analysis (SNA has been adopted in the UK construction management research and generated meaningful insights in analysing project management organisations from network perspectives. As an effective tool, social network analysis has been used to analyse information and knowledge flow between construction project teams which is considered as foundation for collaborative working and subsequently improving overall performance. Social network analysis is based on an assumption of the importance of relationships among interacting units. The social network perspective encompasses theories, models and applications that are expressed in terms of relational concepts or processes. Many believe, moreover, that the success or failure of organisations often depends on the patterning of their internal structure. This paper reviewed existing literatures on SNA applications in construction industry from three leading construction management journals.  From the review, the research proposed some advance in the application of SNA in the construction industry.

  17. Construcción y validación del cuestionario de adicción a redes sociales (ARS(Construction and Validation of the Questionnairy of Social Networking Addiction (SNA

    Directory of Open Access Journals (Sweden)

    Miguel Escurra Mayaute

    2014-06-01

    Full Text Available RESUMEN: El propósito del presente estudio fue diseñar, construir y validar el cuestionario de Adicción a Redes Sociales (ARS mediante la aplicación del modelo de la Teoría de Respuesta al Ítem (TRI para ítems politómicos de respuesta graduada. Inicialmente los ítems se diseñaron de acuerdo a los indicadores del DSM-IV para adicción a sustancias, adaptándolos al constructo estudiado, los cuales fueron evaluados en su validez de contenido sobre la base del criterio de jueces. La versión inicial de 31 ítems se aplicó a 380 estudiantes de diferentes universidades de la ciudad de Lima. Se analizó la estructura latente de los ítems aplicando el análisis factorial exploratorio a la matriz de correlaciones policóricas entre ítems. Los resultados indicaron que existen tres dimensiones que se analizaron de forma independiente. La estimación de los parámetros de los modelos se realizó con el método de máxima verosimilitud marginal. A partir de los resultados se excluyeron de la escala ocho ítems por presentar un comportamiento inadecuado. Los parámetros de localización se ubican en niveles medios y altos de la escala. Los parámetros de discriminación adoptaron valores moderados y altos. Las funciones de información de los ítems evidenciaron que las dimensiones son más precisas para discriminar a los individuos con niveles medios y altos del rasgo evaluado. Los resultados revelaron que la escala y sus componentes presentaron adecuadas propiedades psicométricas de validez y confiabilidad ABSTRACT: The purpose of this study was to design, construct, and validate The Social Network Addiction Questionnaire (SNA by applying the Item Response Theory (ITR for polyatomic graded response items. At first, items were designed according to the DSM-IV criteria for substance addiction and adapted to the construct under study that was evaluated in its content validity by the judges’ criterion. The initial version of 31 items was

  18. Social network analysis. Review of general concepts and use in preventive veterinary medicine.

    Science.gov (United States)

    Martínez-López, B; Perez, A M; Sánchez-Vizcaíno, J M

    2009-05-01

    Social network analysis (SNA) and graph theory have been used widely in sociology, psychology, anthropology, biology and medicine. Social network analysis and graph theory provide a conceptual framework to study contact patterns and to identify units of analysis that are frequently or intensely connected within the network. Social network analysis has been used in human epidemiology as a tool to explore the potential transmission of infectious agents such as HIV, tuberculosis, hepatitis B and syphilis. In preventive veterinary medicine, SNA is an approach that offers benefits for exploring the nature and extent of the contacts between animals or farms, which ultimately leads to a better understanding of the potential risk for disease spread in a susceptible population. Social network analysis, however, has been applied only recently in preventive veterinary medicine, therefore the characteristics of the technique and the potential benefits of its use remain unknown for an important section of the international veterinary medicine community. The objectives of this paper were to review the concepts and theoretical aspects underlying the use of SNA and graph theory, with particular emphasis on their application to the study of infectious diseases of animals. The paper includes a review of recent applications of SNA in preventive veterinary medicine and a discussion of the potential uses and limitations of this methodology for the study of animal diseases.

  19. 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.

  20. 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.

  1. Forensic SNP genotyping with SNaPshot

    DEFF Research Database (Denmark)

    Fondevila, M; Børsting, C; Phillips, C

    2017-01-01

    This review explores the key factors that influence the optimization, routine use, and profile interpretation of the SNaPshot single-base extension (SBE) system applied to forensic single-nucleotide polymorphism (SNP) genotyping. Despite being a mainly complimentary DNA genotyping technique...... to routine STR profiling, use of SNaPshot is an important part of the development of SNP sets for a wide range of forensic applications with these markers, from genotyping highly degraded DNA with very short amplicons to the introduction of SNPs to ascertain the ancestry and physical characteristics...... of an unidentified contact trace donor. However, this technology, as resourceful as it is, displays several features that depart from the usual STR genotyping far enough to demand a certain degree of expertise from the forensic analyst before tackling the complex casework on which SNaPshot application provides...

  2. The use of nodes attributes in social network analysis with an application to an international trade network

    Science.gov (United States)

    de Andrade, Ricardo Lopes; Rêgo, Leandro Chaves

    2018-02-01

    The social network analysis (SNA) studies the interactions among actors in a network formed through some relationship (friendship, cooperation, trade, among others). The SNA is constantly approached from a binary point of view, i.e., it is only observed if a link between two actors is present or not regardless of the strength of this link. It is known that different information can be obtained in weighted and unweighted networks and that the information extracted from weighted networks is more accurate and detailed. Another rarely discussed approach in the SNA is related to the individual attributes of the actors (nodes), because such analysis is usually focused on the topological structure of networks. Features of the nodes are not incorporated in the SNA what implies that there is some loss or misperception of information in those analyze. This paper aims at exploring more precisely the complexities of a social network, initially developing a method that inserts the individual attributes in the topological structure of the network and then analyzing the network in four different ways: unweighted, edge-weighted and two methods for using both edge-weights and nodes' attributes. The international trade network was chosen in the application of this approach, where the nodes represent the countries, the links represent the cash flow in the trade transactions and countries' GDP were chosen as nodes' attributes. As a result, it is possible to observe which countries are most connected in the world economy and with higher cash flows, to point out the countries that are central to the intermediation of the wealth flow and those that are most benefited from being included in this network. We also made a principal component analysis to study which metrics are more influential in describing the data variability, which turn out to be mostly the weighted metrics which include the nodes' attributes.

  3. 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), ...

  4. Changes in Social Capital and Networks: A Study of Community-Based Environmental Management through a School-Centered Research Program

    Science.gov (United States)

    Thornton, Teresa; Leahy, Jessica

    2012-01-01

    Social network analysis (SNA) is a social science research tool that has not been applied to educational programs. This analysis is critical to documenting the changes in social capital and networks that result from community based K-12 educational collaborations. We review SNA and show an application of this technique in a school-centered,…

  5. 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…

  6. Cliques and Cohesion in a Clinical Psychology Graduate Cohort: A Longitudinal Social Network Analysis

    Science.gov (United States)

    Kunze, Kimberley Annette

    2013-01-01

    To date, no published research has utilized social network analysis (SNA) to analyze graduate cohorts in clinical psychology. The purpose of this research is to determine how issues of likability among students correlate with other measures, such as disclosure, health, spiritual maturity, help in projects, familiarity, and ease of providing…

  7. The network researchers' network: A social network analysis of the IMP Group 1985-2006

    DEFF Research Database (Denmark)

    Henneberg, Stephan C. M.; Ziang, Zhizhong; Naudé, Peter

    ). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...... components in some detail. The egonets of three of the original 'founding fathers' are examined in detail, and we draw comparisons as to how their publishing strategies vary. Finally, the paper draws some more general conclusions as to the insights that SNA can bring to those working within business...

  8. An Analysis of Density and Degree-Centrality According to the Social Networking Structure Formed in an Online Learning Environment

    Science.gov (United States)

    Ergün, Esin; Usluel, Yasemin Koçak

    2016-01-01

    In this study, we assessed the communication structure in an educational online learning environment using social network analysis (SNA). The communication structure was examined with respect to time, and instructor's participation. The course was implemented using ELGG, a network learning environment, blended with face-to-face sessions over a…

  9. Higher Education Change and Social Networks: A Review of Research

    Science.gov (United States)

    Kezar, Adrianna

    2014-01-01

    This article reviews literature on the potential for understanding higher education change processes through social network analysis (SNA). In this article, the main tenets of SNA are reviewed and, in conjunction with organizational theory, are applied to higher education change to develop a set of hypotheses that can be tested in future research.

  10. 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.

  11. Analysis of the Air Transport Network Characteristics of Major Airports

    Directory of Open Access Journals (Sweden)

    Min Geun Song

    2017-09-01

    Full Text Available The world's major airports are directly connected to hundreds of airports without intermediate routes. This connectivity can be described as the network in which the airport becomes a node and the route becomes a connection line. In this regard, this study analyzes the air transport network of 1,060 airports using the social network analysis (SNA methodology. We consolidated the data from three airline alliances and established a network of 1,060 airports and 5,580 routes in 173 countries. Many previous studies on air transport network examined several specific airports or regions and mainly utilized the internal indicators of airports. Conversely, this study conducted a comprehensive analysis covering 173 countries by using air route, which is an external indicator of airports. This study presented the general characteristics of major countries and regions from the perspective of SNA and compared the individual networks of the United States and China, which have the greatest influence on international air logistics within the scope of the entire network analysis. This study can aid in the understanding of air transport networks and logistics connectivity in inter-city and inter-country transport.

  12. Internet-Based Approaches to Building Stakeholder Networks for Conservation and Natural Resource Management.

    Science.gov (United States)

    Social network analysis (SNA) is based on a conceptual network representation of social interactions and is an invaluable tool for conservation professionals to increase collaboration, improve information flow, and increase efficiency. We present two approaches to constructing in...

  13. 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.

  14. Custos dos Serviços de Não-auditoria (SNA das Maiores Empresas Brasileiras = Non-audit service (SNA fees in the biggest brazilian companies

    Directory of Open Access Journals (Sweden)

    Carolina Aguiar da Rosa

    2014-04-01

    identify elements that characterize groups of firms with different SNA fees analysis of variance was used, evaluating variables from the total assets, equity, net income and external audit services – SAE fees. The results show that most SNAare used by companies to audit tax (31%. Moreover, the audit SOX holds a significant cost, representing 16% of total SNA, but there is a low incidence, which can be justified by a concern with recent corporate governance. One concern with the disclosure of SNA can arise because 50% of the costs evidenced by the companies comprising the group "other services" and the types of services that are part of this group are not explained. In addition, information inconsistencies were found between RF and RA in 35% of the companies. Concerning the cost variable of SNA, this study provides evidence that the highest SNA fees were evidenced by the sample companies which evidenced the highest SAE fees.

  15. Connecting the Disconnected: Social Work and Social Network Analysis. A Methodological Approach to Identifying Network Peer Leaders

    Directory of Open Access Journals (Sweden)

    del Fresno García, Miguel

    2015-02-01

    Full Text Available Social network theory and analysis (SNA offers a useful conceptual framework and a robust set of methods for understanding, analysing, and representing the pattern of social interactions that surround individuals forming an overall network of ties. SNA provides both insights and applications regarding relational structures that may be consequential for individual and collective agency. Despite the fact that both SNA and social work focus on relationships and behaviour, and that each discipline could substantively inform the other, there remains a significant lack of intersection between the two disciplines. In response to this gap, SNA applied to social work can provide additional ways to both diagnose and intervene behaviourally through the following approaches: a by identifying key players in promoting the dissemination of behavioral changes in networks; b by segmenting and identifying groups, cliques and communities; c by supporting behavioural change through social ties surrounding the individual; and d by aligning and applying specific interventions that draw on mutually interactive processes in terms of individual influences on networks, as well as network influences on individuals. SNA provides social work with an additional lens and set of tools based on the constellation of interactions surrounding individuals, families, groups or communities that supports understanding, diagnosis, and intervention.La Teoría y Análisis de Redes Sociales (SNA ofrece un conjunto de métodos de análisis de las interacciones sociales de los seres humanos, que permiten de forma específica investigar las estructuras relacionales y la representación de éstas como redes. SNA proporciona tanto acceso a nuevo conocimiento como la representación de las estructuras relacionales y como éstas pueden ser consecuencia de la acción individual y colectiva. A pesar de que tanto el SNA como el Trabajo Social tienen su foco en las relaciones y el comportamiento, de

  16. Application of Social Network Analysis for Livelihood System Study

    Directory of Open Access Journals (Sweden)

    Sanchayeeta Misra

    2014-12-01

    Full Text Available Social Network Analysis (SNA has received growing attention among diverse academic fields for studying ‘social relations’ among individuals and institutions. Unfortunately, its application has remained limited in the study of livelihood systems of rural poor. Complexity in rural livelihoods has increased sharply in the face of increased pressure on natural resources and rapid shift in farm-based to non-farm based employments. This poses great challenge to successful livelihood intervention in rural areas. On one hand, rural development/extension needs to cater to diverse information and service need of the rural people; on other hand, rural institutions need to deliver livelihood-sustaining services more efficiently, which often need institutional restructuring at multiple levels. To achieve these challenges, a strong innovative analytical tool is required for understanding the complexity of rural livelihoods and the associated role of rural institutions. SNA provides excellent scope to analyse such complex systems and interactions among their components. This article proposes an outline of using SNA in livelihood system analysis. The analysis can provide answer to many questions of practical importance – Who are the influential actors in a livelihood system? Which are the key institutions contributing towards sustainable livelihoods? How do these actors interact among themselves? This will help rural development administrators to deliver livelihood-supporting services more efficiently through informed targeting and capacity building.

  17. Participation in protected areas: A social network case study in Catalonia, Spain

    NARCIS (Netherlands)

    Calvet-Mir, L.; Maestre Andrés, S.; Molina, J.L.; van den Bergh, J.C.J.M.

    2015-01-01

    Local participation of stakeholders in governance of protected areas is considered to be important to natural resource management and biodiversity conservation. Social network analysis (SNA) is a useful tool for analysis because it allows the understanding of stakeholders’ relationships,

  18. 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.

  19. A Qualitative Study of Secondary School Teachers’ Perception of Social Network Analysis Metrics in the Context of Alcohol Consumption among Adolescents

    Directory of Open Access Journals (Sweden)

    Enedina Quiroga

    2017-12-01

    Full Text Available Adolescence is a transitional period during which a number of changes occur. Social relationships established during this period influence adolescent behaviour and affect academic performance or alcohol consumption habits, among other issues. Teachers are very important actors in observing and guiding the evolution of their students, and should therefore have the appropriate knowledge and tools to gain insight into the complex social relationships that exist in their classes. The use of social network analysis (SNA techniques may be helpful in order to study and monitor the evolution of these social networks. This study tries to understand how teachers perceive SNA metrics from an intuitive point of view. Using this information, useful tools could be created that allow teachers to use SNA techniques to improve their understanding of student relationships. A number of interviews with different teachers were held in secondary schools in Spain, allowing SNA concepts to be related to the everyday terms used by the teachers to characterize their students. Results from the study have an impact on questionnaire design for gathering data from students in order to perform an SNA analysis and on the design of software applications that can help teachers to understand the results of this analysis.

  20. The Private Lives of Minerals: Social Network Analysis Applied to Mineralogy and Petrology

    Science.gov (United States)

    Hazen, R. M.; Morrison, S. M.; Fox, P. A.; Golden, J. J.; Downs, R. T.; Eleish, A.; Prabhu, A.; Li, C.; Liu, C.

    2016-12-01

    Comprehensive databases of mineral species (rruff.info/ima) and their geographic localities and co-existing mineral assemblages (mindat.org) reveal patterns of mineral association and distribution that mimic social networks, as commonly applied to such varied topics as social media interactions, the spread of disease, terrorism networks, and research collaborations. Applying social network analysis (SNA) to common assemblages of rock-forming igneous and regional metamorphic mineral species, we find patterns of cohesion, segregation, density, and cliques that are similar to those of human social networks. These patterns highlight classic trends in lithologic evolution and are illustrated with sociograms, in which mineral species are the "nodes" and co-existing species form "links." Filters based on chemistry, age, structural group, and other parameters highlight visually both familiar and new aspects of mineralogy and petrology. We quantify sociograms with SNA metrics, including connectivity (based on the frequency of co-occurrence of mineral pairs), homophily (the extent to which co-existing mineral species share compositional and other characteristics), network closure (based on the degree of network interconnectivity), and segmentation (as revealed by isolated "cliques" of mineral species). Exploitation of large and growing mineral data resources with SNA offers promising avenues for discovering previously hidden trends in mineral diversity-distribution systematics, as well as providing new pedagogical approaches to teaching mineralogy and petrology.

  1. Health care provider social network analysis: A systematic review.

    Science.gov (United States)

    Bae, Sung-Heui; Nikolaev, Alexander; Seo, Jin Young; Castner, Jessica

    2015-01-01

    Although considerable progress has been made in understanding networks, their structure, and their development, little has been known about their effectiveness in the health care setting and their contributions to quality of care and patient safety.The purpose of this study was to examine studies using social network analysis (SNA) in the health care workforce and assess factors contributing to social network and their relationships with care processes and patient outcomes. We identified all published peer-reviewed SNA articles in CINAHL, PubMed, PsycINFO, JSTOR, Medline (OVID), and Web of Science databases up to April 2013. Twenty-nine published articles met the inclusion criteria. Current evidence of the health care workforce's social networks reveals the nature of social ties are related to personal characteristics, practice setting, and types of patients. A few studies also revealed the social network effects adoption and the use of a health information system, patient outcomes, and coordination. Current studies on the social ties of health care workforce professionals include several assessments of inefficiencies. The level of technical sophistication in these studies tended to be low. Future study using enhanced sophistication in study design, analysis, and patient outcome testing are warranted to fully leverage the potential of SNA in health care studies. Copyright © 2015 Elsevier Inc. All rights reserved.

  2. Naturally-Emerging Technology-Based Leadership Roles in Three Independent Schools: A Social Network-Based Case Study Using Fuzzy Set Qualitative Comparative Analysis

    Science.gov (United States)

    Velastegui, Pamela J.

    2013-01-01

    This hypothesis-generating case study investigates the naturally emerging roles of technology brokers and technology leaders in three independent schools in New York involving 92 school educators. A multiple and mixed method design utilizing Social Network Analysis (SNA) and fuzzy set Qualitative Comparative Analysis (FSQCA) involved gathering…

  3. Dim Networks: The Utility of Social Network Analysis for Illuminating Partner Security Force Networks

    Science.gov (United States)

    2015-12-01

    Eigenvector centrality ......................................................88 xii THIS PAGE INTENTIONALLY LEFT BLANK xiii LIST OF ACRONYMS AND...should be engaged. This determination will be based on simple SNA centrality measures, total degree,9 betweenness,10 closeness,11 and Eigenvector ...11 Closeness centrality measures how close each node is to all the other nodes in a network by their path distance. 12 Eigenvector centrality

  4. Bridging the Gap: Enhancing SNA Within the Marine Corps Intelligence Community

    Science.gov (United States)

    2015-06-01

    any combination of the two dimensions (Everton, 2012). 16 4. Social Theory The vocabulary offered by mathematics is augmented by social theory...questions, is even more complex, but is part of what predictive analysis is—and it requires more than basic skill. Mastery of SNA requires a

  5. Analyzing Social Media Networks with NodeXL Insights from a Connected World

    CERN Document Server

    Hansen, Derek; Smith, Marc A

    2010-01-01

    Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

  6. TOWARDS THE INVESTIGATION OF USING SOCIAL NETWORK ANALYSIS FOR COUNTER TERRORISM IN WEST AFRICA: CASE STUDY OF BOKO HARAM IN NIGERIA

    Directory of Open Access Journals (Sweden)

    F. OLAJIDE

    2016-11-01

    Full Text Available In this paper, an investigative review of social network analysis (SNA to counter terrorism is presented. Various measures used for predicting key players of terrorist networks are discussed. The methods used for the survey is based on the existing research work that was carried out on counter terrorism of insurgency, for example, 9/11 (2001 attack in the United States. The research papers have shown that the SNA is one of the most efficient and effective methods for understanding terrorist networks. For example, the National security agency has been mapping phone calls ever since the 9/11 event and through this research work, United States have been able to uncover so many hidden terrorist and criminal groups. This paper provides an avenue for a suggestive idea that the Nigerian government can make use of SNA technique by phone mapping. This is based on the fact that Nigeria can combat terrorism in the nation. The Nigerian government can emulate phone mapping technique as Boko Haram terrorists are within the country and they actually make use of phone calls. The government only needs to collaborate with the telecommunication and network providers companies in Nigeria to track down these terrorists. Using SNA to understand/discover terrorist networks in the region is novel.

  7. Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2015-01-01

    Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

  8. Evolution of treatment regimens in multiple myeloma: a social network analysis.

    Directory of Open Access Journals (Sweden)

    Helen Mahony

    Full Text Available Randomized controlled trials (RCTs are considered the gold standard for assessing the efficacy of new treatments compared to standard treatments. However, the reasoning behind treatment selection in RCTs is often unclear. Here, we focus on a cohort of RCTs in multiple myeloma (MM to understand the patterns of competing treatment selections.We used social network analysis (SNA to study relationships between treatment regimens in MM RCTs and to examine the topology of RCT treatment networks. All trials considering induction or autologous stem cell transplant among patients with MM were eligible for our analysis. Medline and abstracts from the annual proceedings of the American Society of Hematology and American Society for Clinical Oncology, as well as all references from relevant publications were searched. We extracted data on treatment regimens, year of publication, funding type, and number of patients enrolled. The SNA metrics used are related to node and network level centrality and to node positioning characterization.135 RCTs enrolling a total of 36,869 patients were included. The density of the RCT network was low indicating little cohesion among treatments. Network Betweenness was also low signifying that the network does not facilitate exchange of information. The maximum geodesic distance was equal to 4, indicating that all connected treatments could reach each other in four "steps" within the same pathway of development. The distance between many important treatment regimens was greater than 1, indicating that no RCTs have compared these regimens.Our findings show that research programs in myeloma, which is a relatively small field, are surprisingly decentralized with a lack of connectivity among various research pathways. As a result there is much crucial research left unexplored. Using SNA to visually and analytically examine treatment networks prior to designing a clinical trial can lead to better designed studies.

  9. US adolescents’ friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data

    Directory of Open Access Journals (Sweden)

    Kwon Chan Jeon

    2015-06-01

    Full Text Available Background. Documented trends in health-related risk behaviors among US adolescents have remained high over time. Studies indicate relationships among mutual friends are a major influence on adolescents’ risky behaviors. Social Network Analysis (SNA can help understand friendship ties affecting individual adolescents’ engagement in these behaviors. Moreover, a systematic literature review can synthesize findings from a range of studies using SNA, as well as assess these studies’ methodological quality. Review findings also can help health educators and promoters develop more effective programs.Objective. This review systematically examined studies of the influence of friendship networks on adolescents’ risk behaviors, which utilized SNA and the Add Health data (a nationally representative sample.Methods. We employed the Matrix Method to synthesize and evaluate 15 published studies that met our inclusion and exclusion criteria, retrieved from the Add Health website and 3 major databases (Medline, Eric, and PsycINFO. Moreover, we assigned each study a methodological quality score (MQS.Results. In all studies, friendship networks among adolescents promoted their risky behaviors, including drinking alcohol, smoking, sexual intercourse, and marijuana use. The average MQS was 4.6, an indicator of methodological rigor (scale: 1–9.Conclusion. Better understanding of risky behaviors influenced by friends can be useful for health educators and promoters, as programs targeting friendships might be more effective. Additionally, the overall MQ of these reviewed studies was good, as average scores fell above the scale’s mid-point.

  10. US adolescents' friendship networks and health risk behaviors: a systematic review of studies using social network analysis and Add Health data.

    Science.gov (United States)

    Jeon, Kwon Chan; Goodson, Patricia

    2015-01-01

    Background. Documented trends in health-related risk behaviors among US adolescents have remained high over time. Studies indicate relationships among mutual friends are a major influence on adolescents' risky behaviors. Social Network Analysis (SNA) can help understand friendship ties affecting individual adolescents' engagement in these behaviors. Moreover, a systematic literature review can synthesize findings from a range of studies using SNA, as well as assess these studies' methodological quality. Review findings also can help health educators and promoters develop more effective programs. Objective. This review systematically examined studies of the influence of friendship networks on adolescents' risk behaviors, which utilized SNA and the Add Health data (a nationally representative sample). Methods. We employed the Matrix Method to synthesize and evaluate 15 published studies that met our inclusion and exclusion criteria, retrieved from the Add Health website and 3 major databases (Medline, Eric, and PsycINFO). Moreover, we assigned each study a methodological quality score (MQS). Results. In all studies, friendship networks among adolescents promoted their risky behaviors, including drinking alcohol, smoking, sexual intercourse, and marijuana use. The average MQS was 4.6, an indicator of methodological rigor (scale: 1-9). Conclusion. Better understanding of risky behaviors influenced by friends can be useful for health educators and promoters, as programs targeting friendships might be more effective. Additionally, the overall MQ of these reviewed studies was good, as average scores fell above the scale's mid-point.

  11. Stoichiometric network analysis and associated dimensionless kinetic equations. Application to a model of the Bray-Liebhafsky reaction.

    Science.gov (United States)

    Schmitz, Guy; Kolar-Anić, Ljiljana Z; Anić, Slobodan R; Cupić, Zeljko D

    2008-12-25

    The stoichiometric network analysis (SNA) introduced by B. L. Clarke is applied to a simplified model of the complex oscillating Bray-Liebhafsky reaction under batch conditions, which was not examined by this method earlier. This powerful method for the analysis of steady-states stability is also used to transform the classical differential equations into dimensionless equations. This transformation is easy and leads to a form of the equations combining the advantages of classical dimensionless equations with the advantages of the SNA. The used dimensionless parameters have orders of magnitude given by the experimental information about concentrations and currents. This simplifies greatly the study of the slow manifold and shows which parameters are essential for controlling its shape and consequently have an important influence on the trajectories. The effectiveness of these equations is illustrated on two examples: the study of the bifurcations points and a simple sensitivity analysis, different from the classical one, more based on the chemistry of the studied system.

  12. Bibliometrics/Citation networks

    OpenAIRE

    Leydesdorff, Loet

    2015-01-01

    In addition to shaping social networks, for example, in terms of co-authorship relations, scientific communications induce and reproduce cognitive structures. Scientific literature is intellectually organized in terms of disciplines and specialties; these structures are reproduced and networked reflexively by making references to the authors, concepts and texts embedded in these literatures. The concept of a cognitive structure was introduced in social network analysis (SNA) in 1987 by David ...

  13. You Never Walk Alone: Recommending Academic Events Based on Social Network Analysis

    Science.gov (United States)

    Klamma, Ralf; Cuong, Pham Manh; Cao, Yiwei

    Combining Social Network Analysis and recommender systems is a challenging research field. In scientific communities, recommender systems have been applied to provide useful tools for papers, books as well as expert finding. However, academic events (conferences, workshops, international symposiums etc.) are an important driven forces to move forwards cooperation among research communities. We realize a SNA based approach for academic events recommendation problem. Scientific communities analysis and visualization are performed to provide an insight into the communities of event series. A prototype is implemented based on the data from DBLP and EventSeer.net, and the result is observed in order to prove the approach.

  14. The Effect of Social Network Diagrams on a Virtual Network of Practice: A Korean Case

    Science.gov (United States)

    Jo, Il-Hyun

    2009-01-01

    This study investigates the effect of the presentation of social network diagrams on virtual team members' interaction behavior via e-mail. E-mail transaction data from 22 software developers in a Korean IT company was analyzed and depicted as diagrams by social network analysis (SNA), and presented to the members as an intervention. Results…

  15. Integrating Micro-level Interactions with Social Network Analysis in Tie Strength Research

    DEFF Research Database (Denmark)

    Torre, Osku; Gupta, Jayesh Prakash; Kärkkäinen, Hannu

    2017-01-01

    , relationships) with large-scale social network analysis (SNA). This study provides a way to find relevant actors from publicly available data in the context of tie strengthening process, and answers how to take this stream of research closer to computational social science.......A social tie is a target for ongoing, high-level scientific debate. Measuring the tie strength in social networks has been an important topic for academic studies since Mark Granovetter's seminal papers in 1970's. However, it is still a problematic issue mainly for two reasons: 1) existing tie...... strengthening process in online social networks. Therefore, we suggest a new approach to tie strength research, which focuses on studying communication patterns (edges) more rather than actors (nodes) in a social network. In this paper we build a social network analysis-based approach to enable the evaluation...

  16. Network science and oral health research.

    Science.gov (United States)

    Maupome, Gerardo; McCranie, Ann

    2015-01-01

    The present overview of research methods describes a scientific enquiry paradigm that is well established in other disciplines, including health research, but that is fairly new to oral health research. Social networks analysis (SNA) or network science research is a set of relational methods purporting to identify and characterize the connections between members of a system or network, as well as the structure of the network. Persons and communities making up the members of networks have commonly been the focus of SNA studies but corporations or living organisms might just as well be organized in networks. SNA is grounded in both graphic imagery and computational models. SNA is based on the assumptions that features and structure of networks are amenable to characterization, that such information sheds light on the ways members of the network relate to each other (sharing information, diseases, norms, and so on), and that through these connections between members the overall network structure and characteristics are shaped. The overview resorts to examples specific to oral health themes and proposes a few general avenues for population-based research. © 2015 American Association of Public Health Dentistry.

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

    DEFF Research Database (Denmark)

    Kacanski, Slobodan; Lusher, Dean

    2017-01-01

    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...

  18. Fighting Dark Networks: Using Social Network Analysis to Implement the Special Operations Targeting Process for Direct and Indirect Approaches

    Science.gov (United States)

    2013-03-01

    environmental impacts -- must be considered. H. A FINAL WORD ON SNA CONCEPTS AND DARK NETWORKS. To construct a useful database of network relational...http://www.jstor.org/stable/2780199?origin= JSTOR -pdf. 145 30 Martin Kilduff and Wenpin Tsai, Social Networks and Organizations (London: SAGE, 2003

  19. Using Social Network Analysis to Better Understand Compulsive Exercise Behavior Among a Sample of Sorority Members.

    Science.gov (United States)

    Patterson, Megan S; Goodson, Patricia

    2017-05-01

    Compulsive exercise, a form of unhealthy exercise often associated with prioritizing exercise and feeling guilty when exercise is missed, is a common precursor to and symptom of eating disorders. College-aged women are at high risk of exercising compulsively compared with other groups. Social network analysis (SNA) is a theoretical perspective and methodology allowing researchers to observe the effects of relational dynamics on the behaviors of people. SNA was used to assess the relationship between compulsive exercise and body dissatisfaction, physical activity, and network variables. Descriptive statistics were conducted using SPSS, and quadratic assignment procedure (QAP) analyses were conducted using UCINET. QAP regression analysis revealed a statistically significant model (R 2 = .375, P QAP regression model. In our sample, women who are connected to "important" or "powerful" people in their network are likely to have higher compulsive exercise scores. This result provides healthcare practitioners key target points for intervention within similar groups of women. For scholars researching eating disorders and associated behaviors, this study supports looking into group dynamics and network structure in conjunction with body dissatisfaction and exercise frequency.

  20. The evolution and expression of the snaR family of small non-coding RNAs

    Science.gov (United States)

    Parrott, Andrew M.; Tsai, Michael; Batchu, Priyanka; Ryan, Karen; Ozer, Harvey L.; Tian, Bin; Mathews, Michael B.

    2011-01-01

    We recently identified the snaR family of small non-coding RNAs that associate in vivo with the nuclear factor 90 (NF90/ILF3) protein. The major human species, snaR-A, is an RNA polymerase III transcript with restricted tissue distribution and orthologs in chimpanzee but not rhesus macaque or mouse. We report their expression in human tissues and their evolution in primates. snaR genes are exclusively in African Great Apes and some are unique to humans. Two novel families of snaR-related genetic elements were found in primates: CAS (catarrhine ancestor of snaR), limited to Old World Monkeys and apes; and ASR (Alu/snaR-related), present in all monkeys and apes. ASR and CAS appear to have spread by retrotransposition, whereas most snaR genes have spread by segmental duplication. snaR-A and snaR-G2 are differentially expressed in discrete regions of the human brain and other tissues, notably including testis. snaR-A is up-regulated in transformed and immortalized human cells, and is stably bound to ribosomes in HeLa cells. We infer that snaR evolved from the left monomer of the primate-specific Alu SINE family via ASR and CAS in conjunction with major primate speciation events, and suggest that snaRs participate in tissue- and species-specific regulation of cell growth and translation. PMID:20935053

  1. Privacy and social network applications

    OpenAIRE

    Roig, Antoni

    2009-01-01

    Privacy technological threatens are no limited to data protection. Social Network Applications (SNA) and ubiquitous computing or Ambient Intelligence face other privacy risks. The business model of SNA and the improvement of data mining allow social computation. SNA regulation should favor privacy-by-design and Privacy Enhancing Technologies (PET). Default friendly-privacy policies should also be adopted. The data portability of the applications shifts SNA into a new field of ubiquitous compu...

  2. Handbook of networking & connectivity

    CERN Document Server

    McClain, Gary R

    1994-01-01

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

  3. A social network analysis approach to alcohol use and co-occurring addictive behavior in young adults.

    Science.gov (United States)

    Meisel, Matthew K; Clifton, Allan D; MacKillop, James; Goodie, Adam S

    2015-12-01

    The current study applied egocentric social network analysis (SNA) to investigate the prevalence of addictive behavior and co-occurring substance use in college students' networks. Specifically, we examined individuals' perceptions of the frequency of network members' co-occurring addictive behavior and investigated whether co-occurring addictive behavior is spread evenly throughout networks or is more localized in clusters. We also examined differences in network composition between individuals with varying levels of alcohol use. The study utilized an egocentric SNA approach in which respondents ("egos") enumerated 30 of their closest friends, family members, co-workers, and significant others ("alters") and the relations among alters listed. Participants were 281 undergraduates at a large university in the Southeastern United States. Robust associations were observed among the frequencies of gambling, smoking, drinking, and using marijuana by network members. We also found that alters tended to cluster together into two distinct groups: one cluster moderate-to-high on co-occurring addictive behavior and the other low on co-occurring addictive behavior. Lastly, significant differences were present when examining egos' perceptions of alters' substance use between the networks of at-risk, light, and nondrinkers. These findings provide empirical evidence of distinct clustering of addictive behavior among young adults and suggest the promise of social network-based interventions for this cohort. Copyright © 2015. Published by Elsevier Ltd.

  4. Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

    Science.gov (United States)

    Kelman, Ilan; Luthe, Tobias; Wyss, Romano; Tørnblad, Silje H; Evers, Yvette; Curran, Marina Martin; Williams, Richard J; Berlow, Eric L

    2016-01-01

    This study integrates quantitative social network analysis (SNA) and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.

  5. Social Network Analysis and Qualitative Interviews for Assessing Geographic Characteristics of Tourism Business Networks.

    Directory of Open Access Journals (Sweden)

    Ilan Kelman

    Full Text Available This study integrates quantitative social network analysis (SNA and qualitative interviews for understanding tourism business links in isolated communities through analysing spatial characteristics. Two case studies are used, the Surselva-Gotthard region in the Swiss Alps and Longyearbyen in the Arctic archipelago of Svalbard, to test the spatial characteristics of physical proximity, isolation, and smallness for understanding tourism business links. In the larger Surselva-Gotthard region, we found a strong relationship between geographic separation of the three communities on compartmentalization of the collaboration network. A small set of businesses played a central role in steering collaborative decisions for this community, while a group of structurally 'peripheral' actors were less influential. By contrast, the business community in Svalbard showed compartmentalization that was independent of geographic distance between actors. Within towns of similar size and governance scale, Svalbard is more compartmentalized, and those compartments are not driven by geographic separation of the collaboration clusters. This compartmentalization in Svalbard was reflected in a lower density of formal business collaboration ties compared to the communities of the Alps. We infer that the difference is due to Svalbard having higher cultural diversity and population turnover than the Alps communities. We propose that integrating quantitative network analysis from simple surveys with qualitative interviews targeted from the network results is an efficient general approach to identify regionally specific constraints and opportunities for effective governance.

  6. Network analysis for science and technology management: Evidence from tuberculosis research in Fiocruz, Brazil.

    Directory of Open Access Journals (Sweden)

    Bruna de Paula Fonseca E Fonseca

    Full Text Available Collaborative networks are of great value for science and technology (S&T institutions as a way of sharing, generating and disseminating new knowledge that could ultimately lead to innovations. Driven by the need to assess the contribution and effectiveness of these networks in informing S&T management, we explored the evolution and dynamics of tuberculosis scientific networks involving the Oswaldo Cruz Foundation (Fiocruz, the major public health S&T Institution in Brazil. Social network analysis (SNA was used to produce a 10-year (2005-2009, 2010-2014 retrospective longitudinal mapping of Brazilian tuberculosis research networks within the country and internationally, highlighting Fiocruz collaborations. Co-authorship analysis showed a significant expansion of collaboration in Brazil and the role of Fiocruz and other leading national institutions in maintaining connectivity, facilitating knowledge exchange and reducing network vulnerability. It also identified influential researchers that can act as information leaders and support strategic decisions. When we focused on networks inside the institution, the analysis showed a clear discontinuation between the clinical and the public health research areas, which needs specific internal policies to improve collaborations since outcomes in TB are expected to provide better diagnostic tools and more effective treatments. The approach provides evidence to support S&T management by pinpointing: key central institutions maintaining network connectivity; most influential researchers that can act as advisors/experts for investment and induction policies; key Fiocruz researchers that could improve information exchange, systems integration and innovation within the institution; opportunities for synergy between internal research groups working in complementary areas. In summary, we observed that SNA parameters proved to be a valuable tool that, along with other indicators, can strengthen knowledge

  7. Network analysis for science and technology management: Evidence from tuberculosis research in Fiocruz, Brazil.

    Science.gov (United States)

    Fonseca, Bruna de Paula Fonseca E; Silva, Marcus Vinicius Pereira da; Araújo, Kizi Mendonça de; Sampaio, Ricardo Barros; Moraes, Milton Ozório

    2017-01-01

    Collaborative networks are of great value for science and technology (S&T) institutions as a way of sharing, generating and disseminating new knowledge that could ultimately lead to innovations. Driven by the need to assess the contribution and effectiveness of these networks in informing S&T management, we explored the evolution and dynamics of tuberculosis scientific networks involving the Oswaldo Cruz Foundation (Fiocruz), the major public health S&T Institution in Brazil. Social network analysis (SNA) was used to produce a 10-year (2005-2009, 2010-2014) retrospective longitudinal mapping of Brazilian tuberculosis research networks within the country and internationally, highlighting Fiocruz collaborations. Co-authorship analysis showed a significant expansion of collaboration in Brazil and the role of Fiocruz and other leading national institutions in maintaining connectivity, facilitating knowledge exchange and reducing network vulnerability. It also identified influential researchers that can act as information leaders and support strategic decisions. When we focused on networks inside the institution, the analysis showed a clear discontinuation between the clinical and the public health research areas, which needs specific internal policies to improve collaborations since outcomes in TB are expected to provide better diagnostic tools and more effective treatments. The approach provides evidence to support S&T management by pinpointing: key central institutions maintaining network connectivity; most influential researchers that can act as advisors/experts for investment and induction policies; key Fiocruz researchers that could improve information exchange, systems integration and innovation within the institution; opportunities for synergy between internal research groups working in complementary areas. In summary, we observed that SNA parameters proved to be a valuable tool that, along with other indicators, can strengthen knowledge platforms to support S

  8. Clinical Grade "SNaPshot" Genetic Mutation Profiling in Multiple Myeloma.

    Science.gov (United States)

    O'Donnell, Elizabeth; Mahindra, Anuj; Yee, Andrew J; Nardi, Valentina; Birrer, Nicole; Horick, Nora; Borger, Darrell; Finkelstein, Dianne; Iafrate, John A; Raje, Noopur

    2015-01-01

    Whole genome sequencing studies have identified several oncogenic mutations in multiple myeloma (MM). As MM progresses, it evolves genetically underscoring the need to have tools for rapid detection of targetable mutations to optimize individualized treatment. Massachusetts General Hospital (MGH) has developed a Clinical Laboratory Improvement Amendments (CLIA)-approved, high-throughput, genotyping platform to determine the mutation status of a panel of known oncogenes. Sequence analysis using SNaPshot on DNA extracted from bone marrow and extramedullary plasmacytomas is feasible and leads to the detection of potentially druggable mutations. Screening MM patients for somatic mutations in oncogenes may provide novel targets leading to additional therapies for this patient population.

  9. Peer Influence on Academic Performance: A Social Network Analysis of Social-Emotional Intervention Effects.

    Science.gov (United States)

    DeLay, Dawn; Zhang, Linlin; Hanish, Laura D; Miller, Cindy F; Fabes, Richard A; Martin, Carol Lynn; Kochel, Karen P; Updegraff, Kimberly A

    2016-11-01

    Longitudinal social network analysis (SNA) was used to examine how a social-emotional learning (SEL) intervention may be associated with peer socialization on academic performance. Fifth graders (N = 631; 48 % girls; 9 to 12 years) were recruited from six elementary schools. Intervention classrooms (14) received a relationship building intervention (RBI) and control classrooms (8) received elementary school as usual. At pre- and post-test, students nominated their friends, and teachers completed assessments of students' writing and math performance. The results of longitudinal SNA suggested that the RBI was associated with friend selection and peer influence within the classroom peer network. Friendship choices were significantly more diverse (i.e., less evidence of social segregation as a function of ethnicity and academic ability) in intervention compared to control classrooms, and peer influence on improved writing and math performance was observed in RBI but not control classrooms. The current findings provide initial evidence that SEL interventions may change social processes in a classroom peer network and may break down barriers of social segregation and improve academic performance.

  10. Gender, personal networks, and drug use among rural African Americans.

    Science.gov (United States)

    Goldbarg, Rosalyn Negrón; Brown, Emma J

    One of the main unifying concepts of research examining gender variations in drug use behavior is the social network. Yet, research specifically focusing on how the social networks of these groups differ by gender is limited. Few studies have investigated the social networks of rural African Americans who use drugs. In this study, we compared the personal networks of 20 rural African-American men and women addicted to cocaine using social network analysis (SNA) methods. The data do not support strong assertions about gender differences in the personal networks of the study sample. However, the results of the study suggest that men tend to have more drug users in their networks than women, as well as less structurally cohesive networks. Women tend to include more men in their personal networks than men included women. Implications of the research results for network-based drug prevention intervention as well as the value of SNA methods for drug use research are discussed.

  11. Online Formative Assessments with Social Network Awareness

    Science.gov (United States)

    Lin, Jian-Wei; Lai, Yuan-Cheng

    2013-01-01

    Social network awareness (SNA) has been used extensively as one of the strategies to increase knowledge sharing and collaboration opportunities. However, most SNA studies either focus on being aware of peer's knowledge context or on social context. This work proposes online formative assessments with SNA, trying to address the problems of online…

  12. Evaluating individual performance in team sports : A network analysis of Batsmen and Bowlers in Cricket

    CERN Document Server

    Mukherjee, Satyam

    2012-01-01

    Quantifying individual performance in team activity is critical in team selection in international sports. We explore the application of Social Network Analysis (SNA) to rate individuals in an team activity. We choose the game of Cricket as an example. The number runs scored by batsmen and wickets taken by bowlers serves as a natural way of quantifying the performance of a cricketer. Traditionally the batsmen and bowlers are rated on their batting or bowling average respectively. However in a game like cricket it is always important the manner in which one scores the runs or takes a wicket. Scoring runs against a strong bowling line-up or delivering a brilliant performance against a team with strong batting line-up deserves more credit. A player's average is not able to capture this aspect of the game. In this paper we present a refined method to quantify the `quality' of runs scored by a batsman or wickets taken by a bowler. We apply tools of Social Network Analysis (SNA) to judge a cricketer's performance. ...

  13. Understanding Stakeholders’ Influence on Project Success with a New SNA Method: A Case Study of the Green Retrofit in China

    Directory of Open Access Journals (Sweden)

    Xin Liang

    2017-10-01

    Full Text Available Stakeholders strongly influence project success, particularly for complex projects with heterogeneous stakeholders, and hence, understanding their influence is essential for project management and implementation. This paper proposes an original model based on social network analysis (SNA, which first introduces critical success factors (CSFs as intermediate variables between stakeholders and project success. The model can demonstrate the interrelation between stakeholders and CSFs, and the results can reveal how stakeholders influence project success. Green retrofit is a typical type of complex project. The stakeholder relationship in green retrofit projects is more complex than in new projects, since more stakeholders (e.g., tenants and facility managers who have particular interrelations (e.g., lease contract and split incentives between owners and tenants are involved. Therefore, a case study of green retrofit in China was conducted to illustrate how the proposed model works. The results indicated the priorities and similarities of stakeholders in green retrofit. Stakeholders are categorized into five clusters according to their relationship. Based on the results, the important role of stakeholders in green retrofit projects was discussed. The main contribution of this study is providing a novel method to reveal how stakeholders influence the success of complex projects.

  14. Auto-interpreter for CYP2D6 SNaPshot genotyping.

    Science.gov (United States)

    Ong, Sungmoon; Jeong, Hye-Eun; Lee, Sang Seop; Shon, Ji-Hong; Shin, Jae-Gook; Kim, Eun-Young

    2008-11-06

    CYP2D6 genotyping using SNaPshot method is a very useful tool clinically. However it's hard to interpret the obtained data as a genotype without training. Thus SNaPshot auto-interpreter for the genotype was designed to interpret obtained raw data to a genotype. The auto-interpreter showed good concordance with experts' reading. The validated auto-interpreter of CYP2D6 genotyping using SNaPshot can contribute to accelerating the clinical use.

  15. Arresting Strategy Based on Dynamic Criminal Networks Changing over Time

    Directory of Open Access Journals (Sweden)

    Junqing Yuan

    2013-01-01

    Full Text Available We investigate a sequence of dynamic criminal networks on a time series based on the dynamic network analysis (DNA. According to the change of networks’ structure, networks’ variation trend is analyzed to forecast its future structure. Finally, an optimal arresting time and priority list are designed based on our analysis. Better results can be expected than that based on social network analysis (SNA.

  16. 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

  17. Analyzing the role of social networks in mapping knowledge flows: A case of a pharmaceutical company in India

    Directory of Open Access Journals (Sweden)

    V. Murale

    2014-03-01

    Full Text Available Knowledge Management literature lays emphasis on the fact that a major chunk of knowledge dissemination occurs through the various forms of social networks that exist within the organizations. A social network is a simple structure comprising of set of actors or nodes that may have relationships ties with one another. The social network analysis (SNA will help in mapping and measuring formal and informal relationships to understand what facilitates or impedes the knowledge flows that bind interacting units. This paper aims at studying the knowledge flows that happen through the social networks. It first, provides a conceptual framework and review of literature on the recent research and application of knowledge mapping and SNA, followed by a discussion on application of SNA for mapping knowledge flows in a pharmaceutical firm. In the last part, Knowledge maps are presented to illustrate the actual knowledge flow in firm.

  18. Evaluation of Coordination of Emergency Response Team through the Social Network Analysis. Case Study: Oil and Gas Refinery.

    Science.gov (United States)

    Mohammadfam, Iraj; Bastani, Susan; Esaghi, Mahbobeh; Golmohamadi, Rostam; Saee, Ali

    2015-03-01

    The purpose of this study was to examine the cohesions status of the coordination within response teams in the emergency response team (ERT) in a refinery. For this study, cohesion indicators of social network analysis (SNA; density, degree centrality, reciprocity, and transitivity) were utilized to examine the coordination of the response teams as a whole network. The ERT of this research, which was a case study, included seven teams consisting of 152 members. The required data were collected through structured interviews and were analyzed using the UCINET 6.0 Social Network Analysis Program. The results reported a relatively low number of triple connections, poor coordination with key members, and a high level of mutual relations in the network with low density, all implying that there were low cohesions of coordination in the ERT. The results showed that SNA provided a quantitative and logical approach for the examination of the coordination status among response teams and it also provided a main opportunity for managers and planners to have a clear understanding of the presented status. The research concluded that fundamental efforts were needed to improve the presented situations.

  19. A Framework for Collaborative Networked Learning in Higher Education: Design & Analysis

    Directory of Open Access Journals (Sweden)

    Ghassan F. Issa

    2014-06-01

    Full Text Available This paper presents a comprehensive framework for building collaborative learning networks within higher educational institutions. This framework focuses on systems design and implementation issues in addition to a complete set of evaluation, and analysis tools. The objective of this project is to improve the standards of higher education in Jordan through the implementation of transparent, collaborative, innovative, and modern quality educational programs. The framework highlights the major steps required to plan, design, and implement collaborative learning systems. Several issues are discussed such as unification of courses and program of studies, using appropriate learning management system, software design development using Agile methodology, infrastructure design, access issues, proprietary data storage, and social network analysis (SNA techniques.

  20. 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.

  1. Social network analysis of international scientific collaboration on psychiatry research.

    Science.gov (United States)

    Wu, Ying; Duan, Zhiguang

    2015-01-01

    Mental disorder is harmful to human health, effects social life seriously and still brings a heavy burden for countries all over the world. Scientific collaboration has become the indispensable choice for progress in the field of biomedicine. However, there have been few scientific publications on scientific collaboration in psychiatry research so far. The aim of this study was to measure the activities of scientific collaboration in psychiatry research at the level of authors, institutions and countries. We retrieved 36557 papers about psychiatry from Science Ciation Index Expanded (SCI-Expanded) in web of science. Additionally, some methods such as social network analysis (SNA), K-plex analysis and Core-Periphery were used in this study. Collaboration has been increasing at the level of authors, institutions and countries in psychiatry in the last ten years. We selected the top 100 prolific authors, institutions and 30 countries to construct collaborative map respectively. Freedman, R and Seidman, LJ were the central authors, Harvard university was the central institution and the USA was the central country of the whole network. Notably, the rate of economic development of countries affected collaborative behavior. The results show that we should encourage multiple collaboration types in psychiatry research as they not only help researchers to master the current research hotspots but also provide scientific basis for clinical research on psychiatry and suggest policies to promote the development of this area.

  2. Validation of networks derived from snowball sampling of municipal science education actors

    DEFF Research Database (Denmark)

    von der Fehr, Ane; Sølberg, Jan; Bruun, Jesper

    2016-01-01

    Social network analysis (SNA) has been used in many educational studies in the past decade, but what these studies have in common is that the populations in question in most cases are defined and known to the researchers studying the networks. Snowball sampling is an SNA methodology most often used...... to study hidden populations, for example, groups of homosexual people, drug users or people with sexually transmitted diseases. By use of a snowball sampling approach, this study mapped municipal social networks of educational actors, who were otherwise hidden to the researchers. Subsequently...... predictions based on existing knowledge of the municipalities aligned with SNA data. However, these discrepancies could be explained by development in the municipalities in the time following previous investigations. This study shows that snowball sampling is an applicable method to use for mapping hidden...

  3. Analysing Health Professionals' Learning Interactions in an Online Social Network: A Longitudinal Study.

    Science.gov (United States)

    Li, Xin; Verspoor, Karin; Gray, Kathleen; Barnett, Stephen

    2016-01-01

    This paper summarises a longitudinal analysis of learning interactions occurring over three years among health professionals in an online social network. The study employs the techniques of Social Network Analysis (SNA) and statistical modeling to identify the changes in patterns of interaction over time and test associated structural network effects. SNA results indicate overall low participation in the network, although some participants became active over time and even led discussions. In particular, the analysis has shown that a change of lead contributor results in a change in learning interaction and network structure. The analysis of structural network effects demonstrates that the interaction dynamics slow down over time, indicating that interactions in the network are more stable. The health professionals may be reluctant to share knowledge and collaborate in groups but were interested in building personal learning networks or simply seeking information.

  4. 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...

  5. A collaborative EDNAP exercise on SNaPshot™-based mtDNA control region typing

    DEFF Research Database (Denmark)

    Weiler, NEC; Baca, K; Ballard, D

    2017-01-01

    A collaborative European DNA Profiling (EDNAP) Group exercise was undertaken to assess the performance of an earlier described SNaPshot™-based screening assay (denoted mini-mtSNaPshot) (Weiler et al., 2016) [1] that targets 18 single nucleotide polymorphism (SNP) positions in the mitochondrial (m...

  6. Finding The Most Important Actor in Online Crowd by Social Network Analysis

    Science.gov (United States)

    Yuliana, I.; Santosa, P. I.; Setiawan, N. A.; Sukirman

    2017-02-01

    Billion of people create trillions of connections through social media every single day. The increasing use of social media has led to dramatic changes in the of way science, government, healthcare, entertainment and enterprise operate. Large-scale participation in Technology-Mediated Social Participation (TMSP) system has opened up incredible new opportunities to deploy online crowd. This descriptive-correlational research used social network analysis (SNA) on data gathered from Fanpage Facebook of Greenpeace Indonesia related to important critical issues, the bushfires in 2015. SNA identifies relations on each member by sociometrics parameter such as three centrality (degree, closeness and betweenesse) for measuring and finding the most important actor in the online community. This paper use Fruchterman Rein-gold algorithm to visualize the online community in a graph, while Clauset-Newman-Moore is a technique to identify groups in community. As the result found 3735 vertices related to actors, 6927 edges as relation, 14 main actors in size order and 22 groups in Greenpeace Indonesia online community. This research contributes to organize some information for Greenpeace Indonesia managing their potency in online community to identify human behaviour.

  7. Clinical Grade “SNaPshot” Genetic Mutation Profiling in Multiple Myeloma

    Directory of Open Access Journals (Sweden)

    Elizabeth O'Donnell

    2015-01-01

    Full Text Available Whole genome sequencing studies have identified several oncogenic mutations in multiple myeloma (MM. As MM progresses, it evolves genetically underscoring the need to have tools for rapid detection of targetable mutations to optimize individualized treatment. Massachusetts General Hospital (MGH has developed a Clinical Laboratory Improvement Amendments (CLIA-approved, high-throughput, genotyping platform to determine the mutation status of a panel of known oncogenes. Sequence analysis using SNaPshot on DNA extracted from bone marrow and extramedullary plasmacytomas is feasible and leads to the detection of potentially druggable mutations. Screening MM patients for somatic mutations in oncogenes may provide novel targets leading to additional therapies for this patient population.

  8. Use of social network analysis in maternity care to identify the profession most suited for case manager role.

    Science.gov (United States)

    Groenen, Carola J M; van Duijnhoven, Noortje T L; Faber, Marjan J; Koetsenruijter, Jan; Kremer, Jan A M; Vandenbussche, Frank P H A

    2017-02-01

    To improve Dutch maternity care, professionals start working in interdisciplinary patient-centred networks, which includes the patients as a member. The introduction of the case manager is expected to work positively on both the individual and the network level. However, case management is new in Dutch maternity care. The present study aims to define the profession that would be most suitable to fulfil the role of case manager. The maternal care network in the Nijmegen region was determined by using Social Network Analysis (SNA). SNA is a quantitative methodology that measures and analyses patient-related connections between different professionals working in a network. To identify the case manager we focused on the position, reach, and connections in the network of the maternal care professionals. Maternity healthcare professionals in a single region of the Netherlands with an average of 4,500 births/year. The participants were 214 individual healthcare workers from eight different professions. The total network showed 3948 connections between 214 maternity healthcare professionals with a density of 0.08. Each profession had some central individuals in the network. The 52 community-based midwives were responsible for 51% of all measured connections. The youth health doctors and nurses were mostly situated on the periphery and less connected. The betweenness centrality had the highest score in obstetricians and community-based midwives. Only the community-based midwives had connections with all other groups of professions. Almost all professionals in the network could reach other professionals in two steps. Copyright © 2016 Elsevier Ltd. All rights reserved.

  9. Multiplex SNaPshot for detection of BRCA1/2 common mutations in Spanish and Spanish related breast/ovarian cancer families

    Directory of Open Access Journals (Sweden)

    Carracedo Ángel

    2007-06-01

    Full Text Available Abstract Background It is estimated that 5–10% of all breast cancer are hereditary and attributable to mutations in the highly penetrance susceptibility genes BRCA1 and BRCA2. The genetic analysis of these genes is complex and expensive essentially because their length. Nevertheless, the presence of recurrent and founder mutations allows a pre-screening for the identification of the most frequent mutations found in each geographical region. In Spain, five mutations in BRCA1 and other five in BRCA2 account for approximately 50% of the mutations detected in Spanish families. Methods We have developed a novel PCR multiplex SNaPshot reaction that targets all ten recurrent and founder mutations identified in BRCA1 and BRCA2 in Spain to date. Results The SNaPshot reaction was performed on samples previously analyzed by direct sequencing and all mutations were concordant. This strategy permits the analysis of approximately 50% of all mutations observed to be responsible for breast/ovarian cancer in Spanish families using a single reaction per patient sample. Conclusion The SNaPshot assay developed is sensitive, rapid, with minimum cost per sample and additionally can be automated for high-throughput genotyping. The SNaPshot assay outlined here is not only useful for analysis of Spanish breast/ovarian cancer families, but also e.g. for populations with Spanish ancestry, such as those in Latin America.

  10. Using social network analysis to examine the decision-making process on new vaccine introduction in Nigeria.

    Science.gov (United States)

    Wonodi, C B; Privor-Dumm, L; Aina, M; Pate, A M; Reis, R; Gadhoke, P; Levine, O S

    2012-05-01

    The decision-making process to introduce new vaccines into national immunization programmes is often complex, involving many stakeholders who provide technical information, mobilize finance, implement programmes and garner political support. Stakeholders may have different levels of interest, knowledge and motivations to introduce new vaccines. Lack of consensus on the priority, public health value or feasibility of adding a new vaccine can delay policy decisions. Efforts to support country-level decision-making have largely focused on establishing global policies and equipping policy makers with the information to support decision-making on new vaccine introduction (NVI). Less attention has been given to understanding the interactions of policy actors and how the distribution of influence affects the policy process and decision-making. Social network analysis (SNA) is a social science technique concerned with explaining social phenomena using the structural and relational features of the network of actors involved. This approach can be used to identify how information is exchanged and who is included or excluded from the process. For this SNA of vaccine decision-making in Nigeria, we interviewed federal and state-level government officials, officers of bilateral and multilateral partner organizations, and other stakeholders such as health providers and the media. Using data culled from those interviews, we performed an SNA in order to map formal and informal relationships and the distribution of influence among vaccine decision-makers, as well as to explore linkages and pathways to stakeholders who can influence critical decisions in the policy process. Our findings indicate a relatively robust engagement of key stakeholders in Nigeria. We hypothesized that economic stakeholders and implementers would be important to ensure sustainable financing and strengthen programme implementation, but some economic and implementation stakeholders did not appear centrally on

  11. 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.

  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. Strategic Networking in the Technical HEI‘s of the Baltic Sea Region

    Directory of Open Access Journals (Sweden)

    Justas Nugaras

    2012-12-01

    Full Text Available This paper presents the results of the empirical research of the networking of Technical Higher Education Institutions (HEI‘S of the Baltic Sea region. The research was conducted in order to understand how the Social Network Analysis (SNA and network mapping methods could help to strengthen institution’s strategic perspective through networking. The author analyse the interaction phenomena in the Higher education sector; its’ impact for networking of institutions and for the network itself; the role of the position in the networks; abilities to strengthen the node’s perception of the network for the strategizing purposes. The research was based on the SNA of the Erasmus programme student mobility data. The results of the research cover the implications of aspects of the network centrality, clustering and ego networks let to identify the node’s position in the network, and to understand surrounding network. The research disclosed that the SNA could be applied in supporting the strategizing process by: increasing of understanding of embedded networks, having more realistic network picture, also could be used as supplement evaluation and development planning method for the relationships portfolio management for HEI’s.

  14. 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.

  15. The study on the core personality trait words of Chinese medical university students based on social network analysis.

    Science.gov (United States)

    Wu, Ying; Xue, Yunzhen; Xue, Zhanling

    2017-09-01

    The medical university students in China whose school work is relatively heavy and educational system is long are a special professional group. Many students have psychological problems more or less. So, to understand their personality characteristics will provide a scientific basis for the intervention of psychological health.We selected top 30 personality trait words according to the order of frequency. Additionally, some methods such as social network analysis (SNA) and visualization technology of mapping knowledge domain were used in this study.Among these core personality trait words Family conscious had the 3 highest centralities and possessed the largest core status and influence. From the analysis of core-peripheral structure, we can see polarized core-perpheral structure was quite obvious. From the analysis of K-plex, there were in total 588 "K-2"K-plexs. From the analysis of Principal Components, we selected the 11 principal components.This study of personality not only can prevent disease, but also provide a scientific basis for students' psychological healthy education. In addition, we have adopted SNA to pay more attention to the relationship between personality trait words and the connection among personality dimensions. This study may provide the new ideas and methods for the research of personality structure.

  16. Burning through organizational boundaries? Examining inter-organizational communication networks in policy-mandated collaborative bushfire planning groups

    Science.gov (United States)

    Rachel F. Brummel; Kristen C. Nelson; Pamela J. Jakes

    2012-01-01

    Collaboration can enhance cooperation across geographic and organizational scales, effectively "burning through" those boundaries. Using structured social network analysis (SNA) and qualitative in-depth interviews, this study examined three collaborative bushfire planning groups in New South Wales, Australia and asked: How does participation in policy-...

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Mini-SNaPshot multiplex assays authenticate elephant ivory and simultaneously identify the species origin.

    Science.gov (United States)

    Kitpipit, Thitika; Thongjued, Kantima; Penchart, Kitichaya; Ouithavon, Kanita; Chotigeat, Wilaiwan

    2017-03-01

    Illegal trading of ivory is mainly responsible for the dramatic decline in elephant populations. Thailand is one of the largest laundering hotspots for African ivory, as the domestic Asian elephant ivory can be legally traded. So, to help combat ivory poaching and smuggling, an efficient method is needed to identify the elephant species from its ivory and ivory products. In this study, a mini-SNaPshot® multiplex assay was developed and fully validated for the identification of confiscated ivory and low DNA template ivory products. Elephantid- and elephant species-specific mitochondrial single nucleotide polymorphisms (SNPs) were identified from 207 mammalian and 1705 elephant/mammoth cytochrome b sequence alignments. Seven informative SNPs were used for assay development. The assay unambiguously and accurately identified authentic elephant ivory and its species of origin on the basis of peak size and color observed in the haplotype profile. The assay was highly efficient for analysis of confiscated ivory and low-template ivory products with a 99.29% success rate (N=140). It was highly reproducible, exhibited no cross-reaction with eight other mammalian DNA; and had 100% identification accuracy. In addition, nested and direct PCR amplification were also compatible with the developed assay. This efficient assay should benefit wildlife forensic laboratories and aid in the prosecution of elephant-related crimes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  2. 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

  3. Exploring the use of social network analysis to measure communication between disease programme and district managers at sub-national level in South Africa.

    Science.gov (United States)

    Kawonga, Mary; Blaauw, Duane; Fonn, Sharon

    2015-06-01

    With increasing interest in maximising synergies between disease control programmes (DCP) and general health services (GHS), methods are needed to measure interactions between DCP and GHS actors. In South Africa, administrative integration reforms make GHS managers at decentralised level (district managers) responsible for the oversight of DCP operations within districts, with DCP managers (programme managers) providing specialist support. The reforms necessitate interdependence, but these actors work together ineffectively. Communication is crucial for joint working, but no research to assess communication between these actors has been done. This study explores the use of social network analysis (SNA) to measure the extent to which programme and district managers in South Africa communicate, using HIV monitoring and evaluation (M&E) as an exemplar. Data were collected from fifty one managers in two provinces during 2010-2011, to measure: a) one-on-one task-related communication - talking about the collation (verification, reporting) and use of HIV data for monitoring HIV interventions; and b) group communication through co-participating in management committees where HIV data are used for monitoring HIV interventions in districts. SNA measures were computed to describe actor centrality, network density (cohesion), and communication within and between respective manager groups. Block modelling was applied to identify management committees that connect respective manager groups. Results show HIV programme managers located at higher level communicated largely amongst themselves as a group (homophily), seldom talked to the district managers to whom they are supposed to provide specialist HIV M&E support, and rarely participated with them in management committees. This research demonstrates the utility of SNA as a tool for measuring the extent of communication between DCP and GHS actors at sub-national level. Actions are needed to bridge observed communication gaps in

  4. 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...

  5. Using Social Network Analysis as a Method to Assess and Strengthen Participation in Health Promotion Programs in Vulnerable Areas

    DEFF Research Database (Denmark)

    Hindhede, Anette Lykke; Aagaard-Hansen, Jens

    2017-01-01

    within communities. The concept of community reflects the idea that people’s behavior and well-being are influenced by interaction with others, and here, health promotion requires participation and local leadership to facilitate transmission and uptake of interventions for the overall community......This paper provides an example of the application of Social Network Analysis (SNA) method to assess community participation thereby strengthening planning and implementation of health promotion programming. Community health promotion often takes the form of services that reach out to or are located...... to achieve social change. However, considerable uncertainty exists over exact levels of participation in these interventions. The paper draws on a mixed methods research within a community development project in a vulnerable neighborhood of a town in Denmark. It presents a detailed analysis of the way...

  6. 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...

  7. Narrative ecosystems through the network analysis lens. Step one: The production of U.S. TV series, between capital and labor strategies

    Directory of Open Access Journals (Sweden)

    Marco Ruffino

    2016-06-01

    Full Text Available This paper aims to present a first step in the investigation of the environment hosting narrative ecosystems through the tools offered by Social Network Analysis (SNA. The narrative ecosystem paradigm is a cross-disciplinary approach that considers vast narratives as the result of an ecosystemic design, where a general model is developed in advance as an evolutionary system. Consistently with this systemic view, our idea is to bring the relations among the components of the ecosystems and the environment that host them (i.e. the entertainment industry to the fore through the implementation of SNA. In order to do so, we focused on the relational patterns characterizing a sample of 164 U.S. TV series aired between 1984 and 2013. For each one of them, we collected data on executive producers, broadcasters, production studios, actors and writers. Through the analysis of the networks we obtained by computing the data, we drew some conclusions regarding the effectiveness of the ecological and evolutionary paradigm, the non-rigid and opportunistic patterns of alliances and coalitions among competitive firms, the relevance of the strategies of capital implemented by the firms and the strategies of labor implemented by the people.

  8. 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

  9. Social Network Analysis of peer-specific safety support and ergonomic behaviors: An application to safe patient handling.

    Science.gov (United States)

    Hurtado, David A; Dumet, Lisset M; Greenspan, Samuel A; Rodriguez, Yaritza I

    2018-04-01

    This study applied Social Network Analysis (SNA) to test whether advice-seeking interactions among peers about safe patient handling correlate with a higher frequency of equipment use. Patient-care workers (n=38) at a community hospital in Oregon nominated peers they would consult for advice regarding safe patient handling. Results show a positive correlation between identifying more peers for safe patient handling advice and using equipment more frequently. Moreover, nurses with more reciprocal advice seeking nominations used safe patient handling equipment more frequently. However, employees who would be more consulted about safe patient handling by their peers did not use equipment more frequently than nurses with fewer nominations. Despite the small sample size, the magnitude of the adjusted regressions coefficients ranged between 3 to 4 standard deviations. These results suggest that having more or reciprocal sources of peer-based support may trigger ergonomic related behaviors such as frequent utilization of equipment. Copyright © 2017 Elsevier Ltd. All rights reserved.

  10. the principles of diversity and geographical proximity in an industrial ecosystem: social network analysis in the Toluca-Lerma region

    Directory of Open Access Journals (Sweden)

    Manuel Alexis Vazquez Zacarias

    2015-07-01

    Full Text Available Industrial ecology allows the traditional model of industrial activity, where individual manufacturing process that takes raw materials in order to generate products, to be transformed into a more comprehensive model of a regional economy named industrial ecosystem. This ecosystem functions through industrial symbiosis alliances formed by firms that cooperate through the exchange of residues in order to use them as inputs to transform them into valuable products. Moreover, the principles of geographical proximity and diversity of the firms have been found in successful ecosystems in developed countries. This study contributes empirically by using social network analysis (SNA methods to explore, the presence of these two principles in an industrial ecosystem in the Toluca-Lerma region in Mexico, consisting of 30 firms that have industrial symbiosis alliances. We conclude that in the context of developing countries, the symbiotic exchanges may not be fully explained with the principles of geographical proximity and diversity.

  11. 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

  12. 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).

  13. 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...

  14. Diffusion of nanotechnology knowledge in Turkey and its network structure

    OpenAIRE

    Tonta, Yaşar; Darvish, Hamid

    2016-01-01

    This paper aims to assess the diffusion and adoption of nanotechnology knowledge within the Turkish scientific community using social network analysis (SNA) and bibliometrics. We retrieved a total of 10,062 records of nanotechnology papers authored by Turkish researchers between 2000 and 2011 from Web of Science (WoS) and divided the data set into two 6-year periods. We analyzed the most prolific and collaborative authors and universities on individual, institutional and international level...

  15. Judicial Transformations In Ecuador: The Balance Of Power Seen Through The Analysis Of Social Networks

    Directory of Open Access Journals (Sweden)

    Efrén Ernesto Guerrero

    2015-11-01

    Full Text Available This text explores the balance of powers in the Republic of Ecuador through Social Network Analysis (SNA. It argues that formal and informal ties among political system’s actors can be affected as a result of an improvement action within a part of the State. The Article recounts three essential elements: the theoretical apparatus of the balance of power in the State, a summary of the reform actions in the Ecuadorian juridical system, and an analytical contrast between governance models of the Ecuadorian State after the reform of the judiciary, conducted between 2010 and 2014. For this purpose, a comparison of the models of balance by using social network analysis is proposed; thereof a series of statistics that will show the possibility of changes in the capabilities of horizontal accountability of the Judiciary are obtained.  This data show an evidence base that small changes in the fabric of government relations have extensive quantitative consequences on the balance of powers, and appear as heuristics of change in the dynamics of political power. It concludes indicating that reforms of the judicial system have created a more efficient system but, according to the obtained data, centrality of power can generate unwanted effects in public administration and in the structure of power control of the State.

  16. Adolescent peer networks and the potential for the diffusion of intervention effects.

    Science.gov (United States)

    Rulison, Kelly L; Gest, Scott D; Osgood, D Wayne

    2015-01-01

    Many evaluation studies assess the direct effect of an intervention on individuals, but there is an increasing interest in clarifying how interventions can impact larger social settings. One process that can lead to these setting-level effects is diffusion, in which intervention effects spread from participants to non-participants. Diffusion may be particularly important when intervention participation rates are low, as they often are in universal family based prevention programs. We drew on socialization and diffusion theories to articulate how features of peer networks may promote the diffusion of intervention effects. Then, we tested the measurement properties of ten social network analytic (SNA) measures of diffusion potential. Data were from 42 networks (n = 5,784 students) involved in the PROSPER intervention trial. All families of sixth-grade students were invited to participate in a family based substance use prevention program, and 17 % of the families attended at least one session. We identified two dimensions of network structure--social integration and location of intervention participants in their peer network--that might promote diffusion. Analyses demonstrated that these SNA measures varied across networks and were distinct from traditional analytic measures that do not require social network analysis (i.e., participation rate, how representative participants are of the broader population). Importantly, several SNA measures and the global network index predicted diffusion over and above the effect of participation rate and representativeness. We conclude by recommending which SNA measures may be the most promising for studying how networks promote the diffusion of intervention effects and lead to setting-level effects.

  17. Social Set Analysis

    DEFF Research Database (Denmark)

    Vatrapu, Ravi; Hussain, Abid; Buus Lassen, Niels

    2015-01-01

    This paper argues that the basic premise of Social Network Analysis (SNA) -- namely that social reality is constituted by dyadic relations and that social interactions are determined by structural properties of networks-- is neither necessary nor sufficient, for Big Social Data analytics...... of Facebook or Twitter data. However, there exist no other holistic computational social science approach beyond the relational sociology and graph theory of SNA. To address this limitation, this paper presents an alternative holistic approach to Big Social Data analytics called Social Set Analysis (SSA...... analytics tools for Big Social Data. Four demonstrative case studies, employing SSA, covering the range of descriptive, predictive, visual and prescriptive analytics are presented and briefly discussed....

  18. Participation in protected areas: a social network case study in Catalonia, Spain

    Directory of Open Access Journals (Sweden)

    Laura Calvet-Mir

    2015-12-01

    Full Text Available Local participation of stakeholders in governance of protected areas is considered to be important to natural resource management and biodiversity conservation. Social network analysis (SNA is a useful tool for analysis because it allows the understanding of stakeholders' relationships, interactions, and influences through communication networks. We combine quantitative and qualitative data to undertake a SNA for the natural park of Sant Llorenç del Munt in Catalonia, Spain. This is aimed at (1 assessing the structure of the communication network; (2 comparing the informal communication network with the formal participatory bodies of the natural park; and (3 selecting participants for subsequent analyses of the adequate governance structure of the natural park. The results suggest that an informal network of communication, which is reasonably well represented in participatory bodies, exists. However, this communication network is not functioning perfectly because stakeholders experience a lack of trust in the governance bodies of the park, which they perceive to be ineffective. Our results show that SNA is an effective tool to support the creation of a broad representation of stakeholders in participatory processes.

  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. 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....

  1. 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.

  2. Typing of 49 autosomal SNPs by SNaPshot in the Slovenian population

    DEFF Research Database (Denmark)

    Drobnic, Katja; Børsting, Claus; Rockenbauer, Eszter

    2010-01-01

    A total of 157 unrelated individuals residing in Slovenia were typed for 49 of the autosomal single nucleotide polymorphisms (SNPs) in the SNPforID 52plex with the SNaPshot assay. We obtained full SNP profiles in all but one individual and perfect concordance was obtained in duplicated analyses...... with the Danish population. The mean power of discrimination for the Slovenian population was 1.1 x 10(-19), and the mean exclusion probability for trios was 99.96%....

  3. 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

  4. Use of Network Centrality Measures to Explain Individual Levels of Herbal Remedy Cultural Competence among the Yucatec Maya in Tabi, Mexico.

    Science.gov (United States)

    Hopkins, Allison

    2011-08-01

    Common herbal remedy knowledge varies and is transmitted among individuals who are connected through a social network. Thus, social relationships have the potential to account for some of the variation in knowledge. Cultural consensus analysis (CCA) and social network analysis (SNA) were used together to study the association between intracultural variation in botanical remedy knowledge and social relationships in Tabi, Yucatan, Mexico. CCA, a theory of culture as agreement, was used to assess the competence of individuals in a domain of herbal remedies by measuring individual competence scores within that domain. There was a weak but positive association between these competence scores and network centrality scores. This association disappeared when age was included in the model. People in Tabi, who have higher competence in herbal remedies tend to be older and more centrally located in the herbal remedy inquiry network. The larger implication of the application of CCA and SNA for understanding the acquisition and transmission of cultural knowledge is also explored.

  5. SNaP® Wound Care System: Ultraportable Mechanically Powered Negative Pressure Wound Therapy.

    Science.gov (United States)

    Fong, Kenton D; Marston, William A

    2012-02-01

    Negative pressure wound therapy (NPWT) is a well-accepted modality for treatment of difficult wounds, but has traditionally required a bulky electrically powered pump that was difficult to procure and use for both caregivers and patients. Often times, treatment of refractory smaller-sized wounds was impractical even though they may benefit from NPWT. Spiracur (Sunnyvale, CA) has developed a simple, easy-to-use, single-use, off-the-shelf, mechanically powered NPWT device that weighs Smart Negative Pressure (SNaP®) Wound Care System is a novel light-weight NPWT device that does not require an electrically powered pump. Instead, the SNaP system utilizes specialized springs to generate a preset (-75, -100, and -125 mmHg) continuous subatmospheric pressure level to the wound bed. This technology has demonstrated similar efficacy and increased usability for both clinicians and patients when compared with electrically powered NPWT devices. Chronic, acute, traumatic, subacute, and dehisced wounds, partial-thickness burns, ulcers (such as diabetic or pressure), and surgically closed incisions and flaps. Wounds with excess necrotic tissue, active infection, fistulas, exposed vital structures, untreated osteomyelitis, and that are highly exudative. The SNaP system was not designed for wounds that exceed the size of the dressing in surface area or have exudate levels greater than capacity of the cartridge.

  6. 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.

  7. 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...

  8. 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...

  9. Searching social networks for subgraph patterns

    Science.gov (United States)

    Ogaard, Kirk; Kase, Sue; Roy, Heather; Nagi, Rakesh; Sambhoos, Kedar; Sudit, Moises

    2013-06-01

    Software tools for Social Network Analysis (SNA) are being developed which support various types of analysis of social networks extracted from social media websites (e.g., Twitter). Once extracted and stored in a database such social networks are amenable to analysis by SNA software. This data analysis often involves searching for occurrences of various subgraph patterns (i.e., graphical representations of entities and relationships). The authors have developed the Graph Matching Toolkit (GMT) which provides an intuitive Graphical User Interface (GUI) for a heuristic graph matching algorithm called the Truncated Search Tree (TruST) algorithm. GMT is a visual interface for graph matching algorithms processing large social networks. GMT enables an analyst to draw a subgraph pattern by using a mouse to select categories and labels for nodes and links from drop-down menus. GMT then executes the TruST algorithm to find the top five occurrences of the subgraph pattern within the social network stored in the database. GMT was tested using a simulated counter-insurgency dataset consisting of cellular phone communications within a populated area of operations in Iraq. The results indicated GMT (when executing the TruST graph matching algorithm) is a time-efficient approach to searching large social networks. GMT's visual interface to a graph matching algorithm enables intelligence analysts to quickly analyze and summarize the large amounts of data necessary to produce actionable intelligence.

  10. 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,

  11. Essential role of Sna41/Cdc45 in loading of DNA polymerase alpha onto minichromosome maintenance proteins in fission yeast.

    Science.gov (United States)

    Uchiyama, M; Griffiths, D; Arai, K; Masai, H

    2001-07-13

    Assembly of replication complexes at the replication origins is strictly regulated. Cdc45p is known to be a part of the active replication complexes. In Xenopus egg extracts, Cdc45p was shown to be required for loading of DNA polymerase alpha onto chromatin. The fission yeast cdc45 homologue was identified as a suppressor for nda4 and named sna41. Nevertheless, it is not known how Cdc45p facilitates loading of DNA polymerase alpha onto chromatin, particularly to prereplicative complexes. To gain novel insight into the function of this protein in fission yeast, we characterized the fission yeast Cdc45 homologue, Sna41p. We have constructed C-terminally epitope-tagged Sna41p and Pol alpha p and replaced the endogenous genes with the corresponding tagged genes. Analyses of protein-protein interactions in vivo by the use of these tagged strains revealed the following: Sna41p interacts with Pol alpha p throughout the cell cycle, whereas it interacts with Mis5p/Mcm6p in the chromatin fractions at the G(1)-S boundary through S phase. In an initiation-defective sna41 mutant, sna41(goa1), interaction of Pol alpha p with Mis5p is not observed, although Pol alpha p loading onto the chromatin that occurs before G(1) START is not affected. These results show that fission yeast Sna41p facilitates the loading of Pol alpha p onto minichromosome maintenance proteins. Our results are consistent with a model in which loading of Pol alpha p onto replication origins occurs through two steps, namely, loading onto chromatin at preSTART and association with prereplicative complexes at G(1)-S through Sna41p, which interacts with minichromosome maintenance proteins in a cell cycle-dependent manner.

  12. The Impacts of Network Centrality and Self-Regulation on an E-Learning Environment with the Support of Social Network Awareness

    Science.gov (United States)

    Lin, Jian-Wei; Huang, Hsieh-Hong; Chuang, Yuh-Shy

    2015-01-01

    An e-learning environment that supports social network awareness (SNA) is a highly effective means of increasing peer interaction and assisting student learning by raising awareness of social and learning contexts of peers. Network centrality profoundly impacts student learning in an SNA-related e-learning environment. Additionally,…

  13. Social Networks and Welfare in Future Animal Management.

    Science.gov (United States)

    Koene, Paul; Ipema, Bert

    2014-03-17

    It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

  14. 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

  15. Resilience to climate change in a cross-scale tourism governance context: a combined quantitative-qualitative network analysis

    Directory of Open Access Journals (Sweden)

    Tobias Luthe

    2016-03-01

    Full Text Available Social systems in mountain regions are exposed to a number of disturbances, such as climate change. Calls for conceptual and practical approaches on how to address climate change have been taken up in the literature. The resilience concept as a comprehensive theory-driven approach to address climate change has only recently increased in importance. Limited research has been undertaken concerning tourism and resilience from a network governance point of view. We analyze tourism supply chain networks with regard to resilience to climate change at the municipal governance scale of three Alpine villages. We compare these with a planned destination management organization (DMO as a governance entity of the same three municipalities on the regional scale. Network measures are analyzed via a quantitative social network analysis (SNA focusing on resilience from a tourism governance point of view. Results indicate higher resilience of the regional DMO because of a more flexible and diverse governance structure, more centralized steering of fast collective action, and improved innovative capacity, because of higher modularity and better core-periphery integration. Interpretations of quantitative results have been qualitatively validated by interviews and a workshop. We conclude that adaptation of tourism-dependent municipalities to gradual climate change should be dealt with at a regional governance scale and adaptation to sudden changes at a municipal scale. Overall, DMO building at a regional scale may enhance the resilience of tourism destinations, if the municipalities are well integrated.

  16. 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

  17. 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.

  18. 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

  19. 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.

  20. Structures and dynamics of transnational cooperation networks: evidence based on Local Action Groups in the Veneto Region, Italy

    Directory of Open Access Journals (Sweden)

    Elena Pisani

    2014-12-01

    Full Text Available The paper assesses the structures and dynamics of transnational cooperation projects promoted by Local Action Groups (LAGs in different periods (from LEADER II to LEADER Axis using Social Network Analysis (SNA in a specific case study: the Veneto Region in Italy. The classical indexes of SNA have been critically examined, and the paper also presents innovative indexes that can capture the peculiarity of transnational cooperation: disaggregated densities of the network and transnational centrality of the node. These indexes are useful in order to quantify how transnational a network actually is, and to measure the power-information that each actor (LAG can acquire through its transnational contacts. The methodology can become a tool for Managing Authorities to implement new forms of evaluation of transnational cooperation of LAGs.

  1. A Social Network Analysis of 140 Community-Academic Partnerships for Health: Examining the Healthier Wisconsin Partnership Program.

    Science.gov (United States)

    Franco, Zeno E; Ahmed, Syed M; Maurana, Cheryl A; DeFino, Mia C; Brewer, Devon D

    2015-08-01

    Social Network Analysis (SNA) provides an important, underutilized approach to evaluating Community Academic Partnerships for Health (CAPHs). This study examines administrative data from 140 CAPHs funded by the Healthier Wisconsin Partnership Program (HWPP). Funder data was normalized to maximize number of interconnections between funded projects and 318 non-redundant community partner organizations in a dual mode analysis, examining the period from 2003-2013.Two strategic planning periods, 2003-2008 vs. 2009-2014, allowed temporal comparison. Connectivity of the network was largely unchanged over time, with most projects and partner organizations connected to a single large component in both time periods. Inter-partner ties formed in HWPP projects were transient. Most community partners were only involved in projects during one strategic time period. Community organizations participating in both time periods were involved in significantly more projects during the first time period than partners participating in the first time period only (Cohen's d = 0.93). This approach represents a significant step toward using objective (non-survey) data for large clusters of health partnerships and has implications for translational science in community settings. Considerations for government, funders, and communities are offered. Examining partnerships within health priority areas, orphaned projects, and faculty ties to these networks are areas for future research. © 2015 Wiley Periodicals, Inc.

  2. 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.

  3. An Application of Social Network Analysis on Military Strategy, System Networks and the Phases of War

    Science.gov (United States)

    2015-03-26

    sociology and anthropology , SNA has become more mathematically formalized within the last few decades. Originally, SNA studied the interactions between... Evolutionary Algorithems: Classification, Analyses, and New Innovation, MS Thesis, AFIT/DS/ENG/99-01. School of Engineering and Management, Air

  4. 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.

  5. 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.

  6. Cost and Cost-Effectiveness of Students for Nutrition and eXercise (SNaX).

    Science.gov (United States)

    Ladapo, Joseph A; Bogart, Laura M; Klein, David J; Cowgill, Burton O; Uyeda, Kimberly; Binkle, David G; Stevens, Elizabeth R; Schuster, Mark A

    2016-04-01

    To examine the cost and cost-effectiveness of implementing Students for Nutrition and eXercise (SNaX), a 5-week middle school-based obesity-prevention intervention combining school-wide environmental changes, multimedia, encouragement to eat healthy school cafeteria foods, and peer-led education. Five intervention and 5 control middle schools (mean enrollment, 1520 students) from the Los Angeles Unified School District participated in a randomized controlled trial of SNaX. Acquisition costs for materials and time and wage data for employees involved in implementing the program were used to estimate fixed and variable costs. Cost-effectiveness was determined using the ratio of variable costs to program efficacy outcomes. The costs of implementing the program over 5 weeks were $5433.26 per school in fixed costs and $2.11 per student in variable costs, equaling a total cost of $8637.17 per school, or $0.23 per student per day. This investment yielded significant increases in the proportion of students served fruit and lunch and a significant decrease in the proportion of students buying snacks. The cost-effectiveness of the program, per student over 5 weeks, was $1.20 per additional fruit served during meals, $8.43 per additional full-priced lunch served, $2.11 per additional reduced-price/free lunch served, and $1.69 per reduction in snacks sold. SNaX demonstrated the feasibility and cost-effectiveness of a middle school-based obesity-prevention intervention combining school-wide environmental changes, multimedia, encouragement to eat healthy school cafeteria foods, and peer-led education. Its cost is modest and unlikely to be a significant barrier to adoption for many schools considering its implementation. Copyright © 2016 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

  7. 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...

  8. 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.

  9. 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...

  10. 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.

  11. Quantifying individual performance in Cricket — A network analysis of batsmen and bowlers

    Science.gov (United States)

    Mukherjee, Satyam

    2014-01-01

    Quantifying individual performance in the game of Cricket is critical for team selection in International matches. The number of runs scored by batsmen and wickets taken by bowlers serves as a natural way of quantifying the performance of a cricketer. Traditionally the batsmen and bowlers are rated on their batting or bowling average respectively. However, in a game like Cricket it is always important the manner in which one scores the runs or claims a wicket. Scoring runs against a strong bowling line-up or delivering a brilliant performance against a team with a strong batting line-up deserves more credit. A player’s average is not able to capture this aspect of the game. In this paper we present a refined method to quantify the ‘quality’ of runs scored by a batsman or wickets taken by a bowler. We explore the application of Social Network Analysis (SNA) to rate the players in a team performance. We generate a directed and weighted network of batsmen-bowlers using the player-vs-player information available for Test cricket and ODI cricket. Additionally we generate a network of batsmen and bowlers based on the dismissal record of batsmen in the history of cricket-Test (1877-2011) and ODI (1971-2011). Our results show that M. Muralitharan is the most successful bowler in the history of Cricket. Our approach could potentially be applied in domestic matches to judge a player’s performance which in turn paves the way for a balanced team selection for International matches.

  12. 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.

  13. Connections Among Communities: Preventing Radicalization and Violent Extremism Through Social Network Analysis in the Threat and Hazard Identification and Risk Assessment (THIRA) Framework

    Science.gov (United States)

    2016-12-01

    of Runaway Girls . .......................................9 Figure 2. A Network Representation of an Actor (Node...can be used to reduce the vulnerability of a community at risk of radicalization and violent extremism and to build resilience. Using literature ...risk of radicalization and violent extremism and to build resilience. Using literature that described core SNA principles and related fields of study

  14. 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.

  15. 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

  16. 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...

  17. 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.

  18. 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.

  19. Building Community Partnerships: Using Social Network Analysis to Strengthen Service Networks Supporting a South Carolina Program for Pregnant and Parenting Teens.

    Science.gov (United States)

    Radcliff, Elizabeth; Hale, Nathan; Browder, Jennifer; Cartledge, Claudia

    2017-09-01

    In 2013, South Carolina implemented a multi-year program providing support services for pregnant and parenting teens. Local lead sites were responsible for coordinating service delivery in partnership with other multidisciplinary community-based organizations. We used social network theory and analyses (SNA) to examine changes in partnerships over time. Using two-stage purposeful sampling, we identified three lead sites and their self-reported community partners. We administered two web-based surveys grounded in social network theory that included questions about partnership relationships and organizational characteristics. We calculated selected whole-network measures (size, cohesion, equity, diversity). Following the Year 1 surveys, we reviewed our findings with the lead sites and suggested opportunities to strengthen their respective partnerships. Following the Year 3 surveys, we observed changes across the networks. Survey response rates were 91.5% (43/47) in Year 1 and 68.2% (45/66) in Year 3. By Year 3, the average network size increased from 15.6 to 20.3 organizations. By Year 3, one lead site doubled its measure of network cohesion (connectedness); another lead site doubled in size (capacity). A third lead site, highly dense in Year 1, increased in size but decreased in cohesion by Year 3. Innovative use of SNA findings can help community partnerships identify gaps in capacity or services and organizations needed to fulfill program aims. SNA findings can also improve partnership function by identifying opportunities to improve connectedness or reduce redundancies in program work. The ability of lead sites to strategically reconfigure partnerships can be important to program success and sustainability.

  20. 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 ).

  1. 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...

  2. 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...

  3. 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.

  4. 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.

  5. 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…

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Towards Automatic Extraction of Social Networks of Organizations in PubMed Abstracts

    CERN Document Server

    Jonnalagadda, Siddhartha; Gonzalez, Graciela

    2010-01-01

    Social Network Analysis (SNA) of organizations can attract great interest from government agencies and scientists for its ability to boost translational research and accelerate the process of converting research to care. For SNA of a particular disease area, we need to identify the key research groups in that area by mining the affiliation information from PubMed. This not only involves recognizing the organization names in the affiliation string, but also resolving ambiguities to identify the article with a unique organization. We present here a process of normalization that involves clustering based on local sequence alignment metrics and local learning based on finding connected components. We demonstrate the application of the method by analyzing organizations involved in angiogenensis treatment, and demonstrating the utility of the results for researchers in the pharmaceutical and biotechnology industries or national funding agencies.

  13. 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...

  14. 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.

  15. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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/.

  1. 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.

  2. Who collaborates and why: Assessment and diagnostic of governance network integration for salmon restoration in Puget Sound, USA.

    Science.gov (United States)

    Sayles, Jesse S; Baggio, Jacopo A

    2017-01-15

    Governance silos are settings in which different organizations work in isolation and avoid sharing information and strategies. Siloes are a fundamental challenge for environmental planning and problem solving, which generally requires collaboration. Siloes can be overcome by creating governance networks. Studying the structure and function of these networks is important for understanding how to create institutional arrangements that can respond to the biophysical dynamics of a specific natural resource system (i.e., social-ecological, or institutional fit). Using the case of salmon restoration in a sub-basin of Puget Sound, USA, we assess network integration, considering three different reasons for network collaborations (i.e., mandated, funded, and shared interest relationships) and analyze how these different collaboration types relate to productivity based on practitioner's assessments. We also illustrate how specific and targeted network interventions might enhance the network. To do so, we use a mixed methods approach that combines quantitative social network analysis (SNA) and qualitative interview analysis. Overall, the sub-basin's governance network is fairly well integrated, but several concerning gaps exist. Funded, mandated, and shared interest relationships lead to different network patterns. Mandated relationships are associated with lower productivity than shared interest relationships, highlighting the benefit of genuine collaboration in collaborative watershed governance. Lastly, quantitative and qualitative data comparisons strengthen recent calls to incorporate geographic space and the role of individual actors versus organizational culture into natural resource governance research using SNA. Copyright © 2016 Elsevier Ltd. All rights reserved.

  3. 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.

  4. 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.

  5. Risks, prices, and positions: A social network analysis of illegal drug trafficking in the world-economy.

    Science.gov (United States)

    Boivin, Rémi

    2014-03-01

    Illegal drug prices are extremely high, compared to similar goods. There is, however, considerable variation in value depending on place, market level and type of drugs. A prominent framework for the study of illegal drugs is the "risks and prices" model (Reuter & Kleiman, 1986). Enforcement is seen as a "tax" added to the regular price. In this paper, it is argued that such economic models are not sufficient to explain price variations at country-level. Drug markets are analysed as global trade networks in which a country's position has an impact on various features, including illegal drug prices. This paper uses social network analysis (SNA) to explain price markups between pairs of countries involved in the trafficking of illegal drugs between 1998 and 2007. It aims to explore a simple question: why do prices increase between two countries? Using relational data from various international organizations, separate trade networks were built for cocaine, heroin and cannabis. Wholesale price markups are predicted with measures of supply, demand, risks of seizures, geographic distance and global positioning within the networks. Reported prices (in $US) and purchasing power parity-adjusted values are analysed. Drug prices increase more sharply when drugs are headed to countries where law enforcement imposes higher costs on traffickers. The position and role of a country in global drug markets are also closely associated with the value of drugs. Price markups are lower if the destination country is a transit to large potential markets. Furthermore, price markups for cocaine and heroin are more pronounced when drugs are exported to countries that are better positioned in the legitimate world-economy, suggesting that relations in legal and illegal markets are directed in opposite directions. Consistent with the world-system perspective, evidence is found of coherent world drug markets driven by both local realities and international relations. Copyright © 2013 Elsevier B

  6. SNaX: A Database of Supernova X-Ray Light Curves

    Science.gov (United States)

    Ross, Mathias; Dwarkadas, Vikram V.

    2017-06-01

    We present the Supernova X-ray Database (SNaX), a compilation of the X-ray data from young supernovae (SNe). The database includes the X-ray fluxes and luminosities of young SNe, from days to years after outburst. The original goal and intent of this study was to present a database of Type IIn SNe (SNe IIn), which we have accomplished. Our ongoing goal is to expand the database to include all SNe for which published data are available. The database interface allows one to search for SNe using various criteria, plot all or selected data points, and download both the data and the plot. The plotting facility allows for significant customization. There is also a facility for the user to submit data that can be directly incorporated into the database. We include an option to fit the decay of any given SN light curve with a power-law. The database includes a conversion of most data points to a common 0.3-8 keV band so that SN light curves may be directly compared with each other. A mailing list has been set up to disseminate information about the database. We outline the structure and function of the database, describe its various features, and outline the plans for future expansion.

  7. Towards a More Holistic Stakeholder Analysis Approach

    DEFF Research Database (Denmark)

    Sedereviciute, Kristina; Valentini, Chiara

    2011-01-01

    in finding stakeholders on new environments (social media), where connectivity and relationships play a key role. The argument stems from the need to assess stakeholder presence beyond the dyadic ties. Consequently, the combination of the Stakeholder Salience Model (SSM) and social network analysis (SNA......) is proposed as a more holistic solution for stakeholder identification including those from social media. A process of finding “unknown” but important stakeholders from social media was identified incorporating the content search and the principles of SNA. Consequently, stakeholders from social media...... are identified based on the dimensions of connectivity and the content shared. Accordingly, the study introduces four groups of important actors from social media: unconcerned lurkers, unconcerned influencers, concerned lurkers and concerned influencers and integrates them into the existing Stakeholder Salience...

  8. 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...

  9. 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).

  10. 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....

  11. 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.

  12. 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.

  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. 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

  15. 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...

  16. Using NetMaster to manage IBM networks

    Science.gov (United States)

    Ginsburg, Guss

    1991-01-01

    After defining a network and conveying its importance to support the activities at the JSC, the need for network management based on the size and complexity of the IBM SNA network at JSC is demonstrated. Network Management consists of being aware of component status and the ability to control resources to meet the availability and service needs of users. The concerns of the user are addressed as well as those of the staff responsible for managing the network. It is explained how NetMaster (a network management system for managing SNA networks) is used to enhance reliability and maximize service to SNA network users through automated procedures. The following areas are discussed: customization, problem and configuration management, and system measurement applications of NetMaster. Also, several examples are given that demonstrate NetMaster's ability to manage and control the network, integrate various product functions, as well as provide useful management information.

  17. 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.

  18. 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.

  19. 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...

  20. 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...

  1. 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.

  2. 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...

  3. 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.

  4. 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 ...

  5. 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

  6. 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...

  7. 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.

  8. 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

  9. 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.

  10. 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

  11. 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....

  12. What's in a name generator? Choosing the right name generators for social network surveys in healthcare quality and safety research.

    Science.gov (United States)

    Burt, Ronald S; Meltzer, David O; Seid, Michael; Borgert, Amy; Chung, Jeanette W; Colletti, Richard B; Dellal, George; Kahn, Stacy A; Kaplan, Heather C; Peterson, Laura E; Margolis, Peter

    2012-12-01

    Interest in the use of social network analysis (SNA) in healthcare research has increased, but there has been little methodological research on how to choose the name generators that are often used to collect primary data on the social connection between individuals for SNA. We sought to determine a minimum set of name generators sufficient to distinguish the social networks of a target population of physicians active in quality improvement (QI). We conducted a pilot survey including 8 name generators in a convenience sample of 25 physicians active in QI to characterize their social networks. We used multidimensional scaling to determine what subset of these name generators was needed to distinguish these social networks. We found that some physicians maintain a social network organized around a specific colleague who performed multiple roles while others maintained highly differentiated networks. We found that a set of 5 of the 8 name generators we used was needed to distinguish the networks of these physicians. Beyond methodology for selecting name generators, our findings suggest that QI networks may require 5 or more generators to elicit valid sets of relevant actors and relations in this target population.

  13. 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.

  14. 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.

  15. 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.

  16. 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...

  17. 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.

  18. 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.

  19. 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.

  20. Gender differences in collaborative learning over online social networks: Epistemological beliefs and behaviors

    Directory of Open Access Journals (Sweden)

    Rosanna Y.-Y. Chan

    2013-09-01

    Full Text Available Online social networks are popular venues for computer-supported collaborative work and computer-supported collaborative learning. Professionals within the same discipline, such as software developers, often interact over various social network sites for knowledge updates and collective understandings. The current study aims at gathering empirical evidences concerning gender differences in online social network beliefs and behaviors. A total of 53 engineering postgraduate students were engaged in a blogging community for collaborative learning. Participants’ beliefs about collaboration and nature of knowledge and knowing (i.e. epistemological beliefs are investigated. More specifically, social network analysis metrics including in-degree, out-degree, closeness centrality, and betweenness centrality are obtained from an 8-interval longitudinal SNA. Methodologically speaking, the current work puts forward mixed methods of longitudinal SNA and quantitative beliefs survey to explore online social network participants’ beliefs and behaviors. The study’s findings demonstrate significant gender differences in collaborative learning through online social networks, including (1 female engineering postgraduate students engage significantly more actively in online communications, (2 male engineering postgraduate students are more likely to be the potential controllers of information flows, and (3 gender differences exist in belief gains related to social aspects, but not individual's epistemic aspects. Overall, participants in both genders demonstrated enhanced beliefs in collaboration as well as the nature of knowledge and knowing.

  1. Introduction to stream network habitat analysis

    Science.gov (United States)

    Bartholow, John M.; Waddle, Terry J.

    1986-01-01

    Increasing demands on stream resources by a variety of users have resulted in an increased emphasis on studies that evaluate the cumulative effects of basinwide water management programs. Network habitat analysis refers to the evaluation of an entire river basin (or network) by predicting its habitat response to alternative management regimes. The analysis principally focuses on the biological and hydrological components of the riv er basin, which include both micro- and macrohabitat. (The terms micro- and macrohabitat are further defined and discussed later in this document.) Both conceptual and analytic models are frequently used for simplifying and integrating the various components of the basin. The model predictions can be used in developing management recommendations to preserve, restore, or enhance instream fish habitat. A network habitat analysis should begin with a clear and concise statement of the study objectives and a thorough understanding of the institutional setting in which the study results will be applied. This includes the legal, social, and political considerations inherent in any water management setting. The institutional environment may dictate the focus and level of detail required of the study to a far greater extent than the technical considerations. After the study objectives, including species on interest, and institutional setting are collectively defined, the technical aspects should be scoped to determine the spatial and temporal requirements of the analysis. A macro level approach should be taken first to identify critical biological elements and requirements. Next, habitat availability is quantified much as in a "standard" river segment analysis, with the likely incorporation of some macrohabitat components, such as stream temperature. Individual river segments may be aggregated to represent the networkwide habitat response of alternative water management schemes. Things learned about problems caused or opportunities generated may

  2. 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.

  3. 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.

  4. 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 ...

  5. Cellular Interactions and Immune Response of Spherical Nucleic Acid (SNA) Nanoconjugates

    Science.gov (United States)

    Massich, Matthew David

    Spherical nucleic acid (SNA) nanoconjugates consist of a densely packed monolayer shell of highly-oriented oligonucleotides covalently bound to a gold nanoparticle core. The nanoconjugates exhibit several important qualities, which make them useful for various biological applications, such as antisense gene regulation strategies and the intracellular detection of biomolecules. The focus of this thesis was to characterize the nanoconjugates interaction with cultured cells and specifically the immune response to their intracellular presence. The immune response of macrophage cells to internalized nanoconjugates was studied, and due to the dense functionalization of oligonucleotides on the surface of the nanoparticle and the resulting high localized salt concentration the innate immune response to the nanoconjugates is ˜25-fold less when compared to a lipoplex carrying the same sequence. Additionally, genome-wide expression profiling was used to study the biological response of cultured cells to the nanoconjugates. The biological response of HeLa cells to gold nanoparticles stabilized by weakly bound ligands was significant, yet when these same nanoparticles were stably functionalized with covalently attached oligonucleotides the cells showed no measurable response. In human keratinocytes, the oligonucleotide sequences caused 427 genes to be differentially expressed when complexed with Dharmafect, but when the oligonucleotides were conjugated to nanoparticles only 7 genes were differentially expressed. Beyond characterizing the cellular interactions and immune response of the nanoconjugates, the optimal length of siRNA (from 19--34 base pairs) that induces the most gene knockdown while maintaining limited immune activation was determined to be 24 base pairs. Further, the SNAs were shown to be useful as a potential antiviral gene therapy by demonstrating approximately 50% knockdown of the Ebola VP35 gene. Lastly, a scanning probe-enabled method was used to rapidly

  6. 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.

  7. 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.

  8. Prototype Packages for Managing and Animating Longitudinal Network Data: dynamicnetwork and rSoNIA

    Directory of Open Access Journals (Sweden)

    Skye Bender-deMoll

    2007-12-01

    Full Text Available Work with longitudinal network survey data and the dynamic network outputs of the statnet ERGMs has demonstrated the need for consistent frameworks and data structures for expressing, storing, and manipulating information about networks that change in time. Motivated by our requirements for exchanging data among researchers and various analysis and visualization processes, we have created an R package dynamicnetwork that builds upon previous work in the network, statnet and sna packages and provides a limited functional implementation. This paper discusses design issues and considerations, describes classes and forms of dynamic data, and works through several examples to demonstrate the utility of the package. The functionality of the rSoNIA package that uses dynamicnetwork to exchange data with the Social Network Image Animator (SoNIA software to create animated movies of changing networks from within R is also demonstrated.

  9. Network effects on scientific collaborations.

    Directory of Open Access Journals (Sweden)

    Shahadat Uddin

    Full Text Available BACKGROUND: The analysis of co-authorship network aims at exploring the impact of network structure on the outcome of scientific collaborations and research publications. However, little is known about what network properties are associated with authors who have increased number of joint publications and are being cited highly. METHODOLOGY/PRINCIPAL FINDINGS: Measures of social network analysis, for example network centrality and tie strength, have been utilized extensively in current co-authorship literature to explore different behavioural patterns of co-authorship networks. Using three SNA measures (i.e., degree centrality, closeness centrality and betweenness centrality, we explore scientific collaboration networks to understand factors influencing performance (i.e., citation count and formation (tie strength between authors of such networks. A citation count is the number of times an article is cited by other articles. We use co-authorship dataset of the research field of 'steel structure' for the year 2005 to 2009. To measure the strength of scientific collaboration between two authors, we consider the number of articles co-authored by them. In this study, we examine how citation count of a scientific publication is influenced by different centrality measures of its co-author(s in a co-authorship network. We further analyze the impact of the network positions of authors on the strength of their scientific collaborations. We use both correlation and regression methods for data analysis leading to statistical validation. We identify that citation count of a research article is positively correlated with the degree centrality and betweenness centrality values of its co-author(s. Also, we reveal that degree centrality and betweenness centrality values of authors in a co-authorship network are positively correlated with the strength of their scientific collaborations. CONCLUSIONS/SIGNIFICANCE: Authors' network positions in co

  10. 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…

  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. Exploring social networks of municipal science education stakeholders in Danish Science Municipalities

    DEFF Research Database (Denmark)

    von der Fehr, Ane

    development of science education. By use of social network analysis (SNA), four MSE networks were approached empirically, and the municipal stakeholders and the relationships connecting them were mapped. The central stakeholders were identified based on quantitative network data. Through qualitative...... interviews it was possible to explore how they affected the development. The analysis showed that their positions in the MSE networks enabled them to actualise resources among relevant stakeholders for use in science education development and in this way they contributed to social capital in MSE networks......Science education development is a field of many interests and a key interest is recruitment of students who wish to pursue an education in science. This is an urgent societal demand in Denmark as well as internationally, since highly skilled science graduates are needed for the continuous...

  13. 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.

  14. 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.

  15. 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.

  16. 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 ...

  17. 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.

  18. 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...

  19. 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...

  20. 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.

  1. 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 ...

  2. 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.

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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 ...

  8. 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 ...

  9. 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....

  10. Identifying changes in the support networks of end-of-life carers using social network analysis.

    Science.gov (United States)

    Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie

    2015-06-01

    End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  11. Modelling the public opinion transmission on social networks under opinion leaders

    Science.gov (United States)

    Li, Zuozhi; Li, Meng; Ji, Wanwan

    2017-06-01

    In this paper, based on Social Network Analysis (SNA), the social network model of opinion leaders influencing the public opinion transmission is explored. The hot event, A Female Driver Was Beaten Due To Lane Change, has characteristics of individual short-term and non-government intervention, which is used to data extraction, and formed of the network structure on opinion leaders influencing the public opinion transmission. And the evolution mechanism are analyzed in the three evolutionary situations. Opinion leaders influence micro-blogging public opinion on social network evolution model shows that this type of network public opinion transmission is largely constrained by opinion leaders, so the opinion leaders behavior supervising on the spread of this public opinion is pivotal, and which has a guiding significance.

  12. 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…

  13. Spectral Analysis Methods of Social Networks

    Directory of Open Access Journals (Sweden)

    P. G. Klyucharev

    2017-01-01

    Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work

  14. 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.

  15. Co-occurrence network analysis of Chinese and English poems

    Science.gov (United States)

    Liang, Wei; Wang, Yanli; Shi, Yuming; Chen, Guanrong

    2015-02-01

    A total of 572 co-occurrence networks of Chinese characters and words as well as English words are constructed from both Chinese and English poems. It is found that most of the networks have small-world features; more Chinese networks have scale-free properties and hierarchical structures as compared with the English networks; all the networks are disassortative, and the disassortativeness of the Chinese word networks is more prominent than those of the English networks; the spectral densities of the Chinese word networks and English networks are similar, but they are different from those of the ER, BA, and WS networks. For the above observed phenomena, analysis is provided with interpretation from a linguistic perspective.

  16. Comparative analysis of quantitative efficiency evaluation methods for transportation networks.

    Science.gov (United States)

    He, Yuxin; Qin, Jin; Hong, Jian

    2017-01-01

    An effective evaluation of transportation network efficiency could offer guidance for the optimal control of urban traffic. Based on the introduction and related mathematical analysis of three quantitative evaluation methods for transportation network efficiency, this paper compares the information measured by them, including network structure, traffic demand, travel choice behavior and other factors which affect network efficiency. Accordingly, the applicability of various evaluation methods is discussed. Through analyzing different transportation network examples it is obtained that Q-H method could reflect the influence of network structure, traffic demand and user route choice behavior on transportation network efficiency well. In addition, the transportation network efficiency measured by this method and Braess's Paradox can be explained with each other, which indicates a better evaluation of the real operation condition of transportation network. Through the analysis of the network efficiency calculated by Q-H method, it can also be drawn that a specific appropriate demand is existed to a given transportation network. Meanwhile, under the fixed demand, both the critical network structure that guarantees the stability and the basic operation of the network and a specific network structure contributing to the largest value of the transportation network efficiency can be identified.

  17. Network Characteristics of Successful Performance in Association Football. A Study on the UEFA Champions League

    Directory of Open Access Journals (Sweden)

    Tiago J. Pina

    2017-07-01

    Full Text Available The synergistic interaction between teammates in association football has properties that can be captured by Social Network Analysis (SNA. The analysis of networks formed by team players passing a ball in a match shows that team success is correlated with high network density and clustering coefficient, as well as with reduced network centralization. However, oversimplification needs to be avoided, as network metrics events associated with success should not be considered equally to those that are not. In the present study, we investigated whether network density, clustering coefficient and centralization can predict successful or unsuccessful team performance. We analyzed 12 games of the Group Stage of UEFA Champions League 2015/2016 Group C by using public records from TV broadcasts. Notational analyses were performed to categorize attacking sequences as successful or unsuccessful, and to collect data on the ball-passing networks. The network metrics were then computed. A hierarchical logistic-regression model was used to predict the successfulness of the offensive plays from network density, clustering coefficient and centralization, after controlling for the effect of total passes on successfulness of offensive plays. Results confirmed the independent effect of network metrics. Density, but not clustering coefficient or centralization, was a significant predictor of the successfulness of offensive plays. We found a negative relation between density and successfulness of offensive plays. However, reduced density was associated with a higher number of offensive plays, albeit mostly unsuccessful. Conversely, high density was associated with a lower number of successful offensive plays (SOPs, but also with overall fewer offensive plays and “ball possession losses” before the attacking team entered the finishing zone. Independent SNA of team performance is important to minimize the limitations of oversimplifying effective team synergies.

  18. Analysis and monitoring design for networks

    Energy Technology Data Exchange (ETDEWEB)

    Fedorov, V.; Flanagan, D.; Rowan, T.; Batsell, S.

    1998-06-01

    The idea of applying experimental design methodologies to develop monitoring systems for computer networks is relatively novel even though it was applied in other areas such as meteorology, seismology, and transportation. One objective of a monitoring system should always be to collect as little data as necessary to be able to monitor specific parameters of the system with respect to assigned targets and objectives. This implies a purposeful monitoring where each piece of data has a reason to be collected and stored for future use. When a computer network system as large and complex as the Internet is the monitoring subject, providing an optimal and parsimonious observing system becomes even more important. Many data collection decisions must be made by the developers of a monitoring system. These decisions include but are not limited to the following: (1) The type data collection hardware and software instruments to be used; (2) How to minimize interruption of regular network activities during data collection; (3) Quantification of the objectives and the formulation of optimality criteria; (4) The placement of data collection hardware and software devices; (5) The amount of data to be collected in a given time period, how large a subset of the available data to collect during the period, the length of the period, and the frequency of data collection; (6) The determination of the data to be collected (for instance, selection of response and explanatory variables); (7) Which data will be retained and how long (i.e., data storage and retention issues); and (8) The cost analysis of experiments. Mathematical statistics, and, in particular, optimal experimental design methods, may be used to address the majority of problems generated by 3--7. In this study, the authors focus their efforts on topics 3--5.

  19. Rainwater Harvesting and Social Networks: Visualising Interactions for Niche Governance, Resilience and Sustainability

    Directory of Open Access Journals (Sweden)

    Sarah Ward

    2016-11-01

    Full Text Available Visualising interactions across urban water systems to explore transition and change processes requires the development of methods and models at different scales. This paper contributes a model representing the network interactions of rainwater harvesting (RWH infrastructure innovators and other organisations in the UK RWH niche to identify how resilience and sustainability feature within niche governance in practice. The RWH network interaction model was constructed using a modified participatory social network analysis (SNA. The SNA was further analysed through the application of a two-part analytical framework based on niche management and the safe, resilient and sustainable (‘Safe and SuRe’ framework. Weak interactions between some RWH infrastructure innovators and other organisations highlighted reliance on a limited number of persuaders to influence the regime and landscape, which were underrepresented. Features from niche creation and management were exhibited by the RWH network interaction model, though some observed characteristics were not represented. Additional Safe and SuRe features were identified covering diverse innovation, responsivity, no protection, unconverged expectations, primary influencers, polycentric or adaptive governance and multiple learning-types. These features enable RWH infrastructure innovators and other organisations to reflect on improving resilience and sustainability, though further research in other sectors would be useful to verify and validate observation of the seven features.

  20. 6th International Conference on Network Analysis

    CERN Document Server

    Nikolaev, Alexey; Pardalos, Panos; Prokopyev, Oleg

    2017-01-01

    This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and human brain networks are presented. Chapters in this book cover the following topics: Linear max min fairness Heuristic approaches for high-quality solutions Efficient approaches for complex multi-criteria optimization problems Comparison of heuristic algorithms New heuristic iterative local search Power in network structures Clustering nodes in random graphs Power transmission grid structure Network decomposition problems Homogeneity hypothesis testing Network analy...

  1. Quantitative methods for ecological network analysis.

    Science.gov (United States)

    Ulanowicz, Robert E

    2004-12-01

    The analysis of networks of ecological trophic transfers is a useful complement to simulation modeling in the quest for understanding whole-ecosystem dynamics. Trophic networks can be studied in quantitative and systematic fashion at several levels. Indirect relationships between any two individual taxa in an ecosystem, which often differ in either nature or magnitude from their direct influences, can be assayed using techniques from linear algebra. The same mathematics can also be employed to ascertain where along the trophic continuum any individual taxon is operating, or to map the web of connections into a virtual linear chain that summarizes trophodynamic performance by the system. Backtracking algorithms with pruning have been written which identify pathways for the recycle of materials and energy within the system. The pattern of such cycling often reveals modes of control or types of functions exhibited by various groups of taxa. The performance of the system as a whole at processing material and energy can be quantified using information theory. In particular, the complexity of process interactions can be parsed into separate terms that distinguish organized, efficient performance from the capacity for further development and recovery from disturbance. Finally, the sensitivities of the information-theoretic system indices appear to identify the dynamical bottlenecks in ecosystem functioning.

  2. The Impact of a Researcher's Structural Position on Scientific Performance: An Empirical Analysis.

    Science.gov (United States)

    Contandriopoulos, Damien; Duhoux, Arnaud; Larouche, Catherine; Perroux, Mélanie

    2016-01-01

    This article discusses the nature and structure of scientific collaboration as well as the association between academic collaboration networks and scientific productivity. Based on empirical data gathered from the CVs of 73 researchers affiliated with an academic research network in Canada, this study used social network analysis (SNA) to examine the association between researchers' structural position in the network and their scientific performance. With reference to Granovetter's and Burt's theories on weak ties and structural holes, we argue it is the bridging position a researcher holds in a scientific network that matters most to improve scientific performance. The results of correlation scores between network centrality and two different indicators of scientific performance indicate there is a robust association between researchers' structural position in collaboration networks and their scientific performance. We believe this finding, and the method we have developed, could have implications for the way research networks are managed and researchers are supported.

  3. The Impact of a Researcher's Structural Position on Scientific Performance: An Empirical Analysis.

    Directory of Open Access Journals (Sweden)

    Damien Contandriopoulos

    Full Text Available This article discusses the nature and structure of scientific collaboration as well as the association between academic collaboration networks and scientific productivity. Based on empirical data gathered from the CVs of 73 researchers affiliated with an academic research network in Canada, this study used social network analysis (SNA to examine the association between researchers' structural position in the network and their scientific performance. With reference to Granovetter's and Burt's theories on weak ties and structural holes, we argue it is the bridging position a researcher holds in a scientific network that matters most to improve scientific performance. The results of correlation scores between network centrality and two different indicators of scientific performance indicate there is a robust association between researchers' structural position in collaboration networks and their scientific performance. We believe this finding, and the method we have developed, could have implications for the way research networks are managed and researchers are supported.

  4. Dynamic analysis of biochemical network using complex network method

    Directory of Open Access Journals (Sweden)

    Wang Shuqiang

    2015-01-01

    Full Text Available In this study, the stochastic biochemical reaction model is proposed based on the law of mass action and complex network theory. The dynamics of biochemical reaction system is presented as a set of non-linear differential equations and analyzed at the molecular-scale. Given the initial state and the evolution rules of the biochemical reaction system, the system can achieve homeostasis. Compared with random graph, the biochemical reaction network has larger information capacity and is more efficient in information transmission. This is consistent with theory of evolution.

  5. 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

  6. 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

  7. Analysis of Social Network Measures with Respect to Structural Properties of Networks

    Science.gov (United States)

    2012-03-01

    many researches who used SNA to study everything from friendships to the spread of diseases. 6 In the 1960s, psychologist, Stanley Milgram ...the average number of people it took to get from any one person to another (Newman, 2010, p. 55). In his experiment, Milgram mailed out 96 packages...conclusion of the experiment, Milgram observed (out of the 18 passports that made it to their target) that on average there were about six people

  8. Analysis of Computer Network Information Based on "Big Data"

    Science.gov (United States)

    Li, Tianli

    2017-11-01

    With the development of the current era, computer network and large data gradually become part of the people's life, people use the computer to provide convenience for their own life, but at the same time there are many network information problems has to pay attention. This paper analyzes the information security of computer network based on "big data" analysis, and puts forward some solutions.

  9. Road Transport Network Analysis In Port-Harcourt Metropolics ...

    African Journals Online (AJOL)

    Road transport network contributes to the economy of an area as it connects points of origin to destinations. The thrust of this article therefore, is on the analysis of the road networks in Port – Harcourt metropolis with the aim of determining the connectivity of the road networks and the most accessible node. Consequently ...

  10. Neural network analysis of varying trends in real exchange rates

    NARCIS (Netherlands)

    J.F. Kaashoek (Johan); H.K. van Dijk (Herman)

    1999-01-01

    textabstractIn this paper neural networks are fitted to the real exchange rates of seven industrialized countries. The size and topology of the used networks is found by reducing the size of the network through the use of multiple correlation coefficients, principal component analysis of residuals

  11. 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."

  12. Co-occurrence network analysis of modern Chinese poems

    Science.gov (United States)

    Liang, Wei; Wang, Yanli; Shi, Yuming; Chen, Guanrong

    2015-02-01

    A total of 606 co-occurrence networks of Chinese characters and words are constructed from rhymes, free verses, and prose poems. It is found that 98.5 % of networks have scale-free properties, while 19.8 % of networks do not have small-world features, especially the clustering coefficients in 5.6 % of networks are zero. In addition, 61.4 % of networks have significant hierarchical structures, and 98 % of networks are disassortative. For the above observed phenomena, analysis is provided with interpretation from a linguistic perspective.

  13. Effects of Pre-Purchase Search Motivation on User Attitudes toward Online Social Network Advertising: A Case of University Students

    Directory of Open Access Journals (Sweden)

    Imran A Mir

    2014-06-01

    Full Text Available Since last few years, social media have profoundly changed the ways of social and business communication. Particularly, social network sites (SNSs have rapidly grown in popularity and number of users globally. They have become the main place for social interaction, discussion and communication. Today, businesses of various types use SNSs for commercial communication. Banner advertising is one of the common methods of commercial communication on SNSs. Advertising is a key source of revenue for many SNSs firms such as Facebook. In fact, the existence of many SNSs owners and advertisers is contingent upon the success of social network advertising (SNA. Users demand free SNS services which makes SNA crucial for SNSs firms. SNA can be effective only if it is aligned with user motivations. Marketing literature identifies pre-purchase search as a primary consumer motivation for using media. The current study aims to identify the effects of pre-purchase search motivation (PSM on user attitudes toward SNA. It also assesses the association between the attitudes toward SNA and users’ banner ad-clicking behavior on SNSs. Data was gathered from 200 university students in Islamabad using offline survey. Results show positive effects of PSM on user attitudes toward SNA. They also show positive association between user attitudes toward SNA and their SNS banner ad-clicking behavior. The firms which promote their products through SNSs to the young South Asian consumers may benefit from the findings of the current study.

  14. Complex Network Analysis of Brazilian Power Grid

    CERN Document Server

    Martins, Gabriela C; Ribeiro, Fabiano L; Forgerini, Fabricio L

    2016-01-01

    Power Grids and other delivery networks has been attracted some attention by the network literature last decades. Despite the Power Grids dynamics has been controlled by computer systems and human operators, the static features of this type of network can be studied and analyzed. The topology of the Brazilian Power Grid (BPG) was studied in this work. We obtained the spatial structure of the BPG from the ONS (electric systems national operator), consisting of high-voltage transmission lines, generating stations and substations. The local low-voltage substations and local power delivery as well the dynamic features of the network were neglected. We analyze the complex network of the BPG and identify the main topological information, such as the mean degree, the degree distribution, the network size and the clustering coefficient to caracterize the complex network. We also detected the critical locations on the network and, therefore, the more susceptible points to lead to a cascading failure and even to a blac...

  15. Using SNA to map participation and non-participation in vulnerable populations

    DEFF Research Database (Denmark)

    Hindhede, Anette Lykke

    investigation of social networks in a deprived area, the study aimed at identifying social networks of residents who participated in various community-based activities as well as informal groups. Fisher’s (1982) theoretical definition of relation was used and a scheme for coding respondents on the adequacy......The pursuit of equality in health is an overriding goal and principle in Danish health policy. Inequality in health prevails especially among population groups with low education and income levels. Many municipalities have therefore been focusing on deprived areas attempting to fight inequality...

  16. 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.

  17. 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

  18. Synchronization analysis of coloured delayed networks under ...

    Indian Academy of Sciences (India)

    This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...

  19. Spectral Modelling for Spatial Network Analysis

    NARCIS (Netherlands)

    Nourian, P.; Rezvani, S.; Sariyildiz, I.S.; van der Hoeven, F.D.; Attar, Ramtin; Chronis, Angelos; Hanna, Sean; Turrin, Michela

    2016-01-01

    Spatial Networks represent the connectivity structure between units of space as a weighted graph whose links are weighted as to the strength of connections. In case of urban spatial networks, the units of space correspond closely to streets and in architectural spatial networks the units correspond

  20. 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.

  1. First-principles study of p-type ZnO by S-Na co-doping

    Science.gov (United States)

    Tan, Xingyi; Li, Qiang; Zhu, Yongdan

    2017-08-01

    Using the first-principles method based on the density functional theory, the formation energy, electronic structures of S-Na co-doping in ZnO were calculated. The calculated results show that NaZn-SO have smaller formation energy than Nain-SO in energy ranges from -3.10 to 0 eV of {μ }{{O}}, indicating that it opens up a new opportunity for growth the p-type ZnO. The band structure shows that the NaZn system is a p-type direct-band-gap semiconductor material and the calculated band gap (0.84 eV) is larger than pure ZnO (0.74 eV). The NaZn-SO system is also a p-type semiconductor material with a direct band gap (0.80 eV). The influence of S-Na co-doping in ZnO on p-type conductivity is also discussed. The effective masses of NaZn-SO are larger than effective masses of NaZn and the NaZn-SO have more hole carriers than NaZn, meaning the hole in the NaZn-SO system may have a better carrier transfer character. So we inferred that NaZn-SO should be a candidate of p-type conduction. Project supported by the Natural Science Foundation of Hubei Province, China (Nos. 2014CFB342, 2014CFB619) and the Doctoral Foundation for Scientific Research of Hubei University for Nationalities (No. MY2013B020).

  2. Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

    Science.gov (United States)

    Chernoded, Andrey; Dudko, Lev; Myagkov, Igor; Volkov, Petr

    2017-10-01

    Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

  3. Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis

    Directory of Open Access Journals (Sweden)

    Chernoded Andrey

    2017-01-01

    Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.

  4. Privacy Breach Analysis in Social Networks

    Science.gov (United States)

    Nagle, Frank

    This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

  5. Measuring the Influence of Efficient Ports using Social Network Metrics

    Directory of Open Access Journals (Sweden)

    Byung-Hak Leem

    2015-02-01

    Full Text Available Data envelopment analysis (DEA is known as a useful tool that produces many efficient decision-making units (DMUs. Traditional DEA provides relative efficient scores and reference sets, but does not influence and rank the efficient DMUs. This paper suggests a method that provides influence and ranking information by using PageRank as a centrality of Social Network analysis (SNA based on reference sets and their lambda values. The social network structure expresses the DMU as a node, reference sets as link, and lambda as connection strengths or weights. This paper, with PageRank, compares the Eigenvector centrality suggested by Liu, et al. in 2009, and shows that PageRank centrality is more accurate.

  6. Network Governance of the Commons

    Directory of Open Access Journals (Sweden)

    Lars Gunnar Carlsson

    2007-11-01

    Full Text Available The survival of the commons is closely associated with the potential to find ways to strengthen contemporary management systems, making them more responsive to a number of complexities, like the dynamics of ecosystems and related, but often fragmented, institutions. A discussion on the desirability of finding ways to establish so-called cross-scale linkages has recently been vitalised in the literature. In the same vein, concepts like adaptive management, co-management and adaptive co-management have been discussed. In essence, these ways of organizing management incorporate an implicit assumption about the establishment of social networks and is more closely related to network governance and social network theory, than to political administrative hierarchy. However, so far, attempts to incorporate social network analysis (SNA in this literature have been rather few, and not particularly elaborate. In this paper, a framework for such an approach will be presented. The framework provides an analytical skeleton for the understanding of joint management and the establishment of cross-scale linkages. The relationships between structural network properties - like density, centrality and heterogeneity - and innovation in adaptive co-management systems are highlighted as important to consider when crafting institutions for natural resource management. The paper makes a theoretical and methodological contribution to the understanding of co-management, and thereby to the survival of the commons.

  7. Network analysis and synthesis a modern systems theory approach

    CERN Document Server

    Anderson, Brian D O

    2006-01-01

    Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations

  8. Sensor Network Information Analytical Methods: Analysis of Similarities and Differences

    Directory of Open Access Journals (Sweden)

    Chen Jian

    2014-04-01

    Full Text Available In the Sensor Network information engineering literature, few references focus on the definition and design of Sensor Network information analytical methods. Among those that do are Munson, et al. and the ISO standards on functional size analysis. To avoid inconsistent vocabulary and potentially incorrect interpretation of data, Sensor Network information analytical methods must be better designed, including definitions, analysis principles, analysis rules, and base units. This paper analyzes the similarities and differences across three different views of analytical methods, and uses a process proposed for the design of Sensor Network information analytical methods to analyze two examples of such methods selected from the literature.

  9. State of the art applications of social network analysis

    CERN Document Server

    Can, Fazli; Polat, Faruk

    2014-01-01

    Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user

  10. Investigating communication networks contextually: Qualitative network analysis as cross-media research

    Directory of Open Access Journals (Sweden)

    Andreas Hepp

    2016-06-01

    Full Text Available This article introduces the approach of contextualised communication network analysis as a qualitative procedure for researching communicative relationships realised through the media. It combines qualitative interviews on media appropriation, egocentric network maps, and media diaries. Through the triangulation of these methods of data collection, it is possible to gain a differentiated insight into the specific meanings, structures and processes of communication networks across a variety of media. The approach is illustrated using a recent study dealing with the mediatisation of community building among young people. In this context, the qualitative communication network analysis has been applied to distinguish “localists” from “centrists”, “multilocalists”, and “pluralists”. These different “horizons of mediatised communitisation” are connected to distinct communication networks. Since this involves today a variety of different media, the contextual analysis of communication networks necessarily has to imply a cross-media perspective.

  11. A window on emergent European social network analysis

    OpenAIRE

    Cronin, Bruce

    2011-01-01

    This paper introduces the collection of papers in this issue, providing context in the recent development of social network analysis in Europe and the catalytic contributions of the Essex University Summer School and latterly the UK Social Networks Association. While these organisations have provided important focuses for social network analysis in the UK their reach has been much broader, principally among graduate students across Europe and the emergent research agenda they are forging. Fiv...

  12. 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.

  13. Statistical Network Analysis for Functional MRI: Mean Networks and Group Comparisons.

    Directory of Open Access Journals (Sweden)

    Cedric E Ginestet

    2014-05-01

    Full Text Available Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i the construction of summary networks, such as how to compute and visualize the mean network from a sample of network-valued data points; and (ii how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN, or by directly computing the mean network, provided that a metric has been specified on the space of all networks with a given number of nodes. In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks.

  14. Dengue research networks: building evidence for policy and planning in Brazil.

    Science.gov (United States)

    de Paula Fonseca E Fonseca, Bruna; Zicker, Fabio

    2016-11-08

    The analysis of scientific networks has been applied in health research to map and measure relationships between researchers and institutions, describing collaboration structures, individual roles, and research outputs, and helping the identification of knowledge gaps and cooperation opportunities. Driven by dengue continued expansion in Brazil, we explore the contribution, dynamics and consolidation of dengue scientific networks that could ultimately inform the prioritisation of research, financial investments and health policy. Social network analysis (SNA) was used to produce a 20-year (1995-2014) retrospective longitudinal evaluation of dengue research networks within Brazil and with its partners abroad, with special interest in describing institutional collaboration and their research outputs. The analysis of institutional co-authorship showed a significant expansion of collaboration over the years, increased international involvement, and ensured a shift from public health research toward vector control and basic biomedical research, probably as a reflection of the expansion of transmission, high burden and increasing research funds from the Brazilian government. The analysis identified leading national organisations that maintained the research network connectivity, facilitated knowledge exchange and reduced network vulnerability. SNA proved to be a valuable tool that, along with other indicators, can strengthen a knowledge platform to inform future policy, planning and funding decisions. The paper provides relevant information to policy and planning for dengue research as it reveals: (1) the effectiveness of the research network in knowledge generation, sharing and diffusion; (2) the near-absence of collaboration with the private sector; and (3) the key central organisations that can support strategic decisions on investments, development and implementation of innovations. In addition, the increase in research activities and collaboration has not yet

  15. The SNaP Wound Care System: a case series using a novel ultraportable negative pressure wound therapy device for the treatment of diabetic lower extremity wounds.

    Science.gov (United States)

    Lerman, Bruce; Oldenbrook, Leslie; Ryu, Justin; Fong, Kenton D; Schubart, Peter J

    2010-07-01

    Although there is significant evidence supporting the use of negative pressure wound therapy (NPWT) for the treatment of lower extremity diabetic ulcers, currently available electrically powered NPWT systems are not ideally suited for treating smaller diabetic foot ulcers. The Smart Negative Pressure (SNaP) Wound Care System is a novel, ultraportable device that delivers NPWT without the use of an electrically powered pump. It was specifically designed to meet the wound care needs of patients with diabetes. The SNaP System is compact, silent, mobile, easy-to-use, and available off-the-shelf. It is fully disposable and may offer other important benefits over electrically powered systems to both the clinician and patient. We review the evidence for use of NPWT for the treatment of diabetic wounds and discuss the potential benefits of this new NPWT technology for patients with diabetes. We also present a case series of four difficult lower extremity diabetic ulcers that were successfully treated with the SNaP System. This study suggests that the SNaP System may be a useful addition to the armamentarium of the diabetic wound care clinician. 2010 Diabetes Technology Society.

  16. Reliability Analysis of Wireless Sensor Networks Using Markovian Model

    Directory of Open Access Journals (Sweden)

    Jin Zhu

    2012-01-01

    Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.

  17. Centrality measures in temporal networks with time series analysis

    Science.gov (United States)

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

    2017-05-01

    The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.

  18. The reconstruction and analysis of tissue specific human metabolic networks.

    Science.gov (United States)

    Hao, Tong; Ma, Hong-Wu; Zhao, Xue-Ming; Goryanin, Igor

    2012-02-01

    Human tissues have distinct biological functions. Many proteins/enzymes are known to be expressed only in specific tissues and therefore the metabolic networks in various tissues are different. Though high quality global human metabolic networks and metabolic networks for certain tissues such as liver have already been studied, a systematic study of tissue specific metabolic networks for all main tissues is still missing. In this work, we reconstruct the tissue specific metabolic networks for 15 main tissues in human based on the previously reconstructed Edinburgh Human Metabolic Network (EHMN). The tissue information is firstly obtained for enzymes from Human Protein Reference Database (HPRD) and UniprotKB databases and transfers to reactions through the enzyme-reaction relationships in EHMN. As our knowledge of tissue distribution of proteins is still very limited, we replenish the tissue information of the metabolic network based on network connectivity analysis and thorough examination of the literature. Finally, about 80% of proteins and reactions in EHMN are determined to be in at least one of the 15 tissues. To validate the quality of the tissue specific network, the brain specific metabolic network is taken as an example for functional module analysis and the results reveal that the function of the brain metabolic network is closely related with its function as the centre of the human nervous system. The tissue specific human metabolic networks are available at .

  19. Exploratory social network analysis with Pajek. - 2nd ed.

    NARCIS (Netherlands)

    de Nooy, W.; Mrvar, A.; Batagelj, V.

    2011-01-01

    This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software

  20. Efficient health care service delivery using network analysis: a case ...

    African Journals Online (AJOL)

    Efficient health care service delivery using network analysis: a case study of Kwara State, Nigeria. ... Ethiopian Journal of Environmental Studies and Management ... This paper addresses challenges with prompt health care delivery using Network Analysis of Critical Path Model (CPM) to plan the hospital capacity with a ...

  1. A Social Network Analysis of Occupational Segregation

    OpenAIRE

    Buhai, Sebastian; van der Leij, Marco

    2006-01-01

    We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important in getting a job, then expected inbreeding bias in the contact network structure induces different career choices for individuals from different social groups. This further translates into stable occupational segregation equilibria in the labour market. We derive the condi...

  2. Complex Network Analysis of Pakistan Railways

    Directory of Open Access Journals (Sweden)

    Yasir Tariq Mohmand

    2014-01-01

    Full Text Available We study the structural properties of Pakistan railway network (PRN, where railway stations are considered as nodes while edges are represented by trains directly linking two stations. The network displays small world properties and is assortative in nature. Based on betweenness and closeness centralities of the nodes, the most important cities are identified with respect to connectivity as this could help in identifying the potential congestion points in the network.

  3. Analysis of friendship network from MMORPG based data

    OpenAIRE

    Črnigoj, Dean

    2016-01-01

    This work analyzes friendship network from a Massively Multiplayer Online Role-Playing Game (MMORPG). The network is based on data from a private server that was active from 2007 until 2011. The work conducts a standard analysis of the network and then divides players according to different groups based on their activity. Work checks how friendship network can be correlated to the clan (a self-organized group of players who often form a league and play on the same side in a match) network. Ma...

  4. Applying temporal network analysis to the venture capital market

    Science.gov (United States)

    Zhang, Xin; Feng, Ling; Zhu, Rongqian; Stanley, H. Eugene

    2015-10-01

    Using complex network theory to study the investment relationships of venture capital firms has produced a number of significant results. However, previous studies have often neglected the temporal properties of those relationships, which in real-world scenarios play a pivotal role. Here we examine the time-evolving dynamics of venture capital investment in China by constructing temporal networks to represent (i) investment relationships between venture capital firms and portfolio companies and (ii) the syndication ties between venture capital investors. The evolution of the networks exhibits rich variations in centrality, connectivity and local topology. We demonstrate that a temporal network approach provides a dynamic and comprehensive analysis of real-world networks.

  5. Dynamical Networks for Smog Pattern Analysis

    CERN Document Server

    Zong, Linqi; Zhu, Jia

    2015-01-01

    Smog, as a form of air pollution, poses as a serious problem to the environment, health, and economy of the world[1-4] . Previous studies on smog mostly focused on the components and the effects of smog [5-10]. However, as the smog happens with increased frequency and duration, the smog pattern which is critical for smog forecast and control, is rarely investigated, mainly due to the complexity of the components, the causes, and the spreading processes of smog. Here we report the first analysis on smog pattern applying the model of dynamical networks with spontaneous recovery. We show that many phenomena such as the sudden outbreak and dissipation of smog and the long duration smog can be revealed with the mathematical mechanism under a random walk simulation. We present real-world air quality index data in accord with the predictions of the model. Also we found that compared to external causes such as pollution spreading from nearby, internal causes such as industrial pollution and vehicle emission generated...

  6. Fractal and multifractal analysis of complex networks: Estonian network of payments

    Science.gov (United States)

    Rendón de la Torre, Stephanie; Kalda, Jaan; Kitt, Robert; Engelbrecht, Jüri

    2017-12-01

    Complex networks have gained much attention from different areas of knowledge in recent years. Particularly, the structures and dynamics of such systems have attracted considerable interest. Complex networks may have characteristics of multifractality. In this study, we analyze fractal and multifractal properties of a novel network: the large scale economic network of payments of Estonia, where companies are represented by nodes and the payments done between companies are represented by links. We present a fractal scaling analysis and examine the multifractal behavior of this network by using a sandbox algorithm. Our results indicate the existence of multifractality in this network and consequently, the existence of multifractality in the Estonian economy. To the best of our knowledge, this is the first study that analyzes multifractality of a complex network of payments.

  7. A Social Network Analysis of Occupational Segregation

    NARCIS (Netherlands)

    I.S. Buhai (Sebastian); M.J. van der Leij (Marco)

    2006-01-01

    textabstractThis paper proposes a simple social network model of occupational segregation, generated by the existence of inbreeding bias among individuals of the same social group. If network referrals are important in getting a job, then expected inbreeding bias in the social structure results in

  8. "Us and them": a social network analysis of physicians' professional networks and their attitudes towards EBM.

    Science.gov (United States)

    Mascia, Daniele; Cicchetti, Americo; Damiani, Gianfranco

    2013-10-22

    Extant research suggests that there is a strong social component to Evidence-Based Medicine (EBM) adoption since professional networks amongst physicians are strongly associated with their attitudes towards EBM. Despite this evidence, it is still unknown whether individual attitudes to use scientific evidence in clinical decision-making influence the position that physicians hold in their professional network. This paper explores how physicians' attitudes towards EBM is related to the network position they occupy within healthcare organizations. Data pertain to a sample of Italian physicians, whose professional network relationships, demographics and work-profile characteristics were collected. A social network analysis was performed to capture the structural importance of physicians in the collaboration network by the means of a core-periphery analysis and the computation of network centrality indicators. Then, regression analysis was used to test the association between the network position of individual clinicians and their attitudes towards EBM. Findings documented that the overall network structure is made up of a dense cohesive core of physicians and of less connected clinicians who occupy the periphery. A negative association between the physicians' attitudes towards EBM and the coreness they exhibited in the professional network was also found. Network centrality indicators confirmed these results documenting a negative association between physicians' propensity to use EBM and their structural importance in the professional network. Attitudes that physicians show towards EBM are related to the part (core or periphery) of the professional networks to which they belong as well as to their structural importance. By identifying virtuous attitudes and behaviors of professionals within their organizations, policymakers and executives may avoid marginalization and stimulate integration and continuity of care, both within and across the boundaries of healthcare

  9. NEXCADE: perturbation analysis for complex networks.

    Directory of Open Access Journals (Sweden)

    Gitanjali Yadav

    Full Text Available Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html.

  10. egoSlider: Visual Analysis of Egocentric Network Evolution.

    Science.gov (United States)

    Wu, Yanhong; Pitipornvivat, Naveen; Zhao, Jian; Yang, Sixiao; Huang, Guowei; Qu, Huamin

    2016-01-01

    Ego-network, which represents relationships between a specific individual, i.e., the ego, and people connected to it, i.e., alters, is a critical target to study in social network analysis. Evolutionary patterns of ego-networks along time provide huge insights to many domains such as sociology, anthropology, and psychology. However, the analysis of dynamic ego-networks remains challenging due to its complicated time-varying graph structures, for example: alters come and leave, ties grow stronger and fade away, and alter communities merge and split. Most of the existing dynamic graph visualization techniques mainly focus on topological changes of the entire network, which is not adequate for egocentric analytical tasks. In this paper, we present egoSlider, a visual analysis system for exploring and comparing dynamic ego-networks. egoSlider provides a holistic picture of the data through multiple interactively coordinated views, revealing ego-network evolutionary patterns at three different layers: a macroscopic level for summarizing the entire ego-network data, a mesoscopic level for overviewing specific individuals' ego-network evolutions, and a microscopic level for displaying detailed temporal information of egos and their alters. We demonstrate the effectiveness of egoSlider with a usage scenario with the DBLP publication records. Also, a controlled user study indicates that in general egoSlider outperforms a baseline visualization of dynamic networks for completing egocentric analytical tasks.

  11. Assessing a Sport/Cultural Events Network: An Application of Social Network Analysis

    OpenAIRE

    Ziakas, V; Costa, CA

    2009-01-01

    The purpose of this study was to assess the complexity of a sport/cultural events network. To that intent, a social network analysis was conducted in a small community in the US. The study had three main objectives: (1) Examine relationships among organisations involved in planning and implementing sport and cultural events based on their communication, exchange of resources, and assistance; (2) Identify the most important actors within the events network and their relationships; (3) Investig...

  12. Weighted Complex Network Analysis of Shanghai Rail Transit System

    Directory of Open Access Journals (Sweden)

    Yingying Xing

    2016-01-01

    Full Text Available With increasing passenger flows and construction scale, Shanghai rail transit system (RTS has entered a new era of networking operation. In addition, the structure and properties of the RTS network have great implications for urban traffic planning, design, and management. Thus, it is necessary to acquire their network properties and impacts. In this paper, the Shanghai RTS, as well as passenger flows, will be investigated by using complex network theory. Both the topological and dynamic properties of the RTS network are analyzed and the largest connected cluster is introduced to assess the reliability and robustness of the RTS network. Simulation results show that the distribution of nodes strength exhibits a power-law behavior and Shanghai RTS network shows a strong weighted rich-club effect. This study also indicates that the intentional attacks are more detrimental to the RTS network than to the random weighted network, but the random attacks can cause slightly more damage to the random weighted network than to the RTS network. Our results provide a richer view of complex weighted networks in real world and possibilities of risk analysis and policy decisions for the RTS operation department.

  13. Changes in Social Capital and Networks: A Study of Community-Based Environmental Management Through a School-Centered Research Program

    Science.gov (United States)

    Thornton, Teresa; Leahy, Jessica

    2012-02-01

    Social network analysis (SNA) is a social science research tool that has not been applied to educational programs. This analysis is critical to documenting the changes in social capital and networks that result from community based K-12 educational collaborations. We review SNA and show an application of this technique in a school-centered, community based environmental monitoring research (CBEMR) program. This CBEMR employs K-12 students, state and local government employees, environmental organization representatives, local businesses, colleges, and community volunteers. As citizen scientists and researchers, collaborators create a database of local groundwater quality to use as a baseline for long-term environmental health management and public education. Past studies have evaluated the reliability of data generated by students acting as scientists, but there have been few studies relating to power dynamics, social capital, and resilience in school-centered CBEMR programs. We use qualitative and quantitative data gathered from a science education program conducted in five states in the northeastern United States. SPSS and NVivo data were derived from semi-structured interviews with thirty-nine participants before and after their participation in the CBEMR. Pajek software was used to determine participant centralities and power brokers within networks. Results indicate that there were statistically significant increases in social capital and resilience in social networks after participation in the school-centered CBEMR program leading to an increased community involvement in environmental health management. Limiting factors to the CBMER were based on the educator/administration relationship.

  14. Trauma-Exposed Latina Immigrants' Networks: A Social Network Analysis Approach.

    Science.gov (United States)

    Hurtado-de-Mendoza, Alejandra; Serrano, Adriana; Gonzales, Felisa A; Fernandez, Nicole C; Cabling, Mark; Kaltman, Stacey

    2016-11-01

    Trauma exposure among Latina immigrants is common. Social support networks can buffer the impact of trauma on mental health. This study characterizes the social networks of trauma-exposed Latina immigrants using a social network analysis perspective. In 2011-2012 a convenience sample (n=28) of Latina immigrants with trauma exposure and presumptive depression or posttraumatic stress disorder was recruited from a community clinic in Washington DC. Participants completed a social network assessment and listed up to ten persons in their network (alters). E-Net was used to describe the aggregate structural, interactional, and functional characteristics of networks and Node-XL was used in a case study to diagram one network. Most participants listed children (93%), siblings (82%), and friends (71%) as alters, and most alters lived in the US (69%). Perceived emotional support and positive social interaction were higher compared to tangible, language, information, and financial support. A case study illustrates the use of network visualizations to assess the strengths and weaknesses of social networks. Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted.

  15. Network externalities in telecommunication industry: An analysis of Serbian market

    Directory of Open Access Journals (Sweden)

    Trifunović Dejan

    2016-01-01

    Full Text Available This paper deals with network competition and provides empirical analysis of market concentration, network and call externalities, access pricing, price discrimination and switching costs in Serbian mobile phone telecommunications market. It is shown that network externalities governed the expansion of this market until 2008. Upon entry of VIP incumbents didn't engage in predatory behaviour towards entrant aiming to benefit from locked- in users. The policy of mobile phone number portability reduced on-net prices and substantially increased consumer's surplus. In contrast to some previous research, this policy was pro-competitive in Serbia. We have also determined that users of the network with the largest market share benefit the most from call externalities. Finally, one network does not price discriminate between outgoing and incoming roaming calls, which implies that users of this network have higher level pecuniary externalities in roaming compared to users of price discriminating networks.

  16. A Social Network Analysis of Occupational Segregation

    DEFF Research Database (Denmark)

    Buhai, Ioan Sebastian; van der Leij, Marco

    We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...... induces different career choices for individuals from different social groups. This further translates into stable occupational segregation equilibria in the labor market. We derive the conditions for wage and unemployment inequality in the segregation equilibria and characterize first and second best...... social welfare optima. Surprisingly, we find that socially optimal policies involve segregation....

  17. Network analysis of unstructured EHR data for clinical research.

    Science.gov (United States)

    Bauer-Mehren, Anna; Lependu, Paea; Iyer, Srinivasan V; Harpaz, Rave; Leeper, Nicholas J; Shah, Nigam H

    2013-01-01

    In biomedical research, network analysis provides a conceptual framework for interpreting data from high-throughput experiments. For example, protein-protein interaction networks have been successfully used to identify candidate disease genes. Recently, advances in clinical text processing and the increasing availability of clinical data have enabled analogous analyses on data from electronic medical records. We constructed networks of diseases, drugs, medical devices and procedures using concepts recognized in clinical notes from the Stanford clinical data warehouse. We demonstrate the use of the resulting networks for clinical research informatics in two ways-cohort construction and outcomes analysis-by examining the safety of cilostazol in peripheral artery disease patients as a use case. We show that the network-based approaches can be used for constructing patient cohorts as well as for analyzing differences in outcomes by comparing with standard methods, and discuss the advantages offered by network-based approaches.

  18. 4 Analysis of Network on Twitter under the Disaster Situation

    OpenAIRE

    石原, 裕規; 諏訪, 博彦; 鳥海, 不二夫; 太田, 敏澄; Hiroki, ISHIHARA; Hirohiko, SUWA; Fujio, TORIUMI; Toshizumi, OHTA; 東京大学大学院工学系研究科システム創成学専攻; 電気通信大学大学院情報システム学研究科; Department of Systems Innovation School of Engineering, The University of Tokyo; Graduate School of Information Systems, The University of Electro-Communications

    2012-01-01

    Using tweets extracted from Twitter during the Great Eastern Japan Earthquake 2011, social network analysis techniques were used to generate and analyse the online networks that emerged at that time. People attempted to collect information about earthquakes and to communicate with friends throught the twitter, and it is coping with the earthquake disaster. The aim was to identify active players for the Great Eastern Earthquake on twitter. We construct a communication network and calculate two...

  19. Neural networks analysis on SSME vibration simulation data

    Science.gov (United States)

    Lo, Ching F.; Wu, Kewei

    1993-01-01

    The neural networks method is applied to investigate the feasibility in detecting anomalies in turbopump vibration of SSME to supplement the statistical method utilized in the prototype system. The investigation of neural networks analysis is conducted using SSME vibration data from a NASA developed numerical simulator. The limited application of neural networks to the HPFTP has also shown the effectiveness in diagnosing the anomalies of turbopump vibrations.

  20. Quantitative analysis of access strategies to remoteinformation in network services

    DEFF Research Database (Denmark)

    Olsen, Rasmus Løvenstein; Schwefel, Hans-Peter; Hansen, Martin Bøgsted

    2006-01-01

    Remote access to dynamically changing information elements is a required functionality for various network services, including routing and instances of context-sensitive networking. Three fundamentally different strategies for such access are investigated in this paper: (1) a reactive approach in......, network delay characterization) and specific requirements on mismatch probability, traffic overhead, and access delay. Finally, the analysis is applied to the use-case of context-sensitive service discovery....

  1. Aggregation algorithm towards large-scale Boolean network analysis

    OpenAIRE

    Zhao, Y.; Kim, J.; Filippone, M.

    2013-01-01

    The analysis of large-scale Boolean network dynamics is of great importance in understanding complex phenomena where systems are characterized by a large number of components. The computational cost to reveal the number of attractors and the period of each attractor increases exponentially as the number of nodes in the networks increases. This paper presents an efficient algorithm to find attractors for medium to large-scale networks. This is achieved by analyzing subnetworks within the netwo...

  2. Network analysis and Canada's large value transfer system

    OpenAIRE

    Embree, Lana; Roberts, Tom

    2009-01-01

    Analysis of the characteristics and structure of a network of financial institutions can provide insight into the complex relationships and interdependencies that exist in a payment, clearing, and settlement system (PCSS), and allow an intuitive understanding of the PCSS's efficiency, stability, and resiliency. The authors review the literature related to the PCSS network and describe the daily and intraday network structure of payment activity in the Large Value Transfer System (LVTS), which...

  3. Statistical and machine learning approaches for network analysis

    CERN Document Server

    Dehmer, Matthias

    2012-01-01

    Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation

  4. PAN network analysis program: its development and use

    Energy Technology Data Exchange (ETDEWEB)

    Goldwater, M.H.; Rogers, K.; Turnbull, D.K.

    1976-01-01

    British Gas Corp.'s London Research Station describes a comprehensive, efficient, and flexible computer simulation of pressure and flows in gas networks known as PAN - Program to Analyze Networks. The program is used extensively throughout the BGC system for both design and control of gas transmission grids. Its powerful method of analysis solves network problems quickly and handles complex configurations of compressors and regulators easily.

  5. Transcription regulatory networks analysis using CAGE

    KAUST Repository

    Tegnér, Jesper N.

    2009-10-01

    Mapping out cellular networks in general and transcriptional networks in particular has proved to be a bottle-neck hampering our understanding of biological processes. Integrative approaches fusing computational and experimental technologies for decoding transcriptional networks at a high level of resolution is therefore of uttermost importance. Yet, this is challenging since the control of gene expression in eukaryotes is a complex multi-level process influenced by several epigenetic factors and the fine interplay between regulatory proteins and the promoter structure governing the combinatorial regulation of gene expression. In this chapter we review how the CAGE data can be integrated with other measurements such as expression, physical interactions and computational prediction of regulatory motifs, which together can provide a genome-wide picture of eukaryotic transcriptional regulatory networks at a new level of resolution. © 2010 by Pan Stanford Publishing Pte. Ltd. All rights reserved.

  6. Social network analysis of sustainable transportation organizations.

    Science.gov (United States)

    2012-07-15

    Studying how organizations communicate with each other can provide important insights into the influence, and policy success of different types of organizations. This study examines the communication networks of 121 organizations promoting sustainabl...

  7. Large-scale Heterogeneous Network Data Analysis

    Science.gov (United States)

    2012-07-31

    Information Diffusion over Crowds with Social Network.” ACM SIGGRAPH 2012. (poster)  Wan-Yu Lin, Nanyun Peng, Chun-Chao Yen, Shou-De Lin. “Online Plagiarism ...Abstract: Large-scale network is a powerful data structure allowing the depiction of relationship information between entities. Recent...we propose an unsupervised tensor-based mechanism, considering higher-order relational information , to model the complex semantics of nodes. The

  8. 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

  9. Network analysis of Chinese provincial economies

    Science.gov (United States)

    Sun, Xiaoqi; An, Haizhong; Liu, Xiaojia

    2018-02-01

    Global economic system is a huge network formed by national subnetworks that contains the provincial networks. As the second largest world economy, China has "too big to fail" impact on the interconnected global economy. Detecting the critical sectors and vital linkages inside Chinese economic network is meaningful for understanding the origin of this Chinese impact. Different from tradition network research at national level, this paper focuses on the provincial networks and inter-provincial network. Using Chinese inter-regional input-output table to construct 30 provincial input-output networks and one inter-provincial input-output network, we identify central sectors and vital linkages, as well as analyze economic structure similarity. Results show that (1) Communication Devices sector in Guangdong and that in Jiangsu, Transportation and Storage sector in Shanghai play critical roles in Chinese economy. (2) Advanced manufactures and services industry occupy the central positions in eastern provincial economies, while Construction sector, Heavy industry, and Wholesale and Retail Trades sector are influential in middle and western provinces. (3) The critical monetary flow paths in Chinese economy are Communication Devices sector to Communication Devices sector in Guangdong, Metals Mining sector to Iron and Steel Smelting sector in Henan, Communication Devices sector to Communication Devices sector in Jiangsu, as well as Petroleum Mining sector in Heilongjiang to Petroleum Processing sector in Liaoning. (4) Collective influence results suggest that Finance sector, Transportation and Storage sector, Production of Electricity and Heat sector, and Rubber and Plastics sector in Hainan are strategic influencers, despite being weakly connected. These sectors and input-output relations are worthy of close attention for monitoring Chinese economy.

  10. Gene network analysis: from heart development to cardiac therapy.

    Science.gov (United States)

    Ferrazzi, Fulvia; Bellazzi, Riccardo; Engel, Felix B

    2015-03-01

    Networks offer a flexible framework to represent and analyse the complex interactions between components of cellular systems. In particular gene networks inferred from expression data can support the identification of novel hypotheses on regulatory processes. In this review we focus on the use of gene network analysis in the study of heart development. Understanding heart development will promote the elucidation of the aetiology of congenital heart disease and thus possibly improve diagnostics. Moreover, it will help to establish cardiac therapies. For example, understanding cardiac differentiation during development will help to guide stem cell differentiation required for cardiac tissue engineering or to enhance endogenous repair mechanisms. We introduce different methodological frameworks to infer networks from expression data such as Boolean and Bayesian networks. Then we present currently available temporal expression data in heart development and discuss the use of network-based approaches in published studies. Collectively, our literature-based analysis indicates that gene network analysis constitutes a promising opportunity to infer therapy-relevant regulatory processes in heart development. However, the use of network-based approaches has so far been limited by the small amount of samples in available datasets. Thus, we propose to acquire high-resolution temporal expression data to improve the mathematical descriptions of regulatory processes obtained with gene network inference methodologies. Especially probabilistic methods that accommodate the intrinsic variability of biological systems have the potential to contribute to a deeper understanding of heart development.

  11. Mental health network governance: comparative analysis across Canadian regions

    Science.gov (United States)

    Wiktorowicz, Mary E; Fleury, Marie-Josée; Adair, Carol E; Lesage, Alain; Goldner, Elliot; Peters, Suzanne

    2010-01-01

    Objective Modes of governance were compared in ten local mental health networks in diverse contexts (rural/urban and regionalized/non-regionalized) to clarify the governance processes that foster inter-organizational collaboration and the conditions that support them. Methods Case studies of ten local mental health networks were developed using qualitative methods of document review, semi-structured interviews and focus groups that incorporated provincial policy, network and organizational levels of analysis. Results Mental health networks adopted either a corporate structure, mutual adjustment or an alliance governance model. A corporate structure supported by regionalization offered the most direct means for local governance to attain inter-organizational collaboration. The likelihood that networks with an alliance model developed coordination processes depended on the presence of the following conditions: a moderate number of organizations, goal consensus and trust among the organizations, and network-level competencies. In the small and mid-sized urban networks where these conditions were met their alliance realized the inter-organizational collaboration sought. In the large urban and rural networks where these conditions were not met, externally brokered forms of network governance were required to support alliance based models. Discussion In metropolitan and rural networks with such shared forms of network governance as an alliance or voluntary mutual adjustment, external mediation by a regional or provincial authority was an important lever to foster inter-organizational collaboration. PMID:21289999

  12. An Analysis of the Structure and Evolution of Networks

    Science.gov (United States)

    Hua, Guangying

    2011-01-01

    As network research receives more and more attention from both academic researchers and practitioners, network analysis has become a fast growing field attracting many researchers from diverse fields such as physics, computer science, and sociology. This dissertation provides a review of theory and research on different real data sets from the…

  13. Analysis of wave directional spreading using neural networks

    Digital Repository Service at National Institute of Oceanography (India)

    Deo, M.C.; Gondane, D.S.; SanilKumar, V.

    !. ‘‘Analysis of directional wave energy using neu- ral networks.’’ MS thesis, Indian Institute of Technology, Bombay, India. Kosko, B. ~1992!. Neural networks and fuzzy systems, Prentice Hall, Englewood Cliffs, N.J. Kuik, A. J., Vledder, G., and Holthuijsen, L...

  14. Network analysis reveals multiscale controls on streamwater chemistry

    Science.gov (United States)

    Kevin J. McGuire; Christian E. Torgersen; Gene E. Likens; Donald C. Buso; Winsor H. Lowe; Scott W. Bailey

    2014-01-01

    By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in...

  15. Water Pipeline Network Analysis Using Simultaneous Loop Flow ...

    African Journals Online (AJOL)

    2013-03-01

    Mar 1, 2013 ... solving for the unknown in water network analysis. It is based on a loop iterative computation. Newton-Raphson method is a better technique for solving the network problems; however, the method adopted here computes simultaneous flow corrections for all loops, hence, the best since the computational.

  16. Transport network extensions for accessibility analysis in geographic information systems

    NARCIS (Netherlands)

    Jong, Tom de; Tillema, T.

    2005-01-01

    In many developed countries high quality digital transport networks are available for GIS based analysis. Partly this is due to the requirements of route planning software for internet and car navigation systems. Properties of these networks consist among others of road quality attributes,

  17. Transient stability analysis of a distribution network with distributed generators

    NARCIS (Netherlands)

    Xyngi, I.; Ishchenko, A.; Popov, M.; Van der Sluis, L.

    2009-01-01

    This letter describes the transient stability analysis of a 10-kV distribution network with wind generators, microturbines, and CHP plants. The network being modeled in Matlab/Simulink takes into account detailed dynamic models of the generators. Fault simulations at various locations are

  18. A Graph Oriented Approach for Network Forensic Analysis

    Science.gov (United States)

    Wang, Wei

    2010-01-01

    Network forensic analysis is a process that analyzes intrusion evidence captured from networked environment to identify suspicious entities and stepwise actions in an attack scenario. Unfortunately, the overwhelming amount and low quality of output from security sensors make it difficult for analysts to obtain a succinct high-level view of complex…

  19. Content analysis of Hydrometeorological Network in the Lower ...

    African Journals Online (AJOL)

    jen

    Osogbo, Nigeria. E-mail (ologunorisatemi@yahoo.com). ABSTRACT: This study deals with content analysis of hydrometerological networks in the Lower Benue. River Basin, Nigeria. This is with the overall aim of determining the effectiveness of the network in terms of providing useful data for agricultural planning. The study ...

  20. Analysis and control of flows in pressurized hydraulic networks

    NARCIS (Netherlands)

    Gupta, R.K.

    2006-01-01

    Analysis, design and flow control problems in pressurized hydraulic networks such as water transmission and distribution systems consisting of pipes and other appurtenant components such as reservoirs, pumps, valves and surge devices are dealt with from the prospective of network synthesis aiming at

  1. Static analysis of topology-dependent broadcast networks

    DEFF Research Database (Denmark)

    Nanz, Sebastian; Nielson, Flemming; Nielson, Hanne Riis

    2010-01-01

    changing network topology is a crucial ingredient. In this paper, we develop a static analysis that automatically constructs an abstract transition system, labelled by actions and connectivity information, to yield a mobility-preserving finite abstraction of the behaviour of a network expressed...

  2. Content analysis of Hydrometeorological Network in the Lower ...

    African Journals Online (AJOL)

    This study deals with content analysis of hydrometerological networks in the Lower Benue River Basin, Nigeria. This is with the overall aim of determining the effectiveness of the network in terms of providing useful data for agricultural planning. The study examines the type of stations in the river basin, the type of equipment ...

  3. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics

    Directory of Open Access Journals (Sweden)

    Jinhui eWang

    2015-06-01

    Full Text Available Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i an open-source, Matlab-based, cross-platform (Windows and UNIX OS package with a graphical user interface; (ii allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website (http://www.nitrc.org/projects/gretna/.

  4. GRETNA: a graph theoretical network analysis toolbox for imaging connectomics.

    Science.gov (United States)

    Wang, Jinhui; Wang, Xindi; Xia, Mingrui; Liao, Xuhong; Evans, Alan; He, Yong

    2015-01-01

    Recent studies have suggested that the brain's structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.

  5. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  6. SBEToolbox: A Matlab Toolbox for Biological Network Analysis.

    Science.gov (United States)

    Konganti, Kranti; Wang, Gang; Yang, Ence; Cai, James J

    2013-01-01

    We present SBEToolbox (Systems Biology and Evolution Toolbox), an open-source Matlab toolbox for biological network analysis. It takes a network file as input, calculates a variety of centralities and topological metrics, clusters nodes into modules, and displays the network using different graph layout algorithms. Straightforward implementation and the inclusion of high-level functions allow the functionality to be easily extended or tailored through developing custom plugins. SBEGUI, a menu-driven graphical user interface (GUI) of SBEToolbox, enables easy access to various network and graph algorithms for programmers and non-programmers alike. All source code and sample data are freely available at https://github.com/biocoder/SBEToolbox/releases.

  7. Inter-organizational network in Indonesia during disasters: Examples and research agenda on disaster management

    Science.gov (United States)

    Bisri, M. B. F.

    2017-02-01

    Indonesia is facing various type of disaster risks, each with its own nature (sudden or slow onset, purely natural or man-made) and coverage of affected areas. Whereas science, technology and engineering intervention requires different modalities for each hazard, little has been known on whether the institutional setup and organizations involvement requires a different or similar types of intervention. Under a decentralized disaster management system, potential involvement of international organizations in response and growing diversified organizations involved in responding to disaster, it is important to understand the nature of inter-organizational network during various type of disasters in Indonesia. This paper is mixture of in-depth literature review and multiple case studies on utilization of social network analysis (SNA) in modelling inter-organizational network during various disasters in Indonesia.

  8. Northern emporia and maritime networks. Modelling past communication using archaeological network analysis

    DEFF Research Database (Denmark)

    Sindbæk, Søren Michael

    2015-01-01

    Long-distance communication has emerged as a particular focus for archaeologicalexploration using network theory, analysis, and modelling. The promise is apparentlyobvious: communication in the past doubtlessly had properties of complex, dynamicnetworks, and archaeological datasets almost certainly...... preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical......,and use patterns. This point is demonstrated with reference to a study of Viking-period communication in the North Sea region...

  9. Privacy Analysis in Mobile Social Networks

    DEFF Research Database (Denmark)

    Sapuppo, Antonio

    2012-01-01

    Nowadays, mobile social networks are capable of promoting social networking benefits during physical meetings, in order to leverage interpersonal affinities not only among acquaintances, but also between strangers. Due to their foundation on automated sharing of personal data in the physical...... surroundings of the user, these networks are subject to crucial privacy threats. Privacy management systems must be capable of accurate selection of data disclosure according to human data sensitivity evaluation. Therefore, it is crucial to research and comprehend an individual's personal information...... disclosure decisions happening in ordinary human communication. Consequently, in this paper we provide insight into influential factors of human data disclosure decisions, by presenting and analysing results of an empirical investigation comprising two online surveys. We focus on the following influential...

  10. Network Reconstruction and Systems Analysis of Cardiac Myocyte Hypertrophy Signaling*

    Science.gov (United States)

    Ryall, Karen A.; Holland, David O.; Delaney, Kyle A.; Kraeutler, Matthew J.; Parker, Audrey J.; Saucerman, Jeffrey J.

    2012-01-01

    Cardiac hypertrophy is managed by a dense web of signaling pathways with many pathways influencing myocyte growth. A quantitative understanding of the contributions of individual pathways and their interactions is needed to better understand hypertrophy signaling and to develop more effective therapies for heart failure. We developed a computational model of the cardiac myocyte hypertrophy signaling network to determine how the components and network topology lead to differential regulation of transcription factors, gene expression, and myocyte size. Our computational model of the hypertrophy signaling network contains 106 species and 193 reactions, integrating 14 established pathways regulating cardiac myocyte growth. 109 of 114 model predictions were validated using published experimental data testing the effects of receptor activation on transcription factors and myocyte phenotypic outputs. Network motif analysis revealed an enrichment of bifan and biparallel cross-talk motifs. Sensitivity analysis was used to inform clustering of the network into modules and to identify species with the greatest effects on cell growth. Many species influenced hypertrophy, but only a few nodes had large positive or negative influences. Ras, a network hub, had the greatest effect on cell area and influenced more species than any other protein in the network. We validated this model prediction in cultured cardiac myocytes. With this integrative computational model, we identified the most influential species in the cardiac hypertrophy signaling network and demonstrate how different levels of network organization affect myocyte size, transcription factors, and gene expression. PMID:23091058

  11. Clinical Grade ?SNaPshot? Genetic Mutation Profiling in Multiple Myeloma

    OpenAIRE

    O'Donnell, Elizabeth; Mahindra, Anuj; Yee, Andrew J.; Nardi, Valentina; Birrer, Nicole; Horick, Nora; Borger, Darrell; Finkelstein, Dianne; Iafrate, John A.; Raje, Noopur

    2014-01-01

    Whole genome sequencing studies have identified several oncogenic mutations in multiple myeloma (MM). As MM progresses, it evolves genetically underscoring the need to have tools for rapid detection of targetable mutations to optimize individualized treatment. Massachusetts General Hospital (MGH) has developed a Clinical Laboratory Improvement Amendments (CLIA)-approved, high-throughput, genotyping platform to determine the mutation status of a panel of known oncogenes. Sequence analysis usin...

  12. Muscle networks: Connectivity analysis of EMG activity during postural control

    Science.gov (United States)

    Boonstra, Tjeerd W.; Danna-Dos-Santos, Alessander; Xie, Hong-Bo; Roerdink, Melvyn; Stins, John F.; Breakspear, Michael

    2015-12-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures.

  13. An Approach to Data Analysis in 5G Networks

    Directory of Open Access Journals (Sweden)

    Lorena Isabel Barona López

    2017-02-01

    Full Text Available 5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.

  14. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Kezhu Hong

    2007-04-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  15. Throughput Analysis of Large Wireless Networks with Regular Topologies

    Directory of Open Access Journals (Sweden)

    Hong Kezhu

    2007-01-01

    Full Text Available The throughput of large wireless networks with regular topologies is analyzed under two medium-access control schemes: synchronous array method (SAM and slotted ALOHA. The regular topologies considered are square, hexagon, and triangle. Both nonfading channels and Rayleigh fading channels are examined. Furthermore, both omnidirectional antennas and directional antennas are considered. Our analysis shows that the SAM leads to a much higher network throughput than the slotted ALOHA. The network throughput in this paper is measured in either bits-hops per second per Hertz per node or bits-meters per second per Hertz per node. The exact connection between the two measures is shown for each topology. With these two fundamental units, the network throughput shown in this paper can serve as a reliable benchmark for future works on network throughput of large networks.

  16. Social network analysis of public health programs to measure partnership.

    Science.gov (United States)

    Schoen, Martin W; Moreland-Russell, Sarah; Prewitt, Kim; Carothers, Bobbi J

    2014-12-01

    In order to prevent chronic diseases, community-based programs are encouraged to take an ecological approach to public health promotion and involve many diverse partners. Little is known about measuring partnership in implementing public health strategies. We collected data from 23 Missouri communities in early 2012 that received funding from three separate programs to prevent obesity and/or reduce tobacco use. While all of these funding programs encourage partnership, only the Social Innovation for Missouri (SIM) program included a focus on building community capacity and enhancing collaboration. Social network analysis techniques were used to understand contact and collaboration networks in community organizations. Measurements of average degree, density, degree centralization, and betweenness centralization were calculated for each network. Because of the various sizes of the networks, we conducted comparative analyses with and without adjustment for network size. SIM programs had increased measurements of average degree for partner collaboration and larger networks. When controlling for network size, SIM groups had higher measures of network density and lower measures of degree centralization and betweenness centralization. SIM collaboration networks were more dense and less centralized, indicating increased partnership. The methods described in this paper can be used to compare partnership in community networks of various sizes. Further research is necessary to define causal mechanisms of partnership development and their relationship to public health outcomes. Copyright © 2014 Elsevier Ltd. All rights reserved.

  17. Satellite communications network design and analysis

    CERN Document Server

    Jo, Kenneth Y

    2011-01-01

    This authoritative book provides a thorough understanding of the fundamental concepts of satellite communications (SATCOM) network design and performance assessments. You find discussions on a wide class of SATCOM networks using satellites as core components, as well as coverage key applications in the field. This in-depth resource presents a broad range of critical topics, from geosynchronous Earth orbiting (GEO) satellites and direct broadcast satellite systems, to low Earth orbiting (LEO) satellites, radio standards and protocols.This invaluable reference explains the many specific uses of

  18. Sentiment analysis on smoking in social networks.

    Science.gov (United States)

    Sofean, Mustafa; Smith, Matthew

    2013-01-01

    Online social networks play a vital role in daily life to share the opinions or behaviors on different topics. The data of social networks can be used to understand health-related behaviors. In this work, we used Twitter status updates to survey of smoking behaviors among the users. We introduce approach to classify the sentiment of smoke-related tweets into positive and negative tweets. The classifier is based on the Support Vector Machines (SVMs) and can achieve high accuracy up to 86%.

  19. 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.

  20. SMEX05 Soil Climate Analysis Network (SCAN) Data: Iowa

    Data.gov (United States)

    National Aeronautics and Space Administration — This data set contains measurements taken during the Soil Moisture Experiment 2005 (SMEX05) from 10 June 2005 through 03 July 2005 at Soil Climate Analysis Network...

  1. Network Analysis of Clinical Placement of Athletic Training Students

    National Research Council Canada - National Science Library

    M G Miller; C Harvatt; K Hirsch; W R Holcomb

    2017-01-01

    An abstract of a study by Miller et al determining communication aspects using social network analysis for on-campus and off campus clinical placement sites of undergraduate athletic training students is presented...

  2. Error performance analysis in downlink cellular networks with interference management

    KAUST Repository

    Afify, Laila H.

    2015-05-01

    Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.

  3. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    Directory of Open Access Journals (Sweden)

    Aaron M. Prescott

    2016-08-01

    Full Text Available Most models for ethylene signaling involve a linear pathway. However, measurements of seedling growth kinetics when ethylene is applied and removed have resulted in more complex network models that include coherent feedforward, negative feedback, and positive feedback motifs. However, the dynamical responses of the proposed networks have not been explored in a quantitative manner. Here, we explore (i whether any of the proposed models are capable of producing growth-response behaviors consistent with experimental observations and (ii what mechanistic roles various parts of the network topologies play in ethylene signaling. To address this, we used computational methods to explore two general network topologies: The first contains a coherent feedforward loop that inhibits growth and a negative feedback from growth onto itself (CFF/NFB. In the second, ethylene promotes the cleavage of EIN2, with the product of the cleavage inhibiting growth and promoting the production of EIN2 through a positive feedback loop (PFB. Since few network parameters for ethylene signaling are known in detail, we used an evolutionary algorithm to explore sets of parameters that produce behaviors similar to experimental growth response kinetics of both wildtype and mutant seedlings. We generated a library of parameter sets by independently running the evolutionary algorithm many times. Both network topologies produce behavior consistent with experimental observations and analysis of the parameter sets allows us to identify important network interactions and parameter constraints. We additionally screened these parameter sets for growth recovery in the presence of sub-saturating ethylene doses, which is an experimentally-observed property that emerges in some of the evolved parameter sets. Finally, we probed simplified networks maintaining key features of the CFF/NFB and PFB topologies. From this, we verified observations drawn from the larger networks about mechanisms

  4. Modular analysis of gene networks by linear temporal logic.

    Science.gov (United States)

    Ito, Sohei; Ichinose, Takuma; Shimakawa, Masaya; Izumi, Naoko; Hagihara, Shigeki; Yonezaki, Naoki

    2013-03-25

    Despite a lot of advances in biology and genomics, it is still difficult to utilise such valuable knowledge and information to understand and analyse large biological systems due to high computational complexity. In this paper we propose a modular method with which from several small network analyses we analyse a large network by integrating them. This method is based on the qualitative framework proposed by authors in which an analysis of gene networks is reduced to checking satisfiability of linear temporal logic formulae. The problem of linear temporal logic satisfiability checking needs exponential time in the size of a formula. Thus it is difficult to analyse large networks directly in this method since the size of a formula grows linearly to the size of a network. The modular method alleviates this computational difficulty. We show some experimental results and see how we benefit from the modular analysis method.

  5. Sample-Starved Large Scale Network Analysis

    Science.gov (United States)

    2016-05-05

    Applications to materials science 2.1 Foundational principles for large scale inference on structure of covariance We developed general principles for...concise but accessible format. These principles are applicable to large-scale complex network applications arising genomics , connectomics, eco-informatics...available to estimate or detect patterns in the matrix. 15. SUBJECT TERMS multivariate dependency structure multivariate spatio-temporal prediction

  6. Using Citation Network Analysis in Educational Technology

    Science.gov (United States)

    Cho, Yonjoo; Park, Sunyoung

    2012-01-01

    Previous reviews in the field of Educational Technology (ET) have revealed some publication patterns according to authors, institutions, and affiliations. However, those previous reviews focused only on the rankings of individual authors and institutions, and did not provide qualitative details on relations and networks of scholars and scholarly…

  7. 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.

  8. 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.

  9. Functional Interaction Network Construction and Analysis for Disease Discovery.

    Science.gov (United States)

    Wu, Guanming; Haw, Robin

    2017-01-01

    Network-based approaches project seemingly unrelated genes or proteins onto a large-scale network context, therefore providing a holistic visualization and analysis platform for genomic data generated from high-throughput experiments, reducing the dimensionality of data via using network modules and increasing the statistic analysis power. Based on the Reactome database, the most popular and comprehensive open-source biological pathway knowledgebase, we have developed a highly reliable protein functional interaction network covering around 60 % of total human genes and an app called ReactomeFIViz for Cytoscape, the most popular biological network visualization and analysis platform. In this chapter, we describe the detailed procedures on how this functional interaction network is constructed by integrating multiple external data sources, extracting functional interactions from human curated pathway databases, building a machine learning classifier called a Naïve Bayesian Classifier, predicting interactions based on the trained Naïve Bayesian Classifier, and finally constructing the functional interaction database. We also provide an example on how to use ReactomeFIViz for performing network-based data analysis for a list of genes.

  10. Robust flux balance analysis of multiscale biochemical reaction networks.

    Science.gov (United States)

    Sun, Yuekai; Fleming, Ronan M T; Thiele, Ines; Saunders, Michael A

    2013-07-30

    Biological processes such as metabolism, signaling, and macromolecular synthesis can be modeled as large networks of biochemical reactions. Large and comprehensive networks, like integrated networks that represent metabolism and macromolecular synthesis, are inherently multiscale because reaction rates can vary over many orders of magnitude. They require special methods for accurate analysis because naive use of standard optimization systems can produce inaccurate or erroneously infeasible results. We describe techniques enabling off-the-shelf optimization software to compute accurate solutions to the poorly scaled optimization problems arising from flux balance analysis of multiscale biochemical reaction networks. We implement lifting techniques for flux balance analysis within the openCOBRA toolbox and demonstrate our techniques using the first integrated reconstruction of metabolism and macromolecular synthesis for E. coli. Our techniques enable accurate flux balance analysis of multiscale networks using off-the-shelf optimization software. Although we describe lifting techniques in the context of flux balance analysis, our methods can be used to handle a variety of optimization problems arising from analysis of multiscale network reconstructions.

  11. Learning Bayesian networks from big meteorological spatial datasets. An alternative to complex network analysis

    Science.gov (United States)

    Gutiérrez, Jose Manuel; San Martín, Daniel; Herrera, Sixto; Santiago Cofiño, Antonio

    2016-04-01

    The growing availability of spatial datasets (observations, reanalysis, and regional and global climate models) demands efficient multivariate spatial modeling techniques for many problems of interest (e.g. teleconnection analysis, multi-site downscaling, etc.). Complex networks have been recently applied in this context using graphs built from pairwise correlations between the different stations (or grid boxes) forming the dataset. However, this analysis does not take into account the full dependence structure underlying the data, gien by all possible marginal and conditional dependencies among the stations, and does not allow a probabilistic analysis of the dataset. In this talk we introduce Bayesian networks as an alternative multivariate analysis and modeling data-driven technique which allows building a joint probability distribution of the stations including all relevant dependencies in the dataset. Bayesian networks is a sound machine learning technique using a graph to 1) encode the main dependencies among the variables and 2) to obtain a factorization of the joint probability distribution of the stations given by a reduced number of parameters. For a particular problem, the resulting graph provides a qualitative analysis of the spatial relationships in the dataset (alternative to complex network analysis), and the resulting model allows for a probabilistic analysis of the dataset. Bayesian networks have been widely applied in many fields, but their use in climate problems is hampered by the large number of variables (stations) involved in this field, since the complexity of the existing algorithms to learn from data the graphical structure grows nonlinearly with the number of variables. In this contribution we present a modified local learning algorithm for Bayesian networks adapted to this problem, which allows inferring the graphical structure for thousands of stations (from observations) and/or gridboxes (from model simulations) thus providing new

  12. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Science.gov (United States)

    Zonglin, Li; Guangmin, Hu; Xingmiao, Yao; Dan, Yang

    2008-12-01

    Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation). The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  13. Detecting Distributed Network Traffic Anomaly with Network-Wide Correlation Analysis

    Directory of Open Access Journals (Sweden)

    Yang Dan

    2008-12-01

    Full Text Available Distributed network traffic anomaly refers to a traffic abnormal behavior involving many links of a network and caused by the same source (e.g., DDoS attack, worm propagation. The anomaly transiting in a single link might be unnoticeable and hard to detect, while the anomalous aggregation from many links can be prevailing, and does more harm to the networks. Aiming at the similar features of distributed traffic anomaly on many links, this paper proposes a network-wide detection method by performing anomalous correlation analysis of traffic signals' instantaneous parameters. In our method, traffic signals' instantaneous parameters are firstly computed, and their network-wide anomalous space is then extracted via traffic prediction. Finally, an anomaly is detected by a global correlation coefficient of anomalous space. Our evaluation using Abilene traffic traces demonstrates the excellent performance of this approach for distributed traffic anomaly detection.

  14. Dynamic social network analysis using conversational dynamics in social networking and microblogging environments

    Science.gov (United States)

    Stocco, Gabriel; Savell, Robert; Cybenko, George

    2010-04-01

    In many security environments, the textual content of communications may be unavailable. In these instances, it is often desirable to infer the status of the network and its component entities from patterns of communication flow. Conversational dynamics among entities in the network may provide insight into important aspects of the underlying social network such as the formational dynamics of group structures, the active state of these groups, individuals' roles within groups, and the likelihood of individual participation in conversations. To gain insight into the use of conversational dynamics to facilitate Dynamic Social Network Analysis, we explore the use of interevent timings to associate entities in the Twitter social networking and micro-blogging environment. Specifically, we use message timings to establish inter-nodal relationships among participants. In addition, we demonstrate a new visualization technique for tracking levels of coordination or synchronization within the community via measures of socio-temporal coherence of the participants.

  15. The network analysis of urban streets: A dual approach

    Science.gov (United States)

    Porta, Sergio; Crucitti, Paolo; Latora, Vito

    2006-09-01

    The application of the network approach to the urban case poses several questions in terms of how to deal with metric distances, what kind of graph representation to use, what kind of measures to investigate, how to deepen the correlation between measures of the structure of the network and measures of the dynamics on the network, what are the possible contributions from the GIS community. In this paper, the author considers six cases of urban street networks characterized by different patterns and historical roots. The authors propose a representation of the street networks based firstly on a primal graph, where intersections are turned into nodes and streets into edges. In a second step, a dual graph, where streets are nodes and intersections are edges, is constructed by means of a generalization model named Intersection Continuity Negotiation, which allows to acknowledge the continuity of streets over a plurality of edges. Finally, the authors address a comparative study of some structural properties of the dual graphs, seeking significant similarities among clusters of cases. A wide set of network analysis techniques are implemented over the dual graph: in particular the authors show that the absence of any clue of assortativity differentiates urban street networks from other non-geographic systems and that most of the considered networks have a broad degree distribution typical of scale-free networks and exhibit small-world properties as well.

  16. Sediment Analysis Network for Decision Support (SANDS)

    Science.gov (United States)

    Hardin, D. M.; Keiser, K.; Graves, S. J.; Conover, H.; Ebersole, S.

    2009-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The recently awarded Sediment Analysis Network for Decision Support will generate decision support products using NASA satellite observations from MODIS, Landsat and SeaWiFS instruments to support resource management, planning, and decision making activities in the Gulf of Mexico. Specifically, SANDS will generate decision support products that address the impacts of tropical storms

  17. The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis.

    Science.gov (United States)

    Li, Lun; Catalá-López, Ferrán; Alonso-Arroyo, Adolfo; Tian, Jinhui; Aleixandre-Benavent, Rafael; Pieper, Dawid; Ge, Long; Yao, Liang; Wang, Quan; Yang, Kehu

    Research collaborations in biomedical research have evolved over time. No studies have addressed research collaboration in network meta-analysis (NMA). In this study, we used social network analysis methods to characterize global collaboration patterns of published NMAs over the past decades. PubMed, EMBASE, Web of Science and the Cochrane Library were searched (at 9th July, 2015) to include systematic reviews incorporating NMA. Two reviewers independently selected studies and cross-checked the standardized data. Data was analyzed using Ucinet 6.0 and SPSS 17.0. NetDraw software was used to draw social networks. 771 NMAs published in 336 journals from 3459 authors and 1258 institutions in 49 countries through the period 1997-2015 were included. More than three-quarters (n = 625; 81.06%) of the NMAs were published in the last 5-years. The BMJ (4.93%), Current Medical Research and Opinion (4.67%) and PLOS One (4.02%) were the journals that published the greatest number of NMAs. The UK and the USA (followed by Canada, China, the Netherlands, Italy and Germany) headed the absolute global productivity ranking in number of NMAs. The top 20 authors and institutions with the highest publication rates were identified. Overall, 43 clusters of authors (four major groups: one with 37 members, one with 12 members, one with 11 members and one with 10 members) and 21 clusters of institutions (two major groups: one with 62 members and one with 20 members) were identified. The most prolific authors were affiliated with academic institutions and private consulting firms. 181 consulting firms and pharmaceutical industries (14.39% of institutions) were involved in 199 NMAs (25.81% of total publications). Although there were increases in international and inter-institution collaborations, the research collaboration by authors, institutions and countries were still weak and most collaboration groups were small sizes. Scientific production on NMA is increasing worldwide with research

  18. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  19. Investment Valuation Analysis with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Hüseyin İNCE

    2017-07-01

    Full Text Available This paper shows that discounted cash flow and net present value, which are traditional investment valuation models, can be combined with artificial neural network model forecasting. The main inputs for the valuation models, such as revenue, costs, capital expenditure, and their growth rates, are heavily related to sector dynamics and macroeconomics. The growth rates of those inputs are related to inflation and exchange rates. Therefore, predicting inflation and exchange rates is a critical issue for the valuation output. In this paper, the Turkish economy’s inflation rate and the exchange rate of USD/TRY are forecast by artificial neural networks and implemented to the discounted cash flow model. Finally, the results are benchmarked with conventional practices.

  20. A Network Text Analysis of David Ayer’s Fury

    Directory of Open Access Journals (Sweden)

    Starling David Hunter

    2015-12-01

    Full Text Available Network Text Analysis (NTA involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In this study we demonstrate a deductive approach that we apply to the screenplay of the 2014 World War II-era film Fury. Specifically, we first use genre expectations theory to establish prior expectations as to the key themes associated with war films. We then empirically test whether words and concepts associated with the most influentially-positioned nodes are consistent with themes common to the war-film genre. As predicted, we find that words and concepts associated with the least constrained nodes in the text network were significantly more likely to be associated with the war, action, and biography genres and significantly less likely to be associated with the mystery, science-fiction, fantasy, and film-noir genres. Keywords: content analysis, text analysis, network text analysis, semantic network analysis, film studies, screenplay, screenwriting, war movies, World War II, tanks

  1. Temporal Network Analysis of Literary Texts

    OpenAIRE

    Prado, Sandra D.; Dahmen, Silvio R.; Bazzan, Ana L. C.; Mac Carron, Padraig; Kenna, Ralph

    2016-01-01

    We study temporal networks of characters in literature focusing on "Alice's Adventures in Wonderland" (1865) by Lewis Carroll and the anonymous "La Chanson de Roland" (around 1100). The former, one of the most influential pieces of nonsense literature ever written, describes the adventures of Alice in a fantasy world with logic plays interspersed along the narrative. The latter, a song of heroic deeds, depicts the Battle of Roncevaux in 778 A.D. during Charlemagne's campaign on the Iberian Pe...

  2. Social Network Analysis in Frontier Capital Markets

    Science.gov (United States)

    2012-06-01

    markets using mathematical techniques to identify and evaluate the nodes in the network. Initially focusing on stock exchange personnel and government...values. He is currently affiliated with the Trinidad and Tobago Stock Exchange , a brokerage firm, and a federal anti-corruption commission. He is also on...delisted from the Dar es Salaam stock exchange in July 2011 because it failed to submit 2009 and 2010 financial statements. Ghana Four organizations

  3. The Network's Data Security Risk Analysis

    Directory of Open Access Journals (Sweden)

    Emil BURTESCU

    2008-01-01

    Full Text Available Establishing the networks security risk can be a very difficult operation especially for the small companies which, from financial reasons can't appeal at specialist in this domain, or for the medium or large companies that don't have experience. The following method proposes not to use complex financial calculus to determine the loss level and the value of impact making the determination of risk level a lot easier.

  4. Traffic incidents analysis on Slovenian motorway network

    OpenAIRE

    Jakše, Bojan

    2013-01-01

    In my bachelor thesis we were analysing traffic incidents (such as accidents, congestions, heavy snow, etc.) on Slovenian road network, specifically we focused on incidents on motorways. We were starting from database of incidents provided by Prometno-informacijski center (Traffic information center) and added information about hourly traffic at the moment of incident. We were also researching possible correlations between weather and traffic congestions and accidents as well as behaviour of ...

  5. Supporting MOOC Instruction with Social Network Analysis

    OpenAIRE

    Sinha, Tanmay

    2014-01-01

    With an expansive and ubiquitously available gold mine of educational data, Massive Open Online courses (MOOCs) have become the an important foci of learning analytics research. In this paper, we investigate potential reasons as to why are these digitalized learning repositories being plagued with huge attrition rates. We analyze an ongoing online course offered in Coursera using a social network perspective, with an objective to identify students who are actively participating in course disc...

  6. Analysis and design of networked control systems

    CERN Document Server

    You, Keyou; Xie, Lihua

    2015-01-01

    This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: ·         minimum data rate for stabilization of linear systems over noisy channels; ·         minimum network requirement for stabilization of linear systems over fading channels; and ·         stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are de...

  7. Qualitative Analysis of Commercial Social Network Profiles

    Science.gov (United States)

    Melendez, Lester; Wolfson, Ouri; Adjouadi, Malek; Rishe, Naphtali

    Social-networking sites have become an integral part of many users' daily internet routine. Commercial enterprises have been quick to recognize this and are subsequently creating profiles for many of their products and services. Commercial enterprises use social network profiles to target and interact with potential customers as well as to provide a gateway for users of the product or service to interact with each other. Many commercial enterprises use the statistics from their product or service's social network profile to tout the popularity and success of the product or service being showcased. They will use statistics such as number of friends, number of daily visits, number of interactions, and other similar measurements to quantify their claims. These statistics are often not a clear indication of the true popularity and success of the product. In this chapter the term product is used to refer to any tangible or intangible product, service, celebrity, personality, film, book, or other entity produced by a commercial enterprise.

  8. Identification of Conserved Moieties in Metabolic Networks by Graph Theoretical Analysis of Atom Transition Networks

    Science.gov (United States)

    Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.

    2016-01-01

    Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845

  9. 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.

  10. 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.

  11. Modeling and Analysis of New Products Diffusion on Heterogeneous Networks

    Directory of Open Access Journals (Sweden)

    Shuping Li

    2014-01-01

    Full Text Available We present a heterogeneous networks model with the awareness stage and the decision-making stage to explain the process of new products diffusion. If mass media is neglected in the decision-making stage, there is a threshold whether the innovation diffusion is successful or not, or else it is proved that the network model has at least one positive equilibrium. For networks with the power-law degree distribution, numerical simulations confirm analytical results, and also at the same time, by numerical analysis of the influence of the network structure and persuasive advertisements on the density of adopters, we give two different products propagation strategies for two classes of nodes in scale-free networks.

  12. Estudo da rede de co-autoria e da interdisciplinaridade na produção científica com base nos métodos de análise de redes sociais: avaliação do caso do programa de pós-graduação em ciência da informação - PPGCI / UFMG Study of co-authorship in the nets and the interdisciplinarity in the scientific production on the basis of social network analysis methods: evaluation of the posgraduation program in information science - PPGCI / UFMG

    Directory of Open Access Journals (Sweden)

    Antonio Braz de Oliveira e Silva

    2006-01-01

    Full Text Available Este artigo apresenta a Análise de Redes Sociais (ARS como um método a ser aplicado em estudos na Ciência da Informação (CI. Esta é, normalmente, apresentada como uma área do conhecimento interdisciplinar, mas as diferentes linhas de pesquisa existentes nos Programas de Pós-Graduação no Brasil recebem influências de diferentes áreas do conhecimento, ou seja, possuem diferenças em suas interdisciplinaridades. A aplicação da ARS no estudo da rede de co-autoria dos professores do PPGCI/UFMG permite tanto a apresentação do método como a obtenção de resultados empíricos para alimentar a discussão sobre a CI. As redes de colaboração entre os professores refletem, em tese, a participação em programas de pesquisa da área. A colaboração entre professores das diferentes linhas se relaciona com a integração das diferentes interdisciplinaridades que elas apresentam. O texto dá uma visão geral da ARS e apresenta estudos da área, destacando-se a análise de redes de co-autoria. Em seguida, se descreve a metodologia da pesquisa e os principais resultados obtidos da ARS.This paper discusses the Social Network Analysis (SNA as a method to be broadly applied in researches in the Information Scienc (IS field. This science is, normally, presented as an interdisciplinary filed, but the reseaches lines conducted in Brazil have differents relationship with other disciplines, and doing so, dis-similars interdisciplinaries characteristics. The analysis of the co-authorship network of the professors of the PPGCI/UFMG emphasizes both, the strenght of the methodology and the characteristics of the colaboration in the IS. The article gives an overview of the theoretical basis of the SNA, and presents studies about subjects related to the Information Science field that are done applying SNA, mainly the co-authorship network analysis. Finally, the methodological approach of this research and the main results are presented.

  13. Spatial Distribution Characteristics of Healthcare Facilities in Nanjing: Network Point Pattern Analysis and Correlation Analysis.

    Science.gov (United States)

    Ni, Jianhua; Qian, Tianlu; Xi, Changbai; Rui, Yikang; Wang, Jiechen

    2016-08-18

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities.

  14. Compartmentalization analysis using discrete fracture network models

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)

    1997-08-01

    This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.

  15. 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.

  16. 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.

  17. 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.

  18. On the Optimality of Trust Network Analysis with Subjective Logic

    Directory of Open Access Journals (Sweden)

    PARK, Y.

    2014-08-01

    Full Text Available Building and measuring trust is one of crucial aspects in e-commerce, social networking and computer security. Trust networks are widely used to formalize trust relationships and to conduct formal reasoning of trust values. Diverse trust network analysis methods have been developed so far and one of the most widely used schemes is TNA-SL (Trust Network Analysis with Subjective Logic. Recent papers claimed that TNA-SL always finds the optimal solution by producing the least uncertainty. In this paper, we present some counter-examples, which imply that TNA-SL is not an optimal algorithm. Furthermore, we present a probabilistic algorithm in edge splitting to minimize uncertainty.

  19. A New Approach for the Stability Analysis of Wave Networks

    Directory of Open Access Journals (Sweden)

    Ya Xuan Zhang

    2014-01-01

    Full Text Available We introduce a new approach to investigate the stability of controlled tree-shaped wave networks and subtrees of complex wave networks. It is motivated by regarding the network as branching out from a single edge. We present the recursive relations of the Laplacian transforms of adjacent edges of the system in its branching order, which form the characteristic equation. In the stability analysis, we estimate the infimums of the recursive expressions in the inverse order based on the spectral analysis. It is a feasible way to check whether the system is exponentially stable under any control strategy or parameter choice. As an application we design the control law and study the stability of a 12-edge tree-shaped wave network.

  20. Ego Network Analysis of Upper Division Physics Student Survey

    Science.gov (United States)

    Brewe, Eric

    2017-01-01

    We present the analysis of student networks derived from a survey of upper division physics students. Ego networks focus on the connections that center on one person (the ego). The ego networks in this talk come from a survey that is part of an overall project focused on understanding student retention and persistence. The theory underlying this work is that social and academic integration are essential components to supporting students continued enrollment and ultimately graduation. This work uses network analysis as a way to investigate the role of social and academic interactions in retention and persistence decisions. We focus on student interactions with peers, on mentoring interactions with physics department faculty, and on engagement in physics groups and how they influence persistence. Our results, which are preliminary, will help frame the ongoing research project and identify ways in which departments can support students. This work supported by NSF grant #PHY 1344247.

  1. Anatomy and histology as socially networked learning environments: some preliminary findings.

    Science.gov (United States)

    Hafferty, Frederic W; Castellani, Brian; Hafferty, Philip K; Pawlina, Wojciech

    2013-09-01

    An exploratory study to better understand the "networked" life of the medical school as a learning environment. In a recent academic year, the authors gathered data during two six-week blocks of a sequential histology and anatomy course at a U.S. medical college. An eight-item questionnaire captured different dimensions of student interactions. The student cohort/network was 48 first-year medical students. Using social network analysis (SNA), the authors focused on (1) the initial structure and the evolution of informal class networks over time, (2) how informal class networks compare to formal in-class small-group assignments in influencing student information gathering, and (3) how peer assignment of professionalism role model status is shaped more by informal than formal ties. In examining these latter two issues, the authors explored not only how formal group assignment persisted over time but also how it functioned to prevent the tendency for groupings based on gender or ethnicity. The study revealed an evolving dynamic between the formal small-group learning structure of the course blocks and the emergence of informal student networks. For example, whereas formal group membership did influence in-class questions and did prevent formation of groups of like gender and ethnicity, outside-class questions and professionalism were influenced more by informal group ties where gender and, to a much lesser extent, ethnicity influence student information gathering. The richness of these preliminary findings suggests that SNA may be a useful tool in examining an array of medical student learning encounters.

  2. Assessing state-level active living promotion using network analysis.

    Science.gov (United States)

    Buchthal, Opal Vanessa; Taniguchi, Nicole; Iskandar, Livia; Maddock, Jay

    2013-01-01

    Physical inactivity is a growing problem in the United States, one that is being addressed through the development of active living communities. However, active living promotion requires collaboration among organizations that may not have previously shared goals. A network analysis was conducted to assess Hawaii's active living promotion network. Twenty-six organizations playing a significant role in promoting active living in Hawaii were identified and surveyed about their frequency of contact, level of collaboration, and funding flow with other agencies. A communication network was identified linking all agencies. This network had many long pathways, impeding information flow. The Department of Health (DOH) and the State Nutrition and Physical Activity Coalition (NPAC) were central nodes, but DOH connected state agencies while NPAC linked county and voluntary organizations. Within the network, information sharing was common, but collaboration and formal partnership were low. Linkages between county and state agencies, between counties, and between state agencies with different core agendas were particularly low. Results suggest that in the early stages of development, active living networks may be divided by geography and core missions, requiring work to bridge these divides. Network mapping appears helpful in identifying areas for network development.

  3. Service network design of bike sharing systems analysis and optimization

    CERN Document Server

    Vogel, Patrick

    2016-01-01

    This monograph presents a tactical planning approach for service network design in metropolitan areas. Designing the service network requires the suitable aggregation of demand data as well as the anticipation of operational relocation decisions. To this end, an integrated approach of data analysis and mathematical optimization is introduced. The book also includes a case study based on real-world data to demonstrate the benefit of the proposed service network design approach. The target audience comprises primarily research experts in the field of traffic engineering, but the book may also be beneficial for graduate students.

  4. Network similarity and statistical analysis of earthquake seismic data

    Science.gov (United States)

    Deyasi, Krishanu; Chakraborty, Abhijit; Banerjee, Anirban

    2017-09-01

    We study the structural similarity of earthquake networks constructed from seismic catalogs of different geographical regions. A hierarchical clustering of underlying undirected earthquake networks is shown using Jensen-Shannon divergence in graph spectra. The directed nature of links indicates that each earthquake network is strongly connected, which motivates us to study the directed version statistically. Our statistical analysis of each earthquake region identifies the hub regions. We calculate the conditional probability of the forthcoming occurrences of earthquakes in each region. The conditional probability of each event has been compared with their stationary distribution.

  5. Google matrix analysis of C.elegans neural network

    Science.gov (United States)

    Kandiah, V.; Shepelyansky, D. L.

    2014-05-01

    We study the structural properties of the neural network of the C.elegans (worm) from a directed graph point of view. The Google matrix analysis is used to characterize the neuron connectivity structure and node classifications are discussed and compared with physiological properties of the cells. Our results are obtained by a proper definition of neural directed network and subsequent eigenvector analysis which recovers some results of previous studies. Our analysis highlights particular sets of important neurons constituting the core of the neural system. The applications of PageRank, CheiRank and ImpactRank to characterization of interdependency of neurons are discussed.

  6. Neural network analysis for hazardous waste characterization

    Energy Technology Data Exchange (ETDEWEB)

    Misra, M.; Pratt, L.Y.; Farris, C. [Colorado School of Mines, Golden, CO (United States)] [and others

    1995-12-31

    This paper is a summary of our work in developing a system for interpreting electromagnetic (EM) and magnetic sensor information from the dig face characterization experimental cell at INEL to determine the depth and nature of buried objects. This project contained three primary components: (1) development and evaluation of several geophysical interpolation schemes for correcting missing or noisy data, (2) development and evaluation of several wavelet compression schemes for removing redundancies from the data, and (3) construction of two neural networks that used the results of steps (1) and (2) to determine the depth and nature of buried objects. This work is a proof-of-concept study that demonstrates the feasibility of this approach. The resulting system was able to determine the nature of buried objects correctly 87% of the time and was able to locate a buried object to within an average error of 0.8 feet. These statistics were gathered based on a large test set and so can be considered reliable. Considering the limited nature of this study, these results strongly indicate the feasibility of this approach, and the importance of appropriate preprocessing of neural network input data.

  7. Artificial Neural Network Analysis of Xinhui Pericarpium Citri ...

    African Journals Online (AJOL)

    Artificial Neural Network Analysis of Xinhui Pericarpium ... Results: The Root Mean Square (RMS) error of GRNN was 0.22, less than the error MLFN at different .... Statistical analysis. To quantify the results of the model, the judgments generated by ANN model were presented as "1" or "0". "1" represents the characteristics of ...

  8. Social Networks and Welfare in Future Animal Management

    Science.gov (United States)

    Koene, Paul; Ipema, Bert

    2014-01-01

    Simple Summary Living in a stable social environment is important to animals. Animal species have developed social behaviors and rules of approach and avoidance of conspecifics in order to co-exist. Animal species are kept or domesticated without explicit regard for their inherent social behavior and rules. Examples of social structures are provided for four species kept and managed by humans. This information is important for the welfare management of these species. In the near future, automatic measurement of social structures will provide a tool for daily welfare management together with nearest neighbor information. Abstract It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for

  9. 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

  10. 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.

  11. Exploiting mineral data: applications to the diversity, distribution, and social networks of copper mineral

    Science.gov (United States)

    Morrison, S. M.; Downs, R. T.; Golden, J. J.; Pires, A.; Fox, P. A.; Ma, X.; Zednik, S.; Eleish, A.; Prabhu, A.; Hummer, D. R.; Liu, C.; Meyer, M.; Ralph, J.; Hystad, G.; Hazen, R. M.

    2016-12-01

    We have developed a comprehensive database of copper (Cu) mineral characteristics. These data include crystallographic, paragenetic, chemical, locality, age, structural complexity, and physical property information for the 689 Cu mineral species approved by the International Mineralogical Association (rruff.info/ima). Synthesis of this large, varied dataset allows for in-depth exploration of statistical trends and visualization techniques. With social network analysis (SNA) and cluster analysis of minerals, we create sociograms and chord diagrams. SNA visualizations illustrate the relationships and connectivity between mineral species, which often form cliques associated with rock type and/or geochemistry. Using mineral ecology statistics, we analyze mineral-locality frequency distribution and predict the number of missing mineral species, visualized with accumulation curves. By assembly of 2-dimensional KLEE diagrams of co-existing elements in minerals, we illustrate geochemical trends within a mineral system. To explore mineral age and chemical oxidation state, we create skyline diagrams and compare trends with varying chemistry. These trends illustrate mineral redox changes through geologic time and correlate with significant geologic occurrences, such as the Great Oxidation Event (GOE) or Wilson Cycles.

  12. 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.

  13. Cluster Analysis Based on Bipartite Network

    Directory of Open Access Journals (Sweden)

    Dawei Zhang

    2014-01-01

    Full Text Available Clustering data has a wide range of applications and has attracted considerable attention in data mining and artificial intelligence. However it is difficult to find a set of clusters that best fits natural partitions without any class information. In this paper, a method for detecting the optimal cluster number is proposed. The optimal cluster number can be obtained by the proposal, while partitioning the data into clusters by FCM (Fuzzy c-means algorithm. It overcomes the drawback of FCM algorithm which needs to define the cluster number c in advance. The method works by converting the fuzzy cluster result into a weighted bipartite network and then the optimal cluster number can be detected by the improved bipartite modularity. The experimental results on artificial and real data sets show the validity of the proposed method.

  14. Intruder Activity Analysis under Unreliable Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Tae-Sic Yoo; Humberto E. Garcia

    2007-09-01

    This paper addresses the problem of counting intruder activities within a monitored domain by a sensor network. The deployed sensors are unreliable. We characterize imperfect sensors with misdetection and false-alarm probabilities. We model intruder activities with Markov Chains. A set of Hidden Markov Models (HMM) models the imperfect sensors and intruder activities to be monitored. A novel sequential change detection/isolation algorithm is developed to detect and isolate a change from an HMM representing no intruder activity to another HMM representing some intruder activities. Procedures for estimating the entry time and the trace of intruder activities are developed. A domain monitoring example is given to illustrate the presented concepts and computational procedures.

  15. A topological analysis of scientific coauthorship networks

    Science.gov (United States)

    Cardillo, Alessio; Scellato, Salvatore; Latora, Vito

    2006-12-01

    We study coauthorship networks based on the preprints submitted to the Los Alamos cond-mat database during the period 2000-2005. In our approach two scientists are considered connected if they have coauthored one or more cond-mat preprints together in the same year. We focus on the characterization of the structural properties of the derived graphs and on the time evolution of such properties. The results show that the cond-mat community has grown over the last six years. This is witnessed by an improvement in the connectivity properties of coauthorship graphs over the years, as confirmed by an increasing size of the largest connected component, of the global efficiency and of the clustering coefficient. We have also found that the graphs are characterized by long-tailed degree and betweenness distributions, assortative degree-degree correlations, and a power-law dependence of the clustering coefficient on the node degree.

  16. Mobile networks for biometric data analysis

    CERN Document Server

    Madrid, Natividad; Seepold, Ralf; Orcioni, Simone

    2016-01-01

    This book showcases new and innovative approaches to biometric data capture and analysis, focusing especially on those that are characterized by non-intrusiveness, reliable prediction algorithms, and high user acceptance. It comprises the peer-reviewed papers from the international workshop on the subject that was held in Ancona, Italy, in October 2014 and featured sessions on ICT for health care, biometric data in automotive and home applications, embedded systems for biometric data analysis, biometric data analysis: EMG and ECG, and ICT for gait analysis. The background to the book is the challenge posed by the prevention and treatment of common, widespread chronic diseases in modern, aging societies. Capture of biometric data is a cornerstone for any analysis and treatment strategy. The latest advances in sensor technology allow accurate data measurement in a non-intrusive way, and in many cases it is necessary to provide online monitoring and real-time data capturing to support a patient’s prevention pl...

  17. Protocol design and analysis for cooperative wireless networks

    CERN Document Server

    Song, Wei; Jin, A-Long

    2017-01-01

    This book focuses on the design and analysis of protocols for cooperative wireless networks, especially at the medium access control (MAC) layer and for crosslayer design between the MAC layer and the physical layer. It highlights two main points that are often neglected in other books: energy-efficiency and spatial random distribution of wireless devices. Effective methods in stochastic geometry for the design and analysis of wireless networks are also explored. After providing a comprehensive review of existing studies in the literature, the authors point out the challenges that are worth further investigation. Then, they introduce several novel solutions for cooperative wireless network protocols that reduce energy consumption and address spatial random distribution of wireless nodes. For each solution, the book offers a clear system model and problem formulation, details of the proposed cooperative schemes, comprehensive performance analysis, and extensive numerical and simulation results that validate th...

  18. 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.

  19. Hydraulic Analysis of Water Distribution Network Using Shuffled Complex Evolution

    Directory of Open Access Journals (Sweden)

    Naser Moosavian

    2014-01-01

    Full Text Available Hydraulic analysis of water distribution networks is an important problem in civil engineering. A widely used approach in steady-state analysis of water distribution networks is the global gradient algorithm (GGA. However, when the GGA is applied to solve these networks, zero flows cause a computation failure. On the other hand, there are different mathematical formulations for hydraulic analysis under pressure-driven demand and leakage simulation. This paper introduces an optimization model for the hydraulic analysis of water distribution networks using a metaheuristic method called shuffled complex evolution (SCE algorithm. In this method, applying if-then rules in the optimization model is a simple way in handling pressure-driven demand and leakage simulation, and there is no need for an initial solution vector which must be chosen carefully in many other procedures if numerical convergence is to be achieved. The overall results indicate that the proposed method has the capability of handling various pipe networks problems without changing in model or mathematical formulation. Application of SCE in optimization model can lead to accurate solutions in pipes with zero flows. Finally, it can be concluded that the proposed method is a suitable alternative optimizer challenging other methods especially in terms of accuracy.

  20. Hybrid modeling and empirical analysis of automobile supply chain network

    Science.gov (United States)

    Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

    2017-05-01

    Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

  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. Architecture Analysis of an FPGA-Based Hopfield Neural Network

    Directory of Open Access Journals (Sweden)

    Miguel Angelo de Abreu de Sousa

    2014-01-01

    Full Text Available Interconnections between electronic circuits and neural computation have been a strongly researched topic in the machine learning field in order to approach several practical requirements, including decreasing training and operation times in high performance applications and reducing cost, size, and energy consumption for autonomous or embedded developments. Field programmable gate array (FPGA hardware shows some inherent features typically associated with neural networks, such as, parallel processing, modular executions, and dynamic adaptation, and works on different types of FPGA-based neural networks were presented in recent years. This paper aims to address different aspects of architectural characteristics analysis on a Hopfield Neural Network implemented in FPGA, such as maximum operating frequency and chip-area occupancy according to the network capacity. Also, the FPGA implementation methodology, which does not employ multipliers in the architecture developed for the Hopfield neural model, is presented, in detail.

  3. Center of attention: A network text analysis of American Sniper

    Directory of Open Access Journals (Sweden)

    Starling Hunter

    2016-06-01

    Full Text Available Network Text Analysis (NTA is a term used to describe a variety of software - supported methods for modeling texts as networks of concepts. In this study we apply NTA to the screenplay of American Sniper, an Academy Award nominee for Best Adapted Screenplay in 2014. Specifically, we est ablish prior expectations as to the key themes associated with war films. We then empirically test whether words associated with the most influentially - positioned nodes in the network signify themes common to the war - film genre. As predicted, we find tha t words and concepts associated with the least constrained nodes in the text network were significantly more likely to be associated with the war genre and significantly less likely to be associated with genres to which the film did not belong.

  4. Social network analysis: foundations and frontiers on advantage.

    Science.gov (United States)

    Burt, Ronald S; Kilduff, Martin; Tasselli, Stefano

    2013-01-01

    We provide an overview of social network analysis focusing on network advantage as a lens that touches on much of the area. For reasons of good data and abundant research, we draw heavily on studies of people in organizations. Advantage is traced to network structure as a proxy for the distribution of variably sticky information in a population. The network around a person indicates the person's access and control in the distribution. Advantage is a function of information breadth, timing, and arbitrage. Advantage is manifest in higher odds of proposing good ideas, more positive evaluations and recognition, higher compensation, and faster promotions. We discuss frontiers of advantage contingent on personality, cognition, embeddedness, and dynamics.

  5. 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.

  6. 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.

  7. Community evolution mining and analysis in social network

    Science.gov (United States)

    Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

    2017-03-01

    With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

  8. Analysis and Comparison of Typical Models within Distribution Network Design

    DEFF Research Database (Denmark)

    Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

    This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....... are covered in the categorisation include fixed vs. general networks, specialised vs. general nodes, linear vs. nonlinear costs, single vs. multi commodity, uncapacitated vs. capacitated activities, single vs. multi modal and static vs. dynamic. The models examined address both strategic and tactical planning...

  9. Heterogeneous Deployment Analysis for Cost-Effective Mobile Network Evolution

    DEFF Research Database (Denmark)

    Coletti, Claudio

    2013-01-01

    -powered base stations is a promising cost-effective solution to considerably enhance user experience. In such a network topology, which is denoted as heterogeneous deployment, the macro layer is expected to provide wider coverage but lower average data speeds whereas small cells are targeted at extending...... network coverage and boosting network capacity in traffic hot-spot areas. The thesis deals with the deployment of both outdoor small cells and indoor femto cells. Amongst the outdoor solution, particular emphasis is put on relay base stations as backhaul costs can be reduced by utilizing LTE spectrum...... statistical models of deployment areas, the performance analysis is carried out in the form of operator case studies for large-scale deployment scenarios, including realistic macro network layouts and inhomogeneous spatial traffic distributions. Deployment of small cells is performed by means of proposed...

  10. MHC haplotype analysis by artificial neural networks.

    Science.gov (United States)

    Bellgard, M I; Tay, G K; Hiew, H L; Witt, C S; Ketheesan, N; Christiansen, F T; Dawkins, R L

    1998-01-01

    Conventional matching is based on numbers of alleles shared between donor and recipient. This approach, however, ignores the degree of relationship between alleles and haplotypes, and therefore the actual degree of difference. To address this problem, we have compared family members using a block matching technique which reflects differences in genomic sequences. All parents and siblings had been genotyped using conventional MHC typing so that haplotypes could be assigned and relatives could be classified as sharing 0, 1 or 2 haplotypes. We trained an Artificial Neural Network (ANN) with subjects from 6 families (85 comparisons) to distinguish between relatives. Using the outputs of the ANN, we developed a score, the Histocompatibility Index (HI), as a measure of the degree of difference. Subjects from a further 3 families (106 profile comparisons) were tested. The HI score for each comparison was plotted. We show that the HI score is trimodal allowing the definition of three populations corresponding to approximately 0, 1 or 2 haplotype sharing. The means and standard deviations of the three populations were found. As expected, comparisons between family members sharing 2 haplotypes resulted in high HI scores with one exception. More interestingly, this approach distinguishes between the 1 and 0 haplotype groups, with some informative exceptions. This distinction was considered too difficult to attempt visually. The approach provides promise in the quantification of degrees of histocompatibility.

  11. Semantic network analysis of vaccine sentiment in online social media.

    Science.gov (United States)

    Kang, Gloria J; Ewing-Nelson, Sinclair R; Mackey, Lauren; Schlitt, James T; Marathe, Achla; Abbas, Kaja M; Swarup, Samarth

    2017-06-22

    To examine current vaccine sentiment on social media by constructing and analyzing semantic networks of vaccine information from highly shared websites of Twitter users in the United States; and to assist public health communication of vaccines. Vaccine hesitancy continues to contribute to suboptimal vaccination coverage in the United States, posing significant risk of disease outbreaks, yet remains poorly understood. We constructed semantic networks of vaccine information from internet articles shared by Twitter users in the United States. We analyzed resulting network topology, compared semantic differences, and identified the most salient concepts within networks expressing positive, negative, and neutral vaccine sentiment. The semantic network of positive vaccine sentiment demonstrated greater cohesiveness in discourse compared to the larger, less-connected network of negative vaccine sentiment. The positive sentiment network centered around parents and focused on communicating health risks and benefits, highlighting medical concepts such as measles, autism, HPV vaccine, vaccine-autism link, meningococcal disease, and MMR vaccine. In contrast, the negative network centered around children and focused on organizational bodies such as CDC, vaccine industry, doctors, mainstream media, pharmaceutical companies, and United States. The prevalence of negative vaccine sentiment was demonstrated through diverse messaging, framed around skepticism and distrust of government organizations that communicate scientific evidence supporting positive vaccine benefits. Semantic network analysis of vaccine sentiment in online social media can enhance understanding of the scope and variability of current attitudes and beliefs toward vaccines. Our study synthesizes quantitative and qualitative evidence from an interdisciplinary approach to better understand complex drivers of vaccine hesitancy for public health communication, to improve vaccine confidence and vaccination coverage

  12. Network analysis of breast cancer progression and reversal using a tree-evolving network algorithm.

    Directory of Open Access Journals (Sweden)

    Ankur P Parikh

    2014-07-01

    Full Text Available The HMT3522 progression series of human breast cells have been used to discover how tissue architecture, microenvironment and signaling molecules affect breast cell growth and behaviors. However, much remains to be elucidated about malignant and phenotypic reversion behaviors of the HMT3522-T4-2 cells of this series. We employed a "pan-cell-state" strategy, and analyzed jointly microarray profiles obtained from different state-specific cell populations from this progression and reversion model of the breast cells using a tree-lineage multi-network inference algorithm, Treegl. We found that different breast cell states contain distinct gene networks. The network specific to non-malignant HMT3522-S1 cells is dominated by genes involved in normal processes, whereas the T4-2-specific network is enriched with cancer-related genes. The networks specific to various conditions of the reverted T4-2 cells are enriched with pathways suggestive of compensatory effects, consistent with clinical data showing patient resistance to anticancer drugs. We validated the findings using an external dataset, and showed that aberrant expression values of certain hubs in the identified networks are associated with poor clinical outcomes. Thus, analysis of various reversion conditions (including non-reverted of HMT3522 cells using Treegl can be a good model system to study drug effects on breast cancer.

  13. A graph-based network-vulnerability analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C. [Sandia National Labs., Albuquerque, NM (United States); Gaylor, T. [3M, Austin, TX (United States). Visual Systems Div.

    1998-01-01

    This report 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 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.

  14. 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.

  15. A graph-based network-vulnerability analysis system

    Energy Technology Data Exchange (ETDEWEB)

    Swiler, L.P.; Phillips, C.; Gaylor, T.

    1998-05-03

    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 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.

  16. Development of Network Analysis and Visualization System for KEGG Pathways

    Directory of Open Access Journals (Sweden)

    Dongmin Seo

    2015-07-01

    Full Text Available Big data refers to informationalization technology for extracting valuable information through the use and analysis of large-scale data and, based on that data, deriving plans for response or predicting changes. With the development of software and devices for next generation sequencing, a vast amount of bioinformatics data has been generated recently. Also, bioinformatics data based big-data technology is rising rapidly as a core technology by the bioinformatician, biologist and big-data scientist. KEGG pathway is bioinformatics data for understanding high-level functions and utilities of the biological system. However, KEGG pathway analysis requires a lot of time and effort because KEGG pathways are high volume and very diverse. In this paper, we proposed a network analysis and visualization system that crawl user interest KEGG pathways, construct a pathway network based on a hierarchy structure of pathways and visualize relations and interactions of pathways by clustering and selecting core pathways from the network. Finally, we construct a pathway network collected by starting with an Alzheimer’s disease pathway and show the results on clustering and selecting core pathways from the pathway network.

  17. Temporal Sequence of Hemispheric Network Activation during Semantic Processing: A Functional Network Connectivity Analysis

    Science.gov (United States)

    Assaf, Michal; Jagannathan, Kanchana; Calhoun, Vince; Kraut, Michael; Hart, John, Jr.; Pearlson, Godfrey

    2009-01-01

    To explore the temporal sequence of, and the relationship between, the left and right hemispheres (LH and RH) during semantic memory (SM) processing we identified the neural networks involved in the performance of functional MRI semantic object retrieval task (SORT) using group independent component analysis (ICA) in 47 healthy individuals. SORT…

  18. Predicting disease associations via biological network analysis.

    Science.gov (United States)

    Sun, Kai; Gonçalves, Joana P; Larminie, Chris; Przulj, Nataša

    2014-09-17

    Understanding the relationship between diseases based on the underlying biological mechanisms is one of the greatest challenges in modern biology and medicine. Exploring disease-disease associations by using system-level biological data is expected to improve our current knowledge of disease relationships, which may lead to further improvements in disease diagnosis, prognosis and treatment. We took advantage of diverse biological data including disease-gene associations and a large-scale molecular network to gain novel insights into disease relationships. We analysed and compared four publicly available disease-gene association datasets, then applied three disease similarity measures, namely annotation-based measure, function-based measure and topology-based measure, to estimate the similarity scores between diseases. We systematically evaluated disease associations obtained by these measures against a statistical measure of comorbidity which was derived from a large number of medical patient records. Our results show that the correlation between our similarity measures and comorbidity scores is substantially higher than expected at random, confirming that our similarity measures are able to recover comorbidity associations. We also demonstrated that our predicted disease associations correlated with disease associations generated from genome-wide association studies significantly higher than expected at random. Furthermore, we evaluated our predicted disease associations via mining the literature on PubMed, and presented case studies to demonstrate how these novel disease associations can be used to enhance our current knowledge of disease relationships. We present three similarity measures for predicting disease associations. The strong correlation between our predictions and known disease associations demonstrates the ability of our measures to provide novel insights into disease relationships.

  19. Green pathways: Metabolic network analysis of plant systems.

    Science.gov (United States)

    Dersch, Lisa Maria; Beckers, Veronique; Wittmann, Christoph

    2016-03-01

    Metabolic engineering of plants with enhanced crop yield and value-added compositional traits is particularly challenging as they probably exhibit the highest metabolic network complexity of all living organisms. Therefore, approaches of plant metabolic network analysis, which can provide systems-level understanding of plant physiology, appear valuable as guidance for plant metabolic engineers. Strongly supported by the sequencing of plant genomes, a number of different experimental and computational methods have emerged in recent years to study plant systems at various levels: from heterotrophic cell cultures to autotrophic entire plants. The present review presents a state-of-the-art toolbox for plant metabolic network analysis. Among the described approaches are different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes. The fundamental principles of these techniques, the required data input and the obtained flux information are enriched by technical advices, specific to plants. In addition, pioneering and high-impacting findings of plant metabolic network analysis highlight the potential of the field. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

  20. Bayesian networks for omics data analysis

    NARCIS (Netherlands)

    Gavai, A.K.

    2009-01-01

    This thesis focuses on two aspects of high throughput technologies, i.e. data storage and data analysis, in particular in transcriptomics and metabolomics. Both technologies are part of a research field that is generally called ‘omics’ (or ‘-omics’, with a leading hyphen), which refers to genomics,

  1. [Numerical analysis on network characteristics of communities in herb-pairs network].

    Science.gov (United States)

    Cao, Jia; Xin, Juan-juan; Wang, Yun

    2015-06-01

    To interpret the traditional Chinese medicine (TCM) theory by the network technology, in order to promote the modernization and programming of studies on compatibility of TCMs. In this paper, efforts were made to express the direct interactions between drugs through the herb-pair network, analyze the community characteristics of the network and its relations with blood-Qi theory, and study the expression of blood-Qi theory on the herb-pair network through prescriptions. According to the findings, the herb-pairs network showed a strong community structure characteristics; Each community is composed of a series of herb pairs with close correlations, and either blood efficacy or Qi efficacy but not both of them. Based on that, the 386 single TCM ingredients involved by the herb-pair network were divided into three types of communities: Blood (B) community, Qi (Q) community and uncertain community. According to the statistical results of 262 prescriptions mapped onto the three types of communities, if a prescription contains single herbs of the Q community, the probability that it contains single herbs o the B community is 99.84%; Meanwhile, there are 140 prescriptions containing single herbs of both the Q community and the B community. The result is completely coincident with the TCM Blood-Qi theory that single herbs belong to both Q and B communities or the B community, because Qi regulation leads to blood regulation, but not vice versa. For example, a patient with hemorrhage due to trauma or blood-heat, Qi tonifying prescriptions may aggravate hemorrhage. In this paper, authors found high-recognition macroscopic network numerical characteristics to network data reference for judging rationality of new prescriptions, and proved human blood and Qi relations from the perspective of data analysis.

  2. The Design and Analysis of Virtual Network Configuration for a Wireless Mobile ATM Network

    Science.gov (United States)

    Bush, Stephen F.

    1999-05-01

    This research concentrates on the design and analysis of an algorithm referred to as Virtual Network Configuration (VNC) which uses predicted future states of a system for faster network configuration and management. VNC is applied to the configuration of a wireless mobile ATM network. VNC is built on techniques from parallel discrete event simulation merged with constraints from real-time systems and applied to mobile ATM configuration and handoff. Configuration in a mobile network is a dynamic and continuous process. Factors such as load, distance, capacity and topology are all constantly changing in a mobile environment. The VNC algorithm anticipates configuration changes and speeds the reconfiguration process by pre-computing and caching results. VNC propagates local prediction results throughout the VNC enhanced system. The Global Positioning System is an enabling technology for the use of VNC in mobile networks because it provides location information and accurate time for each node. This research has resulted in well defined structures for the encapsulation of physical processes within Logical Processes and a generic library for enhancing a system with VNC. Enhancing an existing system with VNC is straight forward assuming the existing physical processes do not have side effects. The benefit of prediction is gained at the cost of additional traffic and processing. This research includes an analysis of VNC and suggestions for optimization of the VNC algorithm and its parameters.

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

    Directory of Open Access Journals (Sweden)

    Datta Somnath

    2010-02-01

    Full Text Available Abstract Background It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types. Results We provide a recipe for conducting a differential analysis of networks constructed from microarray data under two experimental settings. At the core of our approach lies a connectivity score that represents the strength of genetic association or interaction between two genes. We use this score to propose formal statistical tests for each of following queries: (i whether the overall modular structures of the two networks are different, (ii whether the connectivity of a particular set of "interesting genes" has changed between the two networks, and (iii whether the connectivity of a given single gene has changed between the two networks. A number of examples of this score is provided. We carried out our method on two types of simulated data: Gaussian networks and networks based on differential equations. We show that, for appropriate choices of the connectivity scores and tuning parameters, our method works well on simulated data. We also analyze a real data set involving normal versus heavy mice and identify an interesting set of genes that may play key roles in obesity. Conclusions Examining changes in network structure can provide valuable information about the

  4. Network analysis shining light on parasite ecology and diversity.

    Science.gov (United States)

    Poulin, Robert

    2010-10-01

    The vast number of species making up natural communities, and the myriad interactions among them, pose great difficulties for the study of community structure, dynamics and stability. Borrowed from other fields, network analysis is making great inroads in community ecology and is only now being applied to host-parasite interactions. It allows a complex system to be examined in its entirety, as opposed to one or a few components at a time. This review explores what network analysis is and how it can be used to investigate parasite ecology. It also summarizes the first findings to emerge from network analyses of host-parasite interactions and identifies promising future directions made possible by this approach. Copyright © 2010 Elsevier Ltd. All rights reserved.

  5. 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

  6. [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.

  7. Utilization of Selected Data Mining Methods for Communication Network Analysis

    Directory of Open Access Journals (Sweden)

    V. Ondryhal

    2011-06-01

    Full Text Available The aim of the project was to analyze the behavior of military communication networks based on work with real data collected continuously since 2005. With regard to the nature and amount of the data, data mining methods were selected for the purpose of analyses and experiments. The quality of real data is often insufficient for an immediate analysis. The article presents the data cleaning operations which have been carried out with the aim to improve the input data sample to obtain reliable models. Gradually, by means of properly chosen SW, network models were developed to verify generally valid patterns of network behavior as a bulk service. Furthermore, unlike the commercially available communication networks simulators, the models designed allowed us to capture nonstandard models of network behavior under an increased load, verify the correct sizing of the network to the increased load, and thus test its reliability. Finally, based on previous experience, the models enabled us to predict emergency situations with a reasonable accuracy.

  8. Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

    Directory of Open Access Journals (Sweden)

    Firoozeh Zare-Farashbandi

    2014-01-01

    Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

  9. Who Is Citing Whom: Citation Network Analysis among HRD Publications from 1990 to 2007

    Science.gov (United States)

    Jo, Sung Jun; Jeung, Chang-Wook; Park, Sunyoung; Yoon, Hea Jun

    2009-01-01

    A citation network analysis among four journals in human resource development (HRD) was conducted to discover the major themes of published articles in HRD. A total of 1,410 articles from 1990 to 2007 were coded. Main path analysis, influence analysis, and reduced network analysis were conducted for citation network analysis. The key findings are…

  10. 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...

  11. Role of Communication Networks in Behavioral Systems Analysis

    Science.gov (United States)

    Houmanfar, Ramona; Rodrigues, Nischal Joseph; Smith, Gregory S.

    2009-01-01

    This article provides an overview of communication networks and the role of verbal behavior in behavioral systems analysis. Our discussion highlights styles of leadership in the design and implementation of effective organizational contingencies that affect ways by which coordinated work practices are managed. We draw upon literature pertaining to…

  12. Globalization and International Student Mobility: A Network Analysis

    Science.gov (United States)

    Shields, Robin

    2013-01-01

    This article analyzes changes to the network of international student mobility in higher education over a 10-year period (1999-2008). International student flows have increased rapidly, exceeding 3 million in 2009, and extensive data on mobility provide unique insight into global educational processes. The analysis is informed by three theoretical…

  13. Improving Family Forest Knowledge Transfer through Social Network Analysis

    Science.gov (United States)

    Gorczyca, Erika L.; Lyons, Patrick W.; Leahy, Jessica E.; Johnson, Teresa R.; Straub, Crista L.

    2012-01-01

    To better engage Maine's family forest landowners our study used social network analysis: a computational social science method for identifying stakeholders, evaluating models of engagement, and targeting areas for enhanced partnerships. Interviews with researchers associated with a research center were conducted to identify how social network…

  14. Social Network Analysis of the Farabi Exchange Program: Student Mobility

    Science.gov (United States)

    Ugurlu, Zeynep

    2016-01-01

    Problem Statement: Exchange programs offer communication channels created through student and instructor exchanges; a flow of information takes place through these channels. The Farabi Exchange Program (FEP) is a student and instructor exchange program between institutions of higher education. Through the use of social network analysis and…

  15. Network topology and resilience analysis of South Korean power grid

    Science.gov (United States)

    Kim, Dong Hwan; Eisenberg, Daniel A.; Chun, Yeong Han; Park, Jeryang

    2017-01-01

    In this work, we present topological and resilience analyses of the South Korean power grid (KPG) with a broad voltage level. While topological analysis of KPG only with high-voltage infrastructure shows an exponential degree distribution, providing another empirical evidence of power grid topology, the inclusion of low voltage components generates a distribution with a larger variance and a smaller average degree. This result suggests that the topology of a power grid may converge to a highly skewed degree distribution if more low-voltage data is considered. Moreover, when compared to ER random and BA scale-free networks, the KPG has a lower efficiency and a higher clustering coefficient, implying that highly clustered structure does not necessarily guarantee a functional efficiency of a network. Error and attack tolerance analysis, evaluated with efficiency, indicate that the KPG is more vulnerable to random or degree-based attacks than betweenness-based intentional attack. Cascading failure analysis with recovery mechanism demonstrates that resilience of the network depends on both tolerance capacity and recovery initiation time. Also, when the two factors are fixed, the KPG is most vulnerable among the three networks. Based on our analysis, we propose that the topology of power grids should be designed so the loads are homogeneously distributed, or functional hubs and their neighbors have high tolerance capacity to enhance resilience.

  16. Network analysis of wildfire transmission and implications for risk governance

    Science.gov (United States)

    Alan A. Ager; Cody R. Evers; Michelle A. Day; Haiganoush K. Preisler; Ana M. G. Barros; Max. Nielsen-Pincus

    2017-01-01

    We characterized wildfire transmission and exposure within a matrix of large land tenures (federal, state, and private) surrounding 56 communities within a 3.3 million ha fire prone region of central Oregon US. Wildfire simulation and network analysis were used to quantify the exchange of fire among land tenures and communities and analyze the relative contributions of...

  17. Analysis of Degree 5 Chordal Rings for Network Topologies

    DEFF Research Database (Denmark)

    Riaz, M. Tahir; Pedersen, Jens Myrup; Bujnowski, Sławomir

    2011-01-01

    This paper presents an analysis of degree 5 chordal rings, from a network topology point of view. The chordal rings are mainly evaluated with respect to average distance and diameter. We derive approximation expressions for the related ideal graphs, and show that these matches the real chordal ri...

  18. Reconstructing networks of pathways via significance analysis of their intersections

    Directory of Open Access Journals (Sweden)

    Francesconi Mirko

    2008-04-01

    Full Text Available Abstract Background Significance analysis at single gene level may suffer from the limited number of samples and experimental noise that can severely limit the power of the chosen statistical test. This problem is typically approached by applying post hoc corrections to control the false discovery rate, without taking into account prior biological knowledge. Pathway or gene ontology analysis can provide an alternative way to relax the significance threshold applied to single genes and may lead to a better biological interpretation. Results Here we propose a new analysis method based on the study of networks of pathways. These networks are reconstructed considering both the significance of single pathways (network nodes and the intersection between them (links. We apply this method for the reconstruction of networks of pathways to two gene expression datasets: the first one obtained from a c-Myc rat fibroblast cell line expressing a conditional Myc-estrogen receptor oncoprotein; the second one obtained from the comparison of Acute Myeloid Leukemia and Acute Lymphoblastic Leukemia derived from bone marrow samples. Conclusion Our method extends statistical models that have been recently adopted for the significance analysis of functional groups of genes to infer links between these groups. We show that groups of genes at the interface between different pathways can be considered as relevant even if the pathways they belong to are not significant by themselves.

  19. Characterizing naval team readiness through social network analysis

    NARCIS (Netherlands)

    Schraagen, J.M.C.; Post, W.M.

    2014-01-01

    Characterizing a team’s level of readiness in an efficient and objective way is important for organizations such as the military. Current methods to characterize real-time team interaction know limitations that may be addressed by social network analysis techniques. The purpose of the current field

  20. Locality Based Analysis of Network Flows

    Science.gov (United States)

    2004-07-21

    University Noise localities • We have been characterizing modest subnets in support of the traffic generation that will be used in the DARPA DQ system...University Software Engineering Institute © 2004 by Carnegie Mellon University Crud and Noise • In January, we observed a /16 for a week, and the whole...some examples of locality on a variety of scales for a variety of representations. • It is our hope that the general notions of locality, and clustering will provide a basis for reducing the complexity of analysis.

  1. Transnational Research Networks in Chinese Scientific Production. An Investigation on Health-Industry Related Sectors

    Directory of Open Access Journals (Sweden)

    Lauretta Rubini

    2017-08-01

    Full Text Available Transnational research networks (TRN are becoming increasingly complex. Such complexity may have both positive and negative effects on the quality of research. Our work studies the evolution over time of Chinese TRN and the role of complexity on the quality of Chinese research, given the leading role this country has recently acquired in international science. We focus on the fields of geriatrics and gerontology. We build an original dataset of all scientific publications of China in these areas in 2009, 2012 and 2015, starting from the ISI Web of Knowledge (ISI WoK database. Using Social Network Analysis (SNA, we analyze the change in scientific network structure across time. Second, we design indices to control for the different aspects of networks complexity (number of authors, country heterogeneity and institutional heterogeneity and we perform negative binomial regressions to identify the main determinants of research quality. Our analysis shows that research networks in the field of geriatrics and gerontology have gradually become wider in terms of countries and have become more balanced. Furthermore, our results identify that different forms of complexity have different impacts on quality, including a reciprocal moderating effect. In particular, according to our analysis, research quality benefits from complex research networks both in terms of countries and of types of institutions involved, but that such networks should be “compact” in terms of number of authors. Eventually, we suggest that complexity should be carefully taken into account when designing policies aimed at enhancing the quality of research.

  2. Transnational Research Networks in Chinese Scientific Production. An Investigation on Health-Industry Related Sectors.

    Science.gov (United States)

    Rubini, Lauretta; Pollio, Chiara; Di Tommaso, Marco R

    2017-08-29

    Transnational research networks (TRN) are becoming increasingly complex. Such complexity may have both positive and negative effects on the quality of research. Our work studies the evolution over time of Chinese TRN and the role of complexity on the quality of Chinese research, given the leading role this country has recently acquired in international science. We focus on the fields of geriatrics and gerontology. We build an original dataset of all scientific publications of China in these areas in 2009, 2012 and 2015, starting from the ISI Web of Knowledge (ISI WoK) database. Using Social Network Analysis (SNA), we analyze the change in scientific network structure across time. Second, we design indices to control for the different aspects of networks complexity (number of authors, country heterogeneity and institutional heterogeneity) and we perform negative binomial regressions to identify the main determinants of research quality. Our analysis shows that research networks in the field of geriatrics and gerontology have gradually become wider in terms of countries and have become more balanced. Furthermore, our results identify that different forms of complexity have different impacts on quality, including a reciprocal moderating effect. In particular, according to our analysis, research quality benefits from complex research networks both in terms of countries and of types of institutions involved, but that such networks should be "compact" in terms of number of authors. Eventually, we suggest that complexity should be carefully taken into account when designing policies aimed at enhancing the quality of research.

  3. Narcissism and Social Networking Behavior: A Meta-Analysis.

    Science.gov (United States)

    Gnambs, Timo; Appel, Markus

    2017-02-07

    The increasing popularity of social networking sites (SNS) such as Facebook and Twitter has given rise to speculations that the intensity of using these platforms is associated with narcissistic tendencies. However, recent research on this issue has been all but conclusive. We present a three-level, random effects meta-analysis including 289 effect sizes from 57 studies (total N = 25,631) on the association between trait narcissism and social networking behavior. The meta-analysis identified a small to moderate effect of ρ = .17 (τ = .11), 95% CI [.13, .21], for grandiose narcissism that replicated across different social networking platforms, respondent characteristics, and time. Moderator analyses revealed pronounced cultural differences, with stronger associations in power-distant cultures. Moreover, social networking behaviors geared toward self-presentation and the number of SNS friends exhibited stronger effects than usage durations. Overall, the study not only supported but also refined the notion of a relationship between engaging in social networking sites and narcissistic personality traits. © 2017 Wiley Periodicals, Inc.

  4. Automated analysis of Physarum network structure and dynamics

    Science.gov (United States)

    Fricker, Mark D.; Akita, Dai; Heaton, Luke LM; Jones, Nick; Obara, Boguslaw; Nakagaki, Toshiyuki

    2017-06-01

    We evaluate different ridge-enhancement and segmentation methods to automatically extract the network architecture from time-series of Physarum plasmodia withdrawing from an arena via a single exit. Whilst all methods gave reasonable results, judged by precision-recall analysis against a ground-truth skeleton, the mean phase angle (Feature Type) from intensity-independent, phase-congruency edge enhancement and watershed segmentation was the most robust to variation in threshold parameters. The resultant single pixel-wide segmented skeleton was converted to a graph representation as a set of weighted adjacency matrices containing the physical dimensions of each vein, and the inter-vein regions. We encapsulate the complete image processing and network analysis pipeline in a downloadable software package, and provide an extensive set of metrics that characterise the network structure, including hierarchical loop decomposition to analyse the nested structure of the developing network. In addition, the change in volume for each vein and intervening plasmodial sheet was used to predict the net flow across the network. The scaling relationships between predicted current, speed and shear force with vein radius were consistent with predictions from Murray’s law. This work was presented at PhysNet 2015.

  5. Complex network analysis of extreme precipitation over the Indian subcontinent.

    Science.gov (United States)

    Stolbova, Veronika; Kurths, Jürgen

    2013-04-01

    The Indian monsoon is a large scale pattern in the climate system of the Earth. The motivation of our work was to reveal spatial structures in strong precipitation over the Indian subcontinent, and their evolution during the year, because it is crucial as for understanding of monsoon regularities as well for India's agriculture and economy. We present an analysis of extreme rainfall over the Indian peninsula and Sri Lanka. Using the method of event synchronization we constructed networks of extreme rainfall events(heavier than the 90-th percentile) for three time periods: during the Indian summer monsoon (ISM, June-September), the Northeast monsoon (NEM, October - December, so called winter monsoon) and period before the summer monsoon (January - May). Obtained networks show how extreme rainfall for specific areas in India is synchronized with extreme rainfall for other areas in India. Analysis of degree centrality of the networks reveals clusters of extreme rainfall events in India which are strongly connected to maximal number of other areas with extreme rainfall events, e.g., North Pakistan and the Eastern Ghats. Additionally, betweenness centrality shows areas that are important in the sense of water transport in the networks (e.g. the Himalayas, Western Ghats, Eastern Ghats etc.). By comparison of networks before the summer monsoon, during summer and winter monsoon season we determined how spatial patterns of rainfalls synchronization change during the year. These changes play a crucial role in the organization of the rainfall all over the Indian subcontinent.

  6. Static Voltage Stability Analysis by Using SVM and Neural Network

    Directory of Open Access Journals (Sweden)

    Mehdi Hajian

    2013-01-01

    Full Text Available Voltage stability is an important problem in power system networks. In this paper, in terms of static voltage stability, and application of Neural Networks (NN and Supported Vector Machine (SVM for estimating of voltage stability margin (VSM and predicting of voltage collapse has been investigated. This paper considers voltage stability in power system in two parts. The first part calculates static voltage stability margin by Radial Basis Function Neural Network (RBFNN. The advantage of the used method is high accuracy in online detecting the VSM. Whereas the second one, voltage collapse analysis of power system is performed by Probabilistic Neural Network (PNN and SVM. The obtained results in this paper indicate, that time and number of training samples of SVM, are less than NN. In this paper, a new model of training samples for detection system, using the normal distribution load curve at each load feeder, has been used. Voltage stability analysis is estimated by well-know L and VSM indexes. To demonstrate the validity of the proposed methods, IEEE 14 bus grid and the actual network of Yazd Province are used.

  7. Multiplex network analysis of employee performance and employee social relationships

    Science.gov (United States)

    Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene

    2018-01-01

    In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.

  8. Smoking-based selection and influence in gender-segregated friendship networks : a social network analysis of adolescent smoking

    NARCIS (Netherlands)

    Mercken, Liesbeth; Snijders, Tom A. B.; Steglich, Christian; Vertiainen, Erkki; Vartiainen, E.; De Vries, H.

    Aims The main goal of this study was to examine differences between adolescent male and female friendship networks regarding smoking-based selection and influence processes using newly developed social network analysis methods that allow the current state of continuously changing friendship networks

  9. Discovering Collaborative Cyber Attack Patterns Using Social Network Analysis

    Science.gov (United States)

    Du, Haitao; Yang, Shanchieh Jay

    This paper investigates collaborative cyber attacks based on social network analysis. An Attack Social Graph (ASG) is defined to represent cyber attacks on the Internet. Features are extracted from ASGs to analyze collaborative patterns. We use principle component analysis to reduce the feature space, and hierarchical clustering to group attack sources that exhibit similar behavior. Experiments with real world data illustrate that our framework can effectively reduce from large dataset to clusters of attack sources exhibiting critical collaborative patterns.

  10. Globalization and international student mobility:a network analysis

    OpenAIRE

    Shields, Robin

    2013-01-01

    This article analyzes changes to the network of international student mobility in higher education over a 10-year period (1999–2008). International student flows have increased rapidly, exceeding 3 million in 2009, and extensive data on mobility provide unique insight into global educational processes. The analysis is informed by three theoretical conceptualizations of globalization: neoliberalism, critical perspectives (e.g., world-systems analysis and poststructuralism), and world culture t...

  11. 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).

  12. 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

  13. 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.

  14. Sample EP Flow Analysis of Severely Damaged Networks

    Energy Technology Data Exchange (ETDEWEB)

    Werley, Kenneth Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); McCown, Andrew William [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-10-12

    These are slides for a presentation at the working group meeting of the WESC SREMP Software Product Integration Team on sample EP flow analysis of severely damaged networks. The following topics are covered: ERCOT EP Transmission Model; Zoomed in to Houston and Overlaying StreetAtlas; EMPACT Solve/Dispatch/Shedding Options; QACS BaseCase Power Flow Solution; 3 Substation Contingency; Gen. & Load/100 Optimal Dispatch; Dispatch Results; Shed Load for Low V; Network Damage Summary; Estimated Service Areas (Potential); Estimated Outage Areas (potential).

  15. Spatial Analysis Along Networks Statistical and Computational Methods

    CERN Document Server

    Okabe, Atsuyuki

    2012-01-01

    In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Process

  16. Management of the Space Physics Analysis Network (SPAN)

    Science.gov (United States)

    Green, James L.; Thomas, Valerie L.; Butler, Todd F.; Peters, David J.; Sisson, Patricia L.

    1990-01-01

    Here, the purpose is to define the operational management structure and to delineate the responsibilities of key Space Physics Analysis Network (SPAN) individuals. The management structure must take into account the large NASA and ESA science research community by giving them a major voice in the operation of the system. Appropriate NASA and ESA interfaces must be provided so that there will be adequate communications facilities available when needed. Responsibilities are delineated for the Advisory Committee, the Steering Committee, the Project Scientist, the Project Manager, the SPAN Security Manager, the Internetwork Manager, the Network Operations Manager, the Remote Site Manager, and others.

  17. 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

  18. Robustness of metabolic networks: Flux balance analysis

    Science.gov (United States)

    Jeong, Hawoong

    2005-03-01

    Biological systems are unimaginably complex, yet also highly robust to genetic perturbations on all levels of organization. For example, the cellular metabolism of the bacterium E. coli maintains its homeostasis, often with little or no effect on the biomass yield under a considerable portion of single gene knockouts. To address the interplay between the robustness of the final biomass yield and the underlying mechanisms in the intracellular metabolism, we identify the set of intracellular metabolites of which presences are essential for the cellular- level viability via flux balance analysis. These essential metabolites exhibit the quite different characteristics both in the topological and physiological aspects of the participating reactions, compared with the case for the non-essential ones. Most importantly, it is revealed that in viable case, production and consumption rates of each essential metabolite acquire their robustness responding to the genetic perturbations, by actively reorganizing the reaction fluxes for the ultimate robustness of the biomass yield. We also find that there is strong correlation between essentiality and flux fluctuation of metabolite under the gene deletion purturbations.

  19. Global analysis of photosynthesis transcriptional regulatory networks.

    Science.gov (United States)

    Imam, Saheed; Noguera, Daniel R; Donohue, Timothy J

    2014-12-01

    Photosynthesis is a crucial biological process that depends on the interplay of many components. This work analyzed the gene targets for 4 transcription factors: FnrL, PrrA, CrpK and MppG (RSP_2888), which are known or predicted to control photosynthesis in Rhodobacter sphaeroides. Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) identified 52 operons under direct control of FnrL, illustrating its regulatory role in photosynthesis, iron homeostasis, nitrogen metabolism and regulation of sRNA synthesis. Using global gene expression analysis combined with ChIP-seq, we mapped the regulons of PrrA, CrpK and MppG. PrrA regulates ∼34 operons encoding mainly photosynthesis and electron transport functions, while CrpK, a previously uncharacterized Crp-family protein, regulates genes involved in photosynthesis and maintenance of iron homeostasis. Furthermore, CrpK and FnrL share similar DNA binding determinants, possibly explaining our observation of the ability of CrpK to partially compensate for the growth defects of a ΔFnrL mutant. We show that the Rrf2 family protein, MppG, plays an important role in photopigment biosynthesis, as part of an incoherent feed-forward loop with PrrA. Our results reveal a previously unrealized, high degree of combinatorial regulation of photosynthetic genes and significant cross-talk between their transcriptional regulators, while illustrating previously unidentified links between photosynthesis and the maintenance of iron homeostasis.

  20. Network Analysis: A Novel Approach to Understand Suicidal Behaviour

    Directory of Open Access Journals (Sweden)

    Derek de Beurs

    2017-02-01

    Full Text Available Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behaviour, but we do not yet understand how their interaction increases the risk for suicidal behaviour. A new approach called network analysis can help us better understand this process as it allows us to visualize and quantify the complex association between many different symptoms or risk factors. A network analysis of data containing information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies.