Science.gov

Sample records for network analysis program

  1. Social Network Analysis for Program Implementation

    PubMed Central

    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. PMID:26110842

  2. Social network analysis for program implementation.

    PubMed

    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. PMID:26110842

  3. Computer program for compressible flow network analysis

    NASA Technical Reports Server (NTRS)

    Wilton, M. E.; Murtaugh, J. P.

    1973-01-01

    Program solves problem of an arbitrarily connected one dimensional compressible flow network with pumping in the channels and momentum balancing at flow junctions. Program includes pressure drop calculations for impingement flow and flow through pin fin arrangements, as currently found in many air cooled turbine bucket and vane cooling configurations.

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

    PubMed

    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. PMID:25462609

  5. Faculty Hiring at Top-Ranked Higher Education Administration Programs: An Examination Using Social Network Analysis

    ERIC Educational Resources Information Center

    DiRamio, David; Theroux, Ryan; Guarino, Anthony J.

    2009-01-01

    Using network analysis we investigated faculty hiring at 21 U. S. News top-ranked programs in higher education administration. Our research questions were as follows. Do top programs hire from each other? Are faculty from the "outside" finding positions at top programs? Mixed results hint at implications for the "health" of the hiring network.…

  6. Network Children's Programming; A Content Analysis of Black and Minority Treatment on Children's Television.

    ERIC Educational Resources Information Center

    Mendelson, Gilbert; Young, Morissa

    A content analysis of network children's programming was undertaken on three consecutive Saturdays in November, 1971, with a total of 14-1/2 hours of programs being videotaped. Each program was then viewed by monitors who judged particularly about racial and ethnic characteristics of program content. Findings were that over 60 percent of the shows…

  7. STICAP: A linear circuit analysis program with stiff systems capability. Volume 1: Theory manual. [network analysis

    NASA Technical Reports Server (NTRS)

    Cooke, C. H.

    1975-01-01

    STICAP (Stiff Circuit Analysis Program) is a FORTRAN 4 computer program written for the CDC-6400-6600 computer series and SCOPE 3.0 operating system. It provides the circuit analyst a tool for automatically computing the transient responses and frequency responses of large linear time invariant networks, both stiff and nonstiff (algorithms and numerical integration techniques are described). The circuit description and user's program input language is engineer-oriented, making simple the task of using the program. Engineering theories underlying STICAP are examined. A user's manual is included which explains user interaction with the program and gives results of typical circuit design applications. Also, the program structure from a systems programmer's viewpoint is depicted and flow charts and other software documentation are given.

  8. Interfacing a General Purpose Fluid Network Flow Program with the SINDA/G Thermal Analysis Program

    NASA Technical Reports Server (NTRS)

    Schallhorn, Paul; Popok, Daniel

    1999-01-01

    A general purpose, one dimensional fluid flow code is currently being interfaced with the thermal analysis program Systems Improved Numerical Differencing Analyzer/Gaski (SINDA/G). The flow code, Generalized Fluid System Simulation Program (GFSSP), is capable of analyzing steady state and transient flow in a complex network. The flow code is capable of modeling several physical phenomena including compressibility effects, phase changes, body forces (such as gravity and centrifugal) and mixture thermodynamics for multiple species. The addition of GFSSP to SINDA/G provides a significant improvement in convective heat transfer modeling for SINDA/G. The interface development is conducted in multiple phases. This paper describes the first phase of the interface which allows for steady and quasi-steady (unsteady solid, steady fluid) conjugate heat transfer modeling.

  9. Strengthening Prevention Program Theories and Evaluations: Contributions from Social Network Analysis

    PubMed Central

    Gest, Scott D.; Osgood, D. Wayne; Feinberg, Mark; Bierman, Karen L.; Moody, James

    2011-01-01

    A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools’ organizational, cultural or instructional systems that influence children’s relationships), or implicitly (e.g., by altering behavioral norms designed to influence children’s social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science – both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts. PMID:21728069

  10. Strengthening prevention program theories and evaluations: contributions from social network analysis.

    PubMed

    Gest, Scott D; Osgood, D Wayne; Feinberg, Mark E; Bierman, Karen L; Moody, James

    2011-12-01

    A majority of school-based prevention programs target the modification of setting-level social dynamics, either explicitly (e.g., by changing schools' organizational, cultural or instructional systems that influence children's relationships), or implicitly (e.g., by altering behavioral norms designed to influence children's social affiliations and interactions). Yet, in outcome analyses of these programs, the rich and complicated set of peer network dynamics is often reduced to an aggregation of individual characteristics or assessed with methods that do not account for the interdependencies of network data. In this paper, we present concepts and analytic methods from the field of social network analysis and illustrate their great value to prevention science--both as a source of tools for refining program theories and as methods that enable more sophisticated and focused tests of intervention effects. An additional goal is to inform discussions of the broader implications of social network analysis for public health efforts. PMID:21728069

  11. Data and programs in support of network analysis of genes and their association with diseases.

    PubMed

    Kontou, Panagiota I; Pavlopoulou, Athanasia; Dimou, Niki L; Pavlopoulos, Georgios A; Bagos, Pantelis G

    2016-09-01

    The network-based approaches that were employed in order to depict the relationships between human genetic diseases and their associated genes are described. Towards this direction, monopartite disease-disease and gene-gene networks were constructed from bipartite gene-disease association networks. The latter were created by collecting and integrating data from three diverse resources, each one with different content, covering from rare monogenic disorders to common complex diseases. Moreover, topological and clustering graph analyses were performed. The methodology and the programs presented in this article are related to the research article entitled "Network analysis of genes and their association with diseases" [1]. PMID:27508260

  12. Networks Analysis of a Regional Ecosystem of Afterschool Programs

    ERIC Educational Resources Information Center

    Russell, Martha G.; Smith, Marc A.

    2011-01-01

    Case studies have documented the impact of family-school-community collaboration in afterschool programs on increasing awareness about the problems of at-risk youth, initiating dialogue among leaders and community representatives, developing rich school-based information systems, and demonstrating how to build strong relationships between public…

  13. Generalized Fluid System Simulation Program (GFSSP) Version 6 - General Purpose Thermo-Fluid Network Analysis Software

    NASA Technical Reports Server (NTRS)

    Majumdar, Alok; Leclair, Andre; Moore, Ric; Schallhorn, Paul

    2011-01-01

    GFSSP stands for Generalized Fluid System Simulation Program. It is a general-purpose computer program to compute pressure, temperature and flow distribution in a flow network. GFSSP calculates pressure, temperature, and concentrations at nodes and calculates flow rates through branches. It was primarily developed to analyze Internal Flow Analysis of a Turbopump Transient Flow Analysis of a Propulsion System. GFSSP development started in 1994 with an objective to provide a generalized and easy to use flow analysis tool for thermo-fluid systems.

  14. Computer network programming

    SciTech Connect

    Hsu, J.Y.

    1996-12-31

    The programs running on a computer network can be divided into two parts, the Network Operating System and the user applications. Any high level language translator, such as C, JAVA, BASIC, FORTRAN, or COBOL, runs under NOS as a programming tool to produce network application programs or software. Each application program while running on the network provides the human user with network application services, such as remote data base search, retrieval, etc. The Network Operating System should provide a simple and elegant system interface to all the network application programs. This programming interface may request the Transport layer services on behalf of a network application program. The primary goals are to achieve programming convenience, and to avoid complexity. In a 5-layer network model, the system interface is comprised of a group of system calls which are collectively known as the session layer with its own Session Protocol Data Units. This is a position paper discussing the basic system primitives which reside between a network application program and the Transport layer, and a programming example of using such primitives.

  15. Networks consolidation program

    NASA Technical Reports Server (NTRS)

    Yeater, M. L.; Herman, D. T.; Luers, E. B.

    1982-01-01

    Progress in the networks consolidations program (NCP) to combine the resources of the two NASA ground spacecraft tracking networks (the Deep Space Network, operated by JPL, and the ground spaceflight tracking and data network, operated by Goddard) into one consolidated network is reported. Management, design, and implementation activities occurring between August 1981 and April 1982 are addressed, with special emphasis on planning and budgeting activities.

  16. Calorimetry Network Program

    Energy Science and Technology Software Center (ESTSC)

    1998-01-30

    This is a Windows NT based program to run the SRTC designed calorimeters. The network version can communicate near real time data and final data values over the network. This version, due to network specifics, can function in a stand-alone operation also.

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

    ERIC Educational Resources Information Center

    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…

  18. Simulation and analysis of solute transport in 2D fracture/pipe networks: The SOLFRAC program

    NASA Astrophysics Data System (ADS)

    Bodin, Jacques; Porel, Gilles; Delay, Fred; Ubertosi, Fabrice; Bernard, Stéphane; de Dreuzy, Jean-Raynald

    2007-01-01

    The Time Domain Random Walk (TDRW) method has been recently developed by Delay and Bodin [Delay, F. and Bodin, J., 2001. Time domain random walk method to simulate transport by advection-dispersion and matrix diffusion in fracture networks. Geophys. Res. Lett., 28(21): 4051-4054.] and Bodin et al. [Bodin, J., Porel, G. and Delay, F., 2003c. Simulation of solute transport in discrete fracture networks using the time domain random walk method. Earth Planet. Sci. Lett., 6566: 1-8.] for simulating solute transport in discrete fracture networks. It is assumed that the fracture network can reasonably be represented by a network of interconnected one-dimensional pipes (i.e. flow channels). Processes accounted for are: (1) advection and hydrodynamic dispersion in the channels, (2) matrix diffusion, (3) diffusion into stagnant zones within the fracture planes, (4) sorption reactions onto the fracture walls and in the matrix, (5) linear decay, and (6) mass sharing at fracture intersections. The TDRW method is handy and very efficient in terms of computation costs since it allows for the one-step calculation of the particle residence time in each bond of the network. This method has been programmed in C++, and efforts have been made to develop an efficient and user-friendly software, called SOLFRAC. This program is freely downloadable at the URL http://labo.univ-poitiers.fr/hydrasa/intranet/telechargement.htm. It calculates solute transport into 2D pipe networks, while considering different types of injections and different concepts of local dispersion within each flow channel. Post-simulation analyses are also available, such as the mean velocity or the macroscopic dispersion at the scale of the entire network. The program may be used to evaluate how a given transport mechanism influences the macroscopic transport behaviour of fracture networks. It may also be used, as is the case, e.g., with analytical solutions, to interpret laboratory or field tracer test experiments

  19. Modeling the electrical behavior of anatomically complex neurons using a network analysis program: excitable membrane.

    PubMed

    Bunow, B; Segev, I; Fleshman, J W

    1985-01-01

    We present methods for using the general-purpose network analysis program, SPICE, to construct computer models of excitable membrane displaying Hodgkin-Huxley-like kinetics. The four non-linear partial differential equations of Hodgkin and Huxley (H-H; 1952) are implemented using electrical circuit elements. The H-H rate constants, alpha and beta, are approximated by polynomial functions rather than exponential functions, since the former are handled more efficiently by SPICE. The process of developing code to implement the H-H sodium conductance is described in detail. The Appendix contains a complete listing of the code required to simulate an H-H action potential. The behavior of models so constructed is validated by comparison with the space-clamped and propagating action potentials of Hodgkin and Huxley. SPICE models of multiply branched axons were tested and found to behave as predicted by previous numerical solutions for propagation in inhomogeneous axons. New results are presented for two cases. First, a detailed, anatomically based model is constructed of group Ia input to an alpha-motoneuron with an excitable soma, a myelinated axon and passive dendrites. Second, we simulate interactions among clusters of mixed excitable and passive dendritic spines on an idealized neuron. The methods presented in this paper and its companion (Segev et al. 1985) should permit neurobiologists to construct and explore models which simulate much more closely the real morphological and physiological characteristics of nerve cells. PMID:3841014

  20. Television Programming for News and Public Affairs. A Quantitative Analysis of Networks and Stations.

    ERIC Educational Resources Information Center

    Wolf, Frank

    The primary objectives of the study reported in this book was the identification and analysis of major factors that accounted for the quantity and proportion of news and public affairs programing shown on commercial television, and to explain why certain types of programs were far more frequently aired than were others. The problem and research…

  1. In Search of Practitioner-Based Social Capital: A Social Network Analysis Tool for Understanding and Facilitating Teacher Collaboration in a US-Based STEM Professional Development Program

    ERIC Educational Resources Information Center

    Baker-Doyle, Kira J.; Yoon, Susan A.

    2011-01-01

    This paper presents the first in a series of studies on the informal advice networks of a community of teachers in an in-service professional development program. The aim of the research was to use Social Network Analysis as a methodological tool to reveal the social networks developed by the teachers, and to examine whether these networks…

  2. Modelling formulations using gene expression programming--a comparative analysis with artificial neural networks.

    PubMed

    Colbourn, E A; Roskilly, S J; Rowe, R C; York, P

    2011-10-01

    This study has investigated the utility and potential advantages of gene expression programming (GEP)--a new development in evolutionary computing for modelling data and automatically generating equations that describe the cause-and-effect relationships in a system--to four types of pharmaceutical formulation and compared the models with those generated by neural networks, a technique now widely used in the formulation development. Both methods were capable of discovering subtle and non-linear relationships within the data, with no requirement from the user to specify the functional forms that should be used. Although the neural networks rapidly developed models with higher values for the ANOVA R(2) these were black box and provided little insight into the key relationships. However, GEP, although significantly slower at developing models, generated relatively simple equations describing the relationships that could be interpreted directly. The results indicate that GEP can be considered an effective and efficient modelling technique for formulation data. PMID:21903163

  3. Program Helps Simulate Neural Networks

    NASA Technical Reports Server (NTRS)

    Villarreal, James; Mcintire, Gary

    1993-01-01

    Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

  4. Deep space network energy program

    NASA Technical Reports Server (NTRS)

    Friesema, S. E.

    1980-01-01

    If the Deep Space Network is to exist in a cost effective and reliable manner in the next decade, the problems presented by international energy cost increases and energy availability must be addressed. The Deep Space Network Energy Program was established to implement solutions compatible with the ongoing development of the total network.

  5. SNAP: A computer program for generating symbolic network functions

    NASA Technical Reports Server (NTRS)

    Lin, P. M.; Alderson, G. E.

    1970-01-01

    The computer program SNAP (symbolic network analysis program) generates symbolic network functions for networks containing R, L, and C type elements and all four types of controlled sources. The program is efficient with respect to program storage and execution time. A discussion of the basic algorithms is presented, together with user's and programmer's guides.

  6. Networking Course Syllabus in Accredited Library and Information Science Programs: A Comparative Analysis Study

    ERIC Educational Resources Information Center

    Abouserie, Hossam Eldin Mohamed Refaat

    2009-01-01

    The study investigated networking courses offered in accredited Library and Information Science schools in the United States in 2009. The study analyzed and compared network syllabi according to Course Syllabus Evaluation Rubric to obtain in-depth understanding of basic features and characteristics of networking courses taught. The study embraced…

  7. Social Network and Content Analysis of the North American Carbon Program as a Scientific Community of Practice

    NASA Technical Reports Server (NTRS)

    Brown, Molly E.; Ihli, Monica; Hendrick, Oscar; Delgado-Arias, Sabrina; Escobar, Vanessa M.; Griffith, Peter

    2015-01-01

    The North American Carbon Program (NACP) was formed to further the scientific understanding of sources, sinks, and stocks of carbon in Earth's environment. Carbon cycle science integrates multidisciplinary research, providing decision-support information for managing climate and carbon-related change across multiple sectors of society. This investigation uses the conceptual framework of com-munities of practice (CoP) to explore the role that the NACP has played in connecting researchers into a carbon cycle knowledge network, and in enabling them to conduct physical science that includes ideas from social science. A CoP describes the communities formed when people consistently engage in shared communication and activities toward a common passion or learning goal. We apply the CoP model by using keyword analysis of abstracts from scientific publications to analyze the research outputs of the NACP in terms of its knowledge domain. We also construct a co-authorship network from the publications of core NACP members, describe the structure and social pathways within the community. Results of the content analysis indicate that the NACP community of practice has substantially expanded its research on human and social impacts on the carbon cycle, contributing to a better understanding of how human and physical processes interact with one another. Results of the co-authorship social network analysis demonstrate that the NACP has formed a tightly connected community with many social pathways through which knowledge may flow, and that it has also expanded its network of institutions involved in carbon cycle research over the past seven years.

  8. Modeling, Simulation and Analysis of Complex Networked Systems: A Program Plan for DOE Office of Advanced Scientific Computing Research

    SciTech Connect

    Brown, D L

    2009-05-01

    Many complex systems of importance to the U.S. Department of Energy consist of networks of discrete components. Examples are cyber networks, such as the internet and local area networks over which nearly all DOE scientific, technical and administrative data must travel, the electric power grid, social networks whose behavior can drive energy demand, and biological networks such as genetic regulatory networks and metabolic networks. In spite of the importance of these complex networked systems to all aspects of DOE's operations, the scientific basis for understanding these systems lags seriously behind the strong foundations that exist for the 'physically-based' systems usually associated with DOE research programs that focus on such areas as climate modeling, fusion energy, high-energy and nuclear physics, nano-science, combustion, and astrophysics. DOE has a clear opportunity to develop a similarly strong scientific basis for understanding the structure and dynamics of networked systems by supporting a strong basic research program in this area. Such knowledge will provide a broad basis for, e.g., understanding and quantifying the efficacy of new security approaches for computer networks, improving the design of computer or communication networks to be more robust against failures or attacks, detecting potential catastrophic failure on the power grid and preventing or mitigating its effects, understanding how populations will respond to the availability of new energy sources or changes in energy policy, and detecting subtle vulnerabilities in large software systems to intentional attack. This white paper outlines plans for an aggressive new research program designed to accelerate the advancement of the scientific basis for complex networked systems of importance to the DOE. It will focus principally on four research areas: (1) understanding network structure, (2) understanding network dynamics, (3) predictive modeling and simulation for complex networked systems

  9. A computer program to automatically generate state equations and macro-models. [for network analysis and design

    NASA Technical Reports Server (NTRS)

    Garrett, S. J.; Bowers, J. C.; Oreilly, J. E., Jr.

    1978-01-01

    A computer program, PROSE, that produces nonlinear state equations from a simple topological description of an electrical or mechanical network is described. Unnecessary states are also automatically eliminated, so that a simplified terminal circuit model is obtained. The program also prints out the eigenvalues of a linearized system and the sensitivities of the eigenvalue of largest magnitude.

  10. Program risk analysis handbook

    NASA Technical Reports Server (NTRS)

    Batson, R. G.

    1987-01-01

    NASA regulations specify that formal risk analysis be performed on a program at each of several milestones. Program risk analysis is discussed as a systems analysis approach, an iterative process (identification, assessment, management), and a collection of techniques. These techniques, which range from extremely simple to complex network-based simulation, are described in this handbook in order to provide both analyst and manager with a guide for selection of the most appropriate technique. All program risk assessment techniques are shown to be based on elicitation and encoding of subjective probability estimates from the various area experts on a program. Techniques to encode the five most common distribution types are given. Then, a total of twelve distinct approaches to risk assessment are given. Steps involved, good and bad points, time involved, and degree of computer support needed are listed. Why risk analysis should be used by all NASA program managers is discussed. Tools available at NASA-MSFC are identified, along with commercially available software. Bibliography (150 entries) and a program risk analysis check-list are provided.

  11. Variable Size Genetic Network Programming

    NASA Astrophysics Data System (ADS)

    Katagiri, Hironobu; Hirasawa, Kotaro; Hu, Jinglu; Murata, Junichi

    Genetic Network Programming (GNP) is a kind of volutionary methods, which evolves arbitrary directed graph programs. Previously, the program size of GNP was fixed. In the paper, a new method is proposed, where the program size is adaptively changed depending on the frequency of the use of nodes. To control and to decide a program size are important and difficult problems in Evolutionary Computation, especially, a well-known crossover operator tends to cause bloat. We introduce two additional operators, add operator and delete operator, that can change the number of each kind of nodes based on whether a node function is important in the environment or not. Simulation results shows that the proposed method brings about extremely better results compared with ordinary fixed size GNP.

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

    PubMed Central

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

    2009-01-01

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

  13. Communication Network Analysis Methods.

    ERIC Educational Resources Information Center

    Farace, Richard V.; Mabee, Timothy

    This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…

  14. Modeling the electrical behavior of anatomically complex neurons using a network analysis program: passive membrane.

    PubMed

    Segev, I; Fleshman, J W; Miller, J P; Bunow, B

    1985-01-01

    We describe the application of a popular and widely available electrical circuit simulation program called SPICE to modeling the electrical behavior of neurons with passive membrane properties and arbitrarily complex dendritic trees. Transient responses may be calculated at any location in the cell model following current, voltage or conductance perturbations at any point. A numbering method is described for binary trees which is helpful in transforming complex dendritic structures into a coded list of short cylindrical dendritic segments suitable for input to SPICE. Individual segments are modeled as isopotential compartments comprised of a parallel resistor and capacitor, representing the transmembrane impedance, in series with one or two core resistors. Synaptic current is modeled by a current source controlled by the local membrane potential and an "alpha-shaped" voltage, thus simulating a conductance change in series with a driving potential. Extensively branched test cell circuits were constructed which satisfied the equivalent cylinder constraints (Rall 1959). These model neurons were perturbed by independent current sources and by synaptic currents. Responses calculated by SPICE are compared with analytical results. With appropriately chosen model parameters, extremely accurate transient calculations may be obtained. Details of the SPICE circuit elements are presented, along with illustrative examples sufficient to allow implementation of passive nerve cell models on a number of common computers. Methods for modeling excitable membrane are presented in the companion paper (Bunow et al. 1985). PMID:3841013

  15. Compressive Network Analysis

    PubMed Central

    Jiang, Xiaoye; Yao, Yuan; Liu, Han; Guibas, Leonidas

    2014-01-01

    Modern data acquisition routinely produces massive amounts of network data. Though many methods and models have been proposed to analyze such data, the research of network data is largely disconnected with the classical theory of statistical learning and signal processing. In this paper, we present a new framework for modeling network data, which connects two seemingly different areas: network data analysis and compressed sensing. From a nonparametric perspective, we model an observed network using a large dictionary. In particular, we consider the network clique detection problem and show connections between our formulation with a new algebraic tool, namely Randon basis pursuit in homogeneous spaces. Such a connection allows us to identify rigorous recovery conditions for clique detection problems. Though this paper is mainly conceptual, we also develop practical approximation algorithms for solving empirical problems and demonstrate their usefulness on real-world datasets. PMID:25620806

  16. Investigating Value Creation in a Community of Practice with Social Network Analysis in a Hybrid Online Graduate Education Program

    ERIC Educational Resources Information Center

    Cowan, John E.; Menchaca, Michael P.

    2014-01-01

    This study reports an analysis of 10?years in the life of the Internet-based Master in Educational Technology program (iMET) at Sacramento State University. iMET is a hybrid educational technology master's program delivered 20% face to face and 80% online. The program has achieved a high degree of success, with a course completion rate of 93%…

  17. ANPS - AUTOMATIC NETWORK PROGRAMMING SYSTEM

    NASA Technical Reports Server (NTRS)

    Schroer, B. J.

    1994-01-01

    Development of some of the space program's large simulation projects -- like the project which involves simulating the countdown sequence prior to spacecraft liftoff -- requires the support of automated tools and techniques. The number of preconditions which must be met for a successful spacecraft launch and the complexity of their interrelationship account for the difficulty of creating an accurate model of the countdown sequence. Researchers developed ANPS for the Nasa Marshall Space Flight Center to assist programmers attempting to model the pre-launch countdown sequence. Incorporating the elements of automatic programming as its foundation, ANPS aids the user in defining the problem and then automatically writes the appropriate simulation program in GPSS/PC code. The program's interactive user dialogue interface creates an internal problem specification file from user responses which includes the time line for the countdown sequence, the attributes for the individual activities which are part of a launch, and the dependent relationships between the activities. The program's automatic simulation code generator receives the file as input and selects appropriate macros from the library of software modules to generate the simulation code in the target language GPSS/PC. The user can recall the problem specification file for modification to effect any desired changes in the source code. ANPS is designed to write simulations for problems concerning the pre-launch activities of space vehicles and the operation of ground support equipment and has potential for use in developing network reliability models for hardware systems and subsystems. ANPS was developed in 1988 for use on IBM PC or compatible machines. The program requires at least 640 KB memory and one 360 KB disk drive, PC DOS Version 2.0 or above, and GPSS/PC System Version 2.0 from Minuteman Software. The program is written in Turbo Prolog Version 2.0. GPSS/PC is a trademark of Minuteman Software. Turbo Prolog

  18. Analysis of network statistics

    NASA Astrophysics Data System (ADS)

    Cottrell, R. L. A.

    1987-08-01

    This talk discusses the types and sources of data obtainable from networks of computer systems and terminals connected by communications paths. These paths often utilize mixtures of protocols and devices (such as modems, multiplexors, switches and front-ends) from multiple vendors. The talk describes how the data can be gathered from these devices and protocol layers, consolidated, stored, and analyzed. The analysis typically includes merging information from data bases describing the network topology, components, etc. Examples of reports and displays of the information gleaned are shown, together with illustrations of how the information may be useful for troubleshooting, performance measurement, auditing, accounting, and trend prediction.

  19. Network systems security analysis

    NASA Astrophysics Data System (ADS)

    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.

  20. Vector Network Analysis

    Energy Science and Technology Software Center (ESTSC)

    1997-10-20

    Vector network analyzers are a convenient way to measure scattering parameters of a variety of microwave devices. However, these instruments, unlike oscilloscopes for example, require a relatively high degree of user knowledge and expertise. Due to the complexity of the instrument and of the calibration process, there are many ways in which an incorrect measurement may be produced. The Microwave Project, which is part of Sandia National Laboratories Primary Standards Laboratory, routinely uses check standardsmore » to verify that the network analyzer is operating properly. In the past, these measurements were recorded manually and, sometimes, interpretation of the results was problematic. To aid our measurement assurance process, a software program was developed to automatically measure a check standard and compare the new measurements with an historical database of measurements of the same device. The program acquires new measurement data from selected check standards, plots the new data against the mean and standard deviation of prior data for the same check standard, and updates the database files for the check standard. The program is entirely menu-driven requiring little additional work by the user.« less

  1. Program analysis for documentation

    NASA Technical Reports Server (NTRS)

    Lolmaugh, G. H.

    1970-01-01

    A program analysis for documentation (PAD) written in FORTRAN has three steps: listing the variables, describing the structure and writing the program specifications. Technical notes on editing criteria for reviewing program documentation, technical notes for PAD, and FORTRAN program analyzer for documentation are appended.

  2. Neural-Network-Development Program

    NASA Technical Reports Server (NTRS)

    Phillips, Todd A.

    1993-01-01

    NETS, software tool for development and evaluation of neural networks, provides simulation of neural-network algorithms plus computing environment for development of such algorithms. Uses back-propagation learning method for all of networks it creates. Enables user to customize patterns of connections between layers of network. Also provides features for saving, during learning process, values of weights, providing more-precise control over learning process. Written in ANSI standard C language. Machine-independent version (MSC-21588) includes only code for command-line-interface version of NETS 3.0.

  3. Comparative analysis of collaboration networks

    SciTech Connect

    Progulova, Tatiana; Gadjiev, Bahruz

    2011-03-14

    In this paper we carry out a comparative analysis of the word network as the collaboration network based on the novel by M. Bulgakov 'Master and Margarita', the synonym network of the Russian language as well as the Russian movie actor network. We have constructed one-mode projections of these networks, defined degree distributions for them and have calculated main characteristics. In the paper a generation algorithm of collaboration networks has been offered which allows one to generate networks statistically equivalent to the studied ones. It lets us reveal a structural correlation between word network, synonym network and movie actor network. We show that the degree distributions of all analyzable networks are described by the distribution of q-type.

  4. Network News-Interview Programs and the "Television War".

    ERIC Educational Resources Information Center

    Carroll, Raymond L.; Lichty, Lawrence W.

    A study was made of the news-interview programs from the three major television networks (ABC, CBS, and NBC) to determine which aspects of the Vietnam War were discussed on the programs and whether participants were supporters of or detractors from the policies of the presidential administration at the time. The content analysis of 481 editions of…

  5. Program for Online Network Inversion

    Energy Science and Technology Software Center (ESTSC)

    2009-12-21

    PONI determines the source location of a contamination incident in a water distribution network. PONI uses large scale optimization methods to predict likely source locations by reconciling the differences between observations and numerical predictions of possible contamination incidents.

  6. Neural Networks for Readability Analysis.

    ERIC Educational Resources Information Center

    McEneaney, John E.

    This paper describes and reports on the performance of six related artificial neural networks that have been developed for the purpose of readability analysis. Two networks employ counts of linguistic variables that simulate a traditional regression-based approach to readability. The remaining networks determine readability from "visual snapshots"…

  7. Analysis of space network loading

    NASA Technical Reports Server (NTRS)

    Simons, Mark; Larrson, Gus

    1994-01-01

    The NASA Space Network (SN) consists of several geosynchronous communications satellites, in addition to ground support facilities. Space Network management must predict years in advance what network resources are necessary to adequately satisfy all SN users. Similarly, users of the Space Network must know throughout all stages of mission planning and operations to what extent their communication support requirements can be met. NASA, at the Goddard Space Flight Center, performs Space Network and Mission Modeling using The Network Planning and Analysis System (NPAS), to determine the answers to these questions.

  8. Statistical Energy Analysis Program

    NASA Technical Reports Server (NTRS)

    Ferebee, R. C.; Trudell, R. W.; Yano, L. I.; Nygaard, S. I.

    1985-01-01

    Statistical Energy Analysis (SEA) is powerful tool for estimating highfrequency vibration spectra of complex structural systems and incorporated into computer program. Basic SEA analysis procedure divided into three steps: Idealization, parameter generation, and problem solution. SEA computer program written in FORTRAN V for batch execution.

  9. Visual Tutoring System for Programming Multiprocessor Networks.

    ERIC Educational Resources Information Center

    Trichina, Elena

    1996-01-01

    Describes a visual tutoring system for programming distributive-memory multiprocessor networks. Highlights include difficulties of parallel programming, and three instructional modes in the system, including a hypertext-like lecture, a question-answer mode, and an expert aid mode. (Author/LRW)

  10. LULU analysis program

    SciTech Connect

    Crawford, H.J.; Lindstrom, P.J.

    1983-06-01

    Our analysis program LULU has proven very useful in all stages of experiment analysis, from prerun detector debugging through final data reduction. It has solved our problem of having arbitrary word length events and is easy enough to use that many separate experimenters are now analyzing with LULU. The ability to use the same software for all stages of experiment analysis greatly eases the programming burden. We may even get around to making the graphics elegant someday.

  11. Network topology analysis.

    SciTech Connect

    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.

  12. The Analysis of Social Networks

    PubMed Central

    O’Malley, A. James; Marsden, Peter V.

    2009-01-01

    Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures. PMID:20046802

  13. Characterization of the Weatherization Assistance Program network

    SciTech Connect

    Mihlmester, P.E.; Koehler, W.C. Jr.; Beyer, M.A. . Applied Management Sciences Div.); Brown, M.A. ); Beschen, D.A. Jr. . Office of Weatherization Assistance Programs)

    1992-02-01

    The Characterization of the Weatherization Assistance Program (WAP) Network was designed to describe the national network of State and local agencies that provide WAP services to qualifying low-income households. The objective of this study was to profile the current WAP network. To achieve the objective, two national surveys were conducted: one survey collected data from 49 State WAP agencies (including the coterminous 48 States and the District of Columbia), and the second survey collected data from 920 (or 81 percent) of the local WAP agencies.

  14. Characterization of the Weatherization Assistance Program network. Weatherization Assistance Program

    SciTech Connect

    Mihlmester, P.E.; Koehler, W.C. Jr.; Beyer, M.A.; Brown, M.A.; Beschen, D.A. Jr.

    1992-02-01

    The Characterization of the Weatherization Assistance Program (WAP) Network was designed to describe the national network of State and local agencies that provide WAP services to qualifying low-income households. The objective of this study was to profile the current WAP network. To achieve the objective, two national surveys were conducted: one survey collected data from 49 State WAP agencies (including the coterminous 48 States and the District of Columbia), and the second survey collected data from 920 (or 81 percent) of the local WAP agencies.

  15. Bolt Analysis Program

    NASA Technical Reports Server (NTRS)

    Travis, Brandon E.

    2004-01-01

    In designing and testing bolted joints there are multiple parameters to be considered and calculations that must be performed to predict the joint behavior. Each different set of parameters may call for a different set of equations. Determining every parameter in each bolted joint is impractical and in many cases impossible. On the other hand, it is much easier to reduce these calculations to a universal set that can be used for all bolted joints. This is the purpose of the Bolt Analysis Program. My project under the Mechanical and Rotating Systems branch of the Engineering Development and Analysis Division was to take the Bolt Analysis Program Version 2.0 and update the program to a modem and user-friendly format. Version 2.0 of the Bolt Analysis Program is a useful program, but lacks the dynamic capabilities that are needed for current applications. Version 2.0 of the Bolt Analysis Program was written in 1993 using the Pascal programming language in a DOS format. This program allows you to input data in a step-by-step format, calculates the data, and then on a final screen displays the input and the output fiom the calculations. Version 2.0 is still applicable for all bolted joint anaiysis, but has updates that are desired. First, the program runs in DOS format. With the applications available today, my mentor decided it would be best to update the program into Excel using Visual Basic for Applications (VBA). This would allow the program to have multiple Graphical User Interfaces (GUI s) while retaining all functions of the previous program. Version 2.0 only allows you to input data in a step-by-step process. If you make a mistake and need to go back, you must run through the entire program before you can return to fix your error. This becomes tedious when needing to change one parameter or test multiple sets of data. In Version 3.0, the program allows you to enter and change data at any time while displaying real-time output data. If you realize an error, it is

  16. Program PSNN (Plasma Spectroscopy Neural Network)

    SciTech Connect

    Morgan, W.L.; Larsen, J.T.

    1993-08-01

    This program uses the standard ``delta rule`` back-propagation supervised training algorithm for multi-layer neural networks. The inputs are line intensities in arbitrary units, which are then normalized within the program. The outputs are T{sub e}(eV), N{sub e}(cm{sup {minus}3}), and a fractional ionization, which in our testing using H- and He-like spectra, was N(He)/[N(H) + N(He)].

  17. A mathematical programming approach for sequential clustering of dynamic networks

    NASA Astrophysics Data System (ADS)

    Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

    2016-02-01

    A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

  18. Network analysis of Bogotá’s Ciclovía Recreativa, a self-organized multisectoral community program to promote physical activity in a middle-income country

    PubMed Central

    Meisel, Jose D; Sarmiento, Olga; Montes, Felipe; Martinez, Edwin O.; Lemoine, Pablo D; Valdivia, Juan A; Brownson, RC; Zarama, Robert

    2016-01-01

    Purpose Conduct a social network analysis of the health and non-health related organizations that participate in the Bogotá’s Ciclovía Recreativa (Ciclovía). Design Cross sectional study. Setting Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and PA. Subjects 25 organizations that participate in the Ciclovía. Measures Seven variables were examined using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). Analysis The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Results Analysis shows that the most central organizations in the network were outside of the health sector and includes Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Conclusion Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central. PMID:23971523

  19. The Role of the School Library Media Program in Networking.

    ERIC Educational Resources Information Center

    National Commission on Libraries and Information Science, Washington, DC.

    This report of a study of the state of networking in school library media programs nationwide and the role of such programs in the National Program for Libraries and Information Services covers the rationale for inclusion of these programs in library networks, contributions of such programs to a national program, the benefits to the users of…

  20. Transmission network planning using linear programming

    SciTech Connect

    Villasana, R.; Garver, L.L.; Salon, S.J.

    1985-02-01

    In long range transmission planning, where new load growth, new generation sites and perhaps a new voltage level are to be considered, a computer aided method of visualizing new circuits in a network context is needed. The new method presented meets this need by the combined use of a linear (dc) power flow transmission model and a transportation model (also known as a trans-shipment model). The dc transmission model is solved for the facilities network by obeying both of Kirchhoff's laws, flow conservation at each bus and voltage conservation around each loop. The transportation model is solved for the overloads by obeying only the bus flow conservation law while minimizing a cost objective function. The linear programming solution of the two models together identifies where capacity shortages exist, where to add new circuits, and how much new capacity is needed. A standard linear programming computer package is used to solve the two model formulation. The overload network model is only a mathematical assistance in selecting new lines and is completely unused when the network design is complete and contains no overloads. An application of the model to the horizon-year planning of a six bus network serves to illustrate the method.

  1. The Coaching Network: A Program for Individual and Organizational Development.

    ERIC Educational Resources Information Center

    Bowerman, Jennifer; Collins, Gordon

    1999-01-01

    Illustrates how job coaching networks can be implemented using adult education principles, with dialog and conversation as the foundation. Network success depends on in-house expertise, program ownership, and enough structure to maintain program integrity while allowing creativity. (SK)

  2. RCytoscape: tools for exploratory network analysis

    PubMed Central

    2013-01-01

    Background Biomolecular pathways and networks are dynamic and complex, and the perturbations to them which cause disease are often multiple, heterogeneous and contingent. Pathway and network visualizations, rendered on a computer or published on paper, however, tend to be static, lacking in detail, and ill-equipped to explore the variety and quantities of data available today, and the complex causes we seek to understand. Results RCytoscape integrates R (an open-ended programming environment rich in statistical power and data-handling facilities) and Cytoscape (powerful network visualization and analysis software). RCytoscape extends Cytoscape's functionality beyond what is possible with the Cytoscape graphical user interface. To illustrate the power of RCytoscape, a portion of the Glioblastoma multiforme (GBM) data set from the Cancer Genome Atlas (TCGA) is examined. Network visualization reveals previously unreported patterns in the data suggesting heterogeneous signaling mechanisms active in GBM Proneural tumors, with possible clinical relevance. Conclusions Progress in bioinformatics and computational biology depends upon exploratory and confirmatory data analysis, upon inference, and upon modeling. These activities will eventually permit the prediction and control of complex biological systems. Network visualizations -- molecular maps -- created from an open-ended programming environment rich in statistical power and data-handling facilities, such as RCytoscape, will play an essential role in this progression. PMID:23837656

  3. Integrated Analysis Capability Program

    NASA Technical Reports Server (NTRS)

    Vos, R. G.; Beste, D. L.; Greg, J.; Frisch, H. P.

    1991-01-01

    Integrated Analysis Capability (IAC) software system intended to provide highly effective, interactive analysis tool for integrated design of large structures. Supports needs of engineering analysis groups concerned with interdisciplinary problems. Developed to serve as software interface between computer programs from fields of structures, thermodynamics, controls, and dynamics of systems on one hand and executive software system and data base on other hand to yield highly efficient multi-disciplinary system. Special attention given to such users' requirements as handling data and online assistance with operational features and ability to add new modules of user's choice at future date. Written in FORTRAN 77.

  4. Neural network ultrasound image analysis

    NASA Astrophysics Data System (ADS)

    Schneider, Alexander C.; Brown, David G.; Pastel, Mary S.

    1993-09-01

    Neural network based analysis of ultrasound image data was carried out on liver scans of normal subjects and those diagnosed with diffuse liver disease. In a previous study, ultrasound images from a group of normal volunteers, Gaucher's disease patients, and hepatitis patients were obtained by Garra et al., who used classical statistical methods to distinguish from among these three classes. In the present work, neural network classifiers were employed with the same image features found useful in the previous study for this task. Both standard backpropagation neural networks and a recently developed biologically-inspired network called Dystal were used. Classification performance as measured by the area under a receiver operating characteristic curve was generally excellent for the back propagation networks and was roughly comparable to that of classical statistical discriminators tested on the same data set and documented in the earlier study. Performance of the Dystal network was significantly inferior; however, this may be due to the choice of network parameter. Potential methods for enhancing network performance was identified.

  5. 40 CFR 51.353 - Network type and program evaluation.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 40 Protection of Environment 2 2010-07-01 2010-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized.... (a) Presumptive equivalency. A decentralized network consisting of stations that only...

  6. 40 CFR 51.353 - Network type and program evaluation.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 40 Protection of Environment 2 2011-07-01 2011-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized.... (a) Presumptive equivalency. A decentralized network consisting of stations that only...

  7. Probabilistic Structural Analysis Program

    NASA Technical Reports Server (NTRS)

    Pai, Shantaram S.; Chamis, Christos C.; Murthy, Pappu L. N.; Stefko, George L.; Riha, David S.; Thacker, Ben H.; Nagpal, Vinod K.; Mital, Subodh K.

    2010-01-01

    NASA/NESSUS 6.2c is a general-purpose, probabilistic analysis program that computes probability of failure and probabilistic sensitivity measures of engineered systems. Because NASA/NESSUS uses highly computationally efficient and accurate analysis techniques, probabilistic solutions can be obtained even for extremely large and complex models. Once the probabilistic response is quantified, the results can be used to support risk-informed decisions regarding reliability for safety-critical and one-of-a-kind systems, as well as for maintaining a level of quality while reducing manufacturing costs for larger-quantity products. NASA/NESSUS has been successfully applied to a diverse range of problems in aerospace, gas turbine engines, biomechanics, pipelines, defense, weaponry, and infrastructure. This program combines state-of-the-art probabilistic algorithms with general-purpose structural analysis and lifting methods to compute the probabilistic response and reliability of engineered structures. Uncertainties in load, material properties, geometry, boundary conditions, and initial conditions can be simulated. The structural analysis methods include non-linear finite-element methods, heat-transfer analysis, polymer/ceramic matrix composite analysis, monolithic (conventional metallic) materials life-prediction methodologies, boundary element methods, and user-written subroutines. Several probabilistic algorithms are available such as the advanced mean value method and the adaptive importance sampling method. NASA/NESSUS 6.2c is structured in a modular format with 15 elements.

  8. The space physics analysis network

    NASA Astrophysics Data System (ADS)

    Green, James L.

    1988-04-01

    The Space Physics Analysis Network, or SPAN, is emerging as a viable method for solving an immediate communication problem for space and Earth scientists and has been operational for nearly 7 years. SPAN and its extension into Europe, utilizes computer-to-computer communications allowing mail, binary and text file transfer, and remote logon capability to over 1000 space science computer systems. The network has been used to successfully transfer real-time data to remote researchers for rapid data analysis but its primary function is for non-real-time applications. One of the major advantages for using SPAN is its spacecraft mission independence. Space science researchers using SPAN are located in universities, industries and government institutions all across the United States and Europe. These researchers are in such fields as magnetospheric physics, astrophysics, ionosperic physics, atmospheric physics, climatology, meteorology, oceanography, planetary physics and solar physics. SPAN users have access to space and Earth science data bases, mission planning and information systems, and computational facilities for the purposes of facilitating correlative space data exchange, data analysis and space research. For example, the National Space Science Data Center (NSSDC), which manages the network, is providing facilities on SPAN such as the Network Information Center (SPAN NIC). SPAN has interconnections with several national and international networks such as HEPNET and TEXNET forming a transparent DECnet network. The combined total number of computers now reachable over these combined networks is about 2000. In addition, SPAN supports full function capabilities over the international public packet switched networks (e.g. TELENET) and has mail gateways to ARPANET, BITNET and JANET.

  9. Timeline Analysis Program (TLA-1)

    NASA Technical Reports Server (NTRS)

    Miller, K. H.

    1976-01-01

    The Timeline Analysis Program (TLA-1) was described. This program is a crew workload analysis computer program that was developed and expanded from previous workload analysis programs, and is designed to be used on the NASA terminal controlled vehicle program. The following information is described: derivation of the input data, processing of the data, and form of the output data. Eight scenarios that were created, programmed, and analyzed as verification of this model were also described.

  10. Computer analysis of general linear networks using digraphs.

    NASA Technical Reports Server (NTRS)

    Mcclenahan, J. O.; Chan, S.-P.

    1972-01-01

    Investigation of the application of digraphs in analyzing general electronic networks, and development of a computer program based on a particular digraph method developed by Chen. The Chen digraph method is a topological method for solution of networks and serves as a shortcut when hand calculations are required. The advantage offered by this method of analysis is that the results are in symbolic form. It is limited, however, by the size of network that may be handled. Usually hand calculations become too tedious for networks larger than about five nodes, depending on how many elements the network contains. Direct determinant expansion for a five-node network is a very tedious process also.

  11. Biomedical systems analysis program

    NASA Technical Reports Server (NTRS)

    1979-01-01

    Biomedical monitoring programs which were developed to provide a system analysis context for a unified hypothesis for adaptation to space flight are presented and discussed. A real-time system of data analysis and decision making to assure the greatest possible crew safety and mission success is described. Information about man's abilities, limitations, and characteristic reactions to weightless space flight was analyzed and simulation models were developed. The predictive capabilities of simulation models for fluid-electrolyte regulation, erythropoiesis regulation, and calcium regulation are discussed.

  12. Regression analysis of networked data

    PubMed Central

    Zhou, Yan; Song, Peter X.-K.

    2016-01-01

    This paper concerns regression methodology for assessing relationships between multi-dimensional response variables and covariates that are correlated within a network. To address analytical challenges associated with the integration of network topology into the regression analysis, we propose a hybrid quadratic inference method that uses both prior and data-driven correlations among network nodes. A Godambe information-based tuning strategy is developed to allocate weights between the prior and data-driven network structures, so the estimator is efficient. The proposed method is conceptually simple and computationally fast, and has appealing large-sample properties. It is evaluated by simulation, and its application is illustrated using neuroimaging data from an association study of the effects of iron deficiency on auditory recognition memory in infants. PMID:27279658

  13. Timeline Resource Analysis Program (TRAP): User's manual and program document

    NASA Technical Reports Server (NTRS)

    Sessler, J. G.

    1981-01-01

    The Timeline Resource Analysis Program (TRAP), developed for scheduling and timelining problems, is described. Given an activity network, TRAP generates timeline plots, resource histograms, and tabular summaries of the network, schedules, and resource levels. It is written in ANSI FORTRAN for the Honeywell SIGMA 5 computer and operates in the interactive mode using the TEKTRONIX 4014-1 graphics terminal. The input network file may be a standard SIGMA 5 file or one generated using the Interactive Graphics Design System. The timeline plots can be displayed in two orderings: according to the sequence in which the tasks were read on input, and a waterfall sequence in which the tasks are ordered by start time. The input order is especially meaningful when the network consists of several interacting subnetworks. The waterfall sequence is helpful in assessing the project status at any point in time.

  14. Programming Sensor Networks Using Remora Component Model

    NASA Astrophysics Data System (ADS)

    Taherkordi, Amirhosein; Loiret, Frédéric; Abdolrazaghi, Azadeh; Rouvoy, Romain; Le-Trung, Quan; Eliassen, Frank

    The success of high-level programming models in Wireless Sensor Networks (WSNs) is heavily dependent on factors such as ease of programming, code well-structuring, degree of code reusability, and required software development effort. Component-based programming has been recognized as an effective approach to meet such requirements. Most of componentization efforts in WSNs were ineffective due to various reasons, such as high resource demand or limited scope of use. In this paper, we present Remora, a new approach to practical and efficient component-based programming in WSNs. Remora offers a well-structured programming paradigm that fits very well with resource limitations of embedded systems, including WSNs. Furthermore, the special attention to event handling in Remora makes our proposal more practical for WSN applications, which are inherently event-driven. More importantly, the mutualism between Remora and underlying system software promises a new direction towards separation of concerns in WSNs. Our evaluation results show that a well-configured Remora application has an acceptable memory overhead and a negligible CPU cost.

  15. NATIONAL CROP LOSS ASSESSMENT NETWORK: QUALITY ASSURANCE PROGRAM (JOURNAL VERSION)

    EPA Science Inventory

    A quality assurance program was incorporated into the National Crop Loss Assessment Network (NCLAN) program, designed to assess the economic impacts of gaseous air pollutants on major agricultural crops in the United States. The quality assurance program developed standardized re...

  16. Functional Localization of Genetic Network Programming

    NASA Astrophysics Data System (ADS)

    Eto, Shinji; Hirasawa, Kotaro; Hu, Jinglu

    According to the knowledge of brain science, it is suggested that there exists cerebral functional localization, which means that a specific part of the cerebrum is activated depending on various kinds of information human receives. The aim of this paper is to build an artificial model to realize functional localization based on Genetic Network Programming (GNP), a new evolutionary computation method recently developed. GNP has a directed graph structure suitable for realizing functional localization. We studied the basic characteristics of the proposed system by making GNP work in a functionally localized way.

  17. 77 FR 62243 - Rural Health Network Development Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-12

    ... HUMAN SERVICES Health Resources and Services Administration Rural Health Network Development Program... Network Development Program to the Siloam Springs Regional Health Cooperative, Inc. This non-competitive... development activities to ensure the sustainability and viability of a rural health network in order to...

  18. CTAS data analysis program

    NASA Technical Reports Server (NTRS)

    Neuman, Frank; Erzberger, Heinz; Schueller, Michael S.

    1994-01-01

    The analysis program (AN) is specifically designed to produce graphic and tabular information to aid in the design and checkout of the Center TRACON Automation System (CTAS). To best reveal CTAS operation and possible problems, data are plotted in many different ways both in detail and summary form. AN has been designed to analyze both radar surveillance data and output data from CTAS. AN has been extensively used to debug and refine CTAS. It is also being used in the field to monitor and assess CTAS performance. AN is continuously refined to keep up with changing needs. The present version of AN grew out of analysis of Denver Center data. However, the AN software has been written to be adaptable to any other facility Center or TRACON. Presently, one can select Denver Stapleton, Denver International, Dallas/Fort Worth International Airport, and Dallas Love Field.

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

    PubMed

    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. PMID:24861621

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

    PubMed Central

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

    2014-01-01

    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. PMID:24861621

  1. Constructing, conducting and interpreting animal social network analysis.

    PubMed

    Farine, Damien R; Whitehead, Hal

    2015-09-01

    1. Animal social networks are descriptions of social structure which, aside from their intrinsic interest for understanding sociality, can have significant bearing across many fields of biology. 2. Network analysis provides a flexible toolbox for testing a broad range of hypotheses, and for describing the social system of species or populations in a quantitative and comparable manner. However, it requires careful consideration of underlying assumptions, in particular differentiating real from observed networks and controlling for inherent biases that are common in social data. 3. We provide a practical guide for using this framework to analyse animal social systems and test hypotheses. First, we discuss key considerations when defining nodes and edges, and when designing methods for collecting data. We discuss different approaches for inferring social networks from these data and displaying them. We then provide an overview of methods for quantifying properties of nodes and networks, as well as for testing hypotheses concerning network structure and network processes. Finally, we provide information about assessing the power and accuracy of an observed network. 4. Alongside this manuscript, we provide appendices containing background information on common programming routines and worked examples of how to perform network analysis using the r programming language. 5. We conclude by discussing some of the major current challenges in social network analysis and interesting future directions. In particular, we highlight the under-exploited potential of experimental manipulations on social networks to address research questions. PMID:26172345

  2. Spectral Analysis of Rich Network Topology in Social Networks

    ERIC Educational Resources Information Center

    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…

  3. A computer program for the generation of logic networks from task chart data

    NASA Technical Reports Server (NTRS)

    Herbert, H. E.

    1980-01-01

    The Network Generation Program (NETGEN), which creates logic networks from task chart data is presented. NETGEN is written in CDC FORTRAN IV (Extended) and runs in a batch mode on the CDC 6000 and CYBER 170 series computers. Data is input via a two-card format and contains information regarding the specific tasks in a project. From this data, NETGEN constructs a logic network of related activities with each activity having unique predecessor and successor nodes, activity duration, descriptions, etc. NETGEN then prepares this data on two files that can be used in the Project Planning Analysis and Reporting System Batch Network Scheduling program and the EZPERT graphics program.

  4. Program Theory Evaluation: Logic Analysis

    ERIC Educational Resources Information Center

    Brousselle, Astrid; Champagne, Francois

    2011-01-01

    Program theory evaluation, which has grown in use over the past 10 years, assesses whether a program is designed in such a way that it can achieve its intended outcomes. This article describes a particular type of program theory evaluation--logic analysis--that allows us to test the plausibility of a program's theory using scientific knowledge.…

  5. Deep Space Network Radiometric Remote Sensing Program

    NASA Technical Reports Server (NTRS)

    Walter, Steven J.

    1994-01-01

    Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid, and precipitation, emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band because communication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of water vapor-induced propagation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity wave experiments, and radio science missions. During 1993, WVRs provided data for propagation model development, supported planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily

  6. Automated drawing of network plots in network meta-analysis.

    PubMed

    Rücker, Gerta; Schwarzer, Guido

    2016-03-01

    In systematic reviews based on network meta-analysis, the network structure should be visualized. Network plots often have been drawn by hand using generic graphical software. A typical way of drawing networks, also implemented in statistical software for network meta-analysis, is a circular representation, often with many crossing lines. We use methods from graph theory in order to generate network plots in an automated way. We give a number of requirements for graph drawing and present an algorithm that fits prespecified ideal distances between the nodes representing the treatments. The method was implemented in the function netgraph of the R package netmeta and applied to a number of networks from the literature. We show that graph representations with a small number of crossing lines are often preferable to circular representations. PMID:26060934

  7. Introduction to stream network habitat analysis

    USGS Publications Warehouse

    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

  8. Topological Analysis of Urban Drainage Networks

    NASA Astrophysics Data System (ADS)

    Yang, Soohyun; Paik, Kyungrock; McGrath, Gavan; Rao, Suresh

    2016-04-01

    Urban drainage networks are an essential component of infrastructure, and comprise the aggregation of underground pipe networks carrying storm water and domestic waste water for eventual discharge to natural stream networks. Growing urbanization has contributed to rapid expansion of sewer networks, vastly increasing their complexity and scale. Importance of sewer networks has been well studied from an engineering perspective, including resilient management, optimal design, and malfunctioning impact. Yet, analysis of the urban drainage networks using complex networks approach are lacking. Urban drainage networks consist of manholes and conduits, which correspond to nodes and edges, analogous to junctions and streams in river networks. Converging water flows in these two networks are driven by elevation gradient. In this sense, engineered urban drainage networks share several attributes of flows in river networks. These similarities between the two directed, converging flow networks serve the basis for us to hypothesize that the functional topology of sewer networks, like river networks, is scale-invariant. We analyzed the exceedance probability distribution of upstream area for practical sewer networks in South Korea. We found that the exceedance probability distributions of upstream area follow power-law, implying that the sewer networks exhibit topological self-similarity. The power-law exponents for the sewer networks were similar, and within the range reported from analysis of natural river networks. Thus, in line with our hypothesis, these results suggest that engineered urban drainage networks share functional topological attributes regardless of their structural dissimilarity or different underlying network evolution processes (natural vs. engineered). Implications of these findings for optimal design of sewer networks and for modeling sewer flows will be discussed.

  9. Microcomputer Network for Computerized Adaptive Testing (CAT): Program Listing.

    ERIC Educational Resources Information Center

    Quan, Baldwin; And Others

    This program listing is a supplement to the Microcomputer Network for Computerized Adaptive Testing (CAT). The driver textfile program allows access to major subprograms of the CAT project. The test administration textfile program gives examinees a prescribed set of subtests. The parameter management textfile program establishes a file containing…

  10. Collector-Output Analysis Program

    NASA Technical Reports Server (NTRS)

    Glandorf, D. R.; Phillips, Robert F., II

    1986-01-01

    Collector-Output Analysis Program (COAP) programmer's aid for analyzing output produced by UNIVAC collector (MAP processor). COAP developed to aid in design of segmentation structures for programs with large memory requirements and numerous elements but of value in understanding relationships among components of any program. Crossreference indexes and supplemental information produced. COAP written in FORTRAN 77.

  11. Comparing the NRC and the Faculty Hiring Network Methods of Ranking Doctoral Programs in Communication

    ERIC Educational Resources Information Center

    Barnett, George A.; Feeley, Thomas Hugh

    2011-01-01

    The current analysis examines the relationship between measures (R-scores, S-scores, faculty productivity) utilized in the recently published National Research Council NRC report and communication doctoral programs' centrality in the faculty-hiring network. Correlations among the network indicators and the NRC ratings were generally moderate and…

  12. Metabolic balance analysis program

    NASA Technical Reports Server (NTRS)

    Rombach, J.

    1971-01-01

    Computer program calculates 28 day diet for life support consumables requirements and waste removal. Equations representing food breakdown into carbohydrates, fats, and proteins, modified to account for digestive materials and indigestible crude fibers, formulate total energy consumption. Program applications are listed.

  13. Google matrix analysis of directed networks

    NASA Astrophysics Data System (ADS)

    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.

  14. Introduction to Network Analysis in Systems Biology

    PubMed Central

    Ma’ayan, Avi

    2011-01-01

    This Teaching Resource provides lecture notes, slides, and a problem set for a set of three lectures from a course entitled “Systems Biology: Biomedical Modeling.” The materials are from three separate lectures introducing applications of graph theory and network analysis in systems biology. The first lecture describes different types of intracellular networks, methods for constructing biological networks, and different types of graphs used to represent regulatory intracellular networks. The second lecture surveys milestones and key concepts in network analysis by introducing topological measures, random networks, growing network models, and topological observations from molecular biological systems abstracted to networks. The third lecture discusses methods for analyzing lists of genes and experimental data in the context of prior knowledge networks to make predictions. PMID:21917719

  15. Artificial-Satellite-Analysis Program

    NASA Technical Reports Server (NTRS)

    Kwok, Johnny H.

    1989-01-01

    Artificial Satellite Analysis Program (ASAP) is general orbit-predicting computer program incorporating sufficient orbit-modeling accuracy for design and planning of missions and analysis of maneuvers. Suitable for study of planetary-orbit missions with spacecraft trajectories of reconnaissance (flyby) and exploratory (mapping) nature. Not written for specific mission and intended use for almost any planetary orbiting mission. Written in FORTRAN 77.

  16. Sandia Infrared Analysis Program

    Energy Science and Technology Software Center (ESTSC)

    2004-05-11

    SandIR is a sophisticated Windows2000/WindowsXP program for the capture and analysis of thermal images in real time. It is a 32-bit, 5 thread C++ OOP application that rests on Microsoft’s MFC and DirectDraw libraries, the DT3152LS driver functions and the LabEngine link libraries of Origin 4.1 for full functionality. Images may be loaded in from saved files or viewed live by connection to a FLIR (Inframetrics) 600 or 760 IR camera or a video cassettemore » recorder playing tapes recorded from a FLIR (Inframetrlcs) 600 or 760 IR camera- At this time, no other IR camera formats are supported. The raw radiosity data used by SandiR is derived from the 8-bit, 256 level, RS-170 (grayscale) NTSC camera signal. The FLIR camera images contain 175x131 pixels of real IR data. SandIR displays these data in a 604x410 image. The maximum matrix size is 640x452 Including VIR and grayscale. Live IR images can be frozen and then stored to computer disk. An incrementing save command makes It easy to save a sequence of images with a series of related file names. These files can then be loaded into SandIR at a later time for anatysis by a number of predefined tools or data probes. Multiple pseudo-color palettes containing 64 colors are available as well as a 256 level grayscale palette for image colorizing. SandtR always processes all the data in the ROt for each acquired image; so a complete temperature matrix is always available for any frozen image. SandIR performs nearly 7 million temperature calculations per second and updates the image display through Direct Draw over the PCI bus at frequencies of 30 Hz. 3-d surface plots, projections, wire maps or contour plots of absolute temperatures are also updated at 20 to 30 Hz which approaches the real-time acquisition rate of the camera, These plots may be viewed full-screen or frozen in separate windows for comparison to later images. The full set of both 2-d and 3-d Origin plotting tools can be used to manipulate the attached plots

  17. Sandia Infrared Analysis Program

    SciTech Connect

    Youchison, Dennis L.

    2004-05-11

    SandIR is a sophisticated Windows2000/WindowsXP program for the capture and analysis of thermal images in real time. It is a 32-bit, 5 thread C++ OOP application that rests on Microsoft’s MFC and DirectDraw libraries, the DT3152LS driver functions and the LabEngine link libraries of Origin 4.1 for full functionality. Images may be loaded in from saved files or viewed live by connection to a FLIR (Inframetrics) 600 or 760 IR camera or a video cassette recorder playing tapes recorded from a FLIR (Inframetrlcs) 600 or 760 IR camera- At this time, no other IR camera formats are supported. The raw radiosity data used by SandiR is derived from the 8-bit, 256 level, RS-170 (grayscale) NTSC camera signal. The FLIR camera images contain 175x131 pixels of real IR data. SandIR displays these data in a 604x410 image. The maximum matrix size is 640x452 Including VIR and grayscale. Live IR images can be frozen and then stored to computer disk. An incrementing save command makes It easy to save a sequence of images with a series of related file names. These files can then be loaded into SandIR at a later time for anatysis by a number of predefined tools or data probes. Multiple pseudo-color palettes containing 64 colors are available as well as a 256 level grayscale palette for image colorizing. SandtR always processes all the data in the ROt for each acquired image; so a complete temperature matrix is always available for any frozen image. SandIR performs nearly 7 million temperature calculations per second and updates the image display through Direct Draw over the PCI bus at frequencies of 30 Hz. 3-d surface plots, projections, wire maps or contour plots of absolute temperatures are also updated at 20 to 30 Hz which approaches the real-time acquisition rate of the camera, These plots may be viewed full-screen or frozen in separate windows for comparison to later images. The full set of both 2-d and 3-d Origin plotting tools can be used to manipulate the attached plots. M plots

  18. NATIONAL GAP ANALYSIS PROGRAM

    EPA Science Inventory

    GAP Analysis is a rapid conservation evaluation method for assessing the current status of biodiversity at large spatial scales. GAP Analysis provides a systematic approach for evaluating the protection afforded biodiversity in given areas. It uses Geographic Information System (...

  19. Applications of Social Network Analysis

    NASA Astrophysics Data System (ADS)

    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.

  20. Interactive analysis program activity

    NASA Technical Reports Server (NTRS)

    Young, J. P.; Frisch, H. P.; Jones, G. K.; Walker, W. J.

    1980-01-01

    The development of an analysis software system capable of performing interdisciplinary preliminary design analyses of large space structure configurations is discussed. Disciplines such as thermal, structures, and controls are to be integrated into a highly user oriented analysis capability. The key feature of the integrated analysis capability, a rapid and efficient system that will minimize solution turnaround time, is discussed.

  1. Network stratification analysis for identifying function-specific network layers.

    PubMed

    Zhang, Chuanchao; Wang, Jiguang; Zhang, Chao; Liu, Juan; Xu, Dong; Chen, Luonan

    2016-04-22

    A major challenge of systems biology is to capture the rewiring of biological functions (e.g. signaling pathways) in a molecular network. To address this problem, we proposed a novel computational framework, namely network stratification analysis (NetSA), to stratify the whole biological network into various function-specific network layers corresponding to particular functions (e.g. KEGG pathways), which transform the network analysis from the gene level to the functional level by integrating expression data, the gene/protein network and gene ontology information altogether. The application of NetSA in yeast and its comparison with a traditional network-partition both suggest that NetSA can more effectively reveal functional implications of network rewiring and extract significant phenotype-related biological processes. Furthermore, for time-series or stage-wise data, the function-specific network layer obtained by NetSA is also shown to be able to characterize the disease progression in a dynamic manner. In particular, when applying NetSA to hepatocellular carcinoma and type 1 diabetes, we can derive functional spectra regarding the progression of the disease, and capture active biological functions (i.e. active pathways) in different disease stages. The additional comparison between NetSA and SPIA illustrates again that NetSA could discover more complete biological functions during disease progression. Overall, NetSA provides a general framework to stratify a network into various layers of function-specific sub-networks, which can not only analyze a biological network on the functional level but also investigate gene rewiring patterns in biological processes. PMID:26879865

  2. Analysis of robustness of urban bus network

    NASA Astrophysics Data System (ADS)

    Tao, Ren; Yi-Fan, Wang; Miao-Miao, Liu; Yan-Jie, Xu

    2016-02-01

    In this paper, the invulnerability and cascade failures are discussed for the urban bus network. Firstly, three static models(bus stop network, bus transfer network, and bus line network) are used to analyse the structure and invulnerability of urban bus network in order to understand the features of bus network comprehensively. Secondly, a new way is proposed to study the invulnerability of urban bus network by modelling two layered networks, i.e., the bus stop-line network and the bus line-transfer network and then the interactions between different models are analysed. Finally, by modelling a new layered network which can reflect the dynamic passenger flows, the cascade failures are discussed. Then a new load redistribution method is proposed to study the robustness of dynamic traffic. In this paper, the bus network of Shenyang City which is one of the biggest cities in China, is taken as a simulation example. In addition, some suggestions are given to improve the urban bus network and provide emergency strategies when traffic congestion occurs according to the numerical simulation results. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473073, 61374178, 61104074, and 61203329), the Fundamental Research Funds for the Central Universities (Grant Nos. N130417006, L1517004), and the Program for Liaoning Excellent Talents in University (Grant No. LJQ2014028).

  3. Health and Physical Education Programs in the National Diffusion Network.

    ERIC Educational Resources Information Center

    Caliguro, Joseph F.

    This catalog contains descriptions of the Health and Physical Education programs in the National Diffusion Network. These programs are available to school systems or other educational institutions for implementation in their classrooms. While all of the programs have been validated as effective by the U.S. Department of Education's Program…

  4. Satellite image analysis using neural networks

    NASA Technical Reports Server (NTRS)

    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.

  5. Muon data analysis program RUMDA

    NASA Astrophysics Data System (ADS)

    Kilcoyne, S. H.

    1994-07-01

    There are currently two data analysis programs available for muon users at ISIS. Both programs can be used for analyzing MuSR and EMU data and can be run on (MUSR01), (EMU01) or set-up to run on a user's account. RUMDA - 'Reading University Muon Data Analysis' was originally from Reading University and is now controlled at ISIS. At present (mid 1994) this suite of programs is run using VAX/VMS and the ISIS plotting package 'GENIE'. It is possible to fit data to any function with a maximum of 10 variables. UDA - 'mu Data Analysis' is a dashboard driven program which allows the user to plot and fit data files on the screen or as hard copies. It is possible to fit data to a combination of Gaussian and/or Lorentzian line shapes. A manual describing this program can be found in the back of the MuSR User Guide.

  6. Interactive cutting path analysis programs

    NASA Technical Reports Server (NTRS)

    Weiner, J. M.; Williams, D. S.; Colley, S. R.

    1975-01-01

    The operation of numerically controlled machine tools is interactively simulated. Four programs were developed to graphically display the cutting paths for a Monarch lathe, Cintimatic mill, Strippit sheet metal punch, and the wiring path for a Standard wire wrap machine. These programs are run on a IMLAC PDS-ID graphic display system under the DOS-3 disk operating system. The cutting path analysis programs accept input via both paper tape and disk file.

  7. Solving deterministic non-linear programming problem using Hopfield artificial neural network and genetic programming techniques

    NASA Astrophysics Data System (ADS)

    Vasant, P.; Ganesan, T.; Elamvazuthi, I.

    2012-11-01

    A fairly reasonable result was obtained for non-linear engineering problems using the optimization techniques such as neural network, genetic algorithms, and fuzzy logic independently in the past. Increasingly, hybrid techniques are being used to solve the non-linear problems to obtain better output. This paper discusses the use of neuro-genetic hybrid technique to optimize the geological structure mapping which is known as seismic survey. It involves the minimization of objective function subject to the requirement of geophysical and operational constraints. In this work, the optimization was initially performed using genetic programming, and followed by hybrid neuro-genetic programming approaches. Comparative studies and analysis were then carried out on the optimized results. The results indicate that the hybrid neuro-genetic hybrid technique produced better results compared to the stand-alone genetic programming method.

  8. The Network Protocol Analysis Technique in Snort

    NASA Astrophysics Data System (ADS)

    Wu, Qing-Xiu

    Network protocol analysis is a network sniffer to capture data for further analysis and understanding of the technical means necessary packets. Network sniffing is intercepted by packet assembly binary format of the original message content. In order to obtain the information contained. Required based on TCP / IP protocol stack protocol specification. Again to restore the data packets at protocol format and content in each protocol layer. Actual data transferred, as well as the application tier.

  9. Network-based social capital and capacity-building programs: an example from Ethiopia

    PubMed Central

    2010-01-01

    Introduction Capacity-building programs are vital for healthcare workforce development in low- and middle-income countries. In addition to increasing human capital, participation in such programs may lead to new professional networks and access to social capital. Although network development and social capital generation were not explicit program goals, we took advantage of a natural experiment and studied the social networks that developed in the first year of an executive-education Master of Hospital and Healthcare Administration (MHA) program in Jimma, Ethiopia. Case description We conducted a sociometric network analysis, which included all program participants and supporters (formally affiliated educators and mentors). We studied two networks: the Trainee Network (all 25 trainees) and the Trainee-Supporter Network (25 trainees and 38 supporters). The independent variable of interest was out-degree, the number of program-related connections reported by each respondent. We assessed social capital exchange in terms of resource exchange, both informational and functional. Contingency table analysis for relational data was used to evaluate the relationship between out-degree and informational and functional exchange. Discussion and evaluation Both networks demonstrated growth and inclusion of most or all network members. In the Trainee Network, those with the highest level of out-degree had the highest reports of informational exchange, χ2 (1, N = 23) = 123.61, p < 0.01. We did not find a statistically significant relationship between out-degree and functional exchange in this network, χ2(1, N = 23) = 26.11, p > 0.05. In the Trainee-Supporter Network, trainees with the highest level of out-degree had the highest reports of informational exchange, χ2 (1, N = 23) = 74.93, p < 0.05. The same pattern held for functional exchange, χ2 (1, N = 23) = 81.31, p < 0.01. Conclusions We found substantial and productive development of social networks in the first year of a

  10. Ecological network analysis for a virtual water network.

    PubMed

    Fang, Delin; Chen, Bin

    2015-06-01

    The notions of virtual water flows provide important indicators to manifest the water consumption and allocation between different sectors via product transactions. However, the configuration of virtual water network (VWN) still needs further investigation to identify the water interdependency among different sectors as well as the network efficiency and stability in a socio-economic system. Ecological network analysis is chosen as a useful tool to examine the structure and function of VWN and the interactions among its sectors. A balance analysis of efficiency and redundancy is also conducted to describe the robustness (RVWN) of VWN. Then, network control analysis and network utility analysis are performed to investigate the dominant sectors and pathways for virtual water circulation and the mutual relationships between pairwise sectors. A case study of the Heihe River Basin in China shows that the balance between efficiency and redundancy is situated on the left side of the robustness curve with less efficiency and higher redundancy. The forestation, herding and fishing sectors and industrial sectors are found to be the main controllers. The network tends to be more mutualistic and synergic, though some competitive relationships that weaken the virtual water circulation still exist. PMID:25938930

  11. Dynamical robustness analysis of weighted complex networks

    NASA Astrophysics Data System (ADS)

    He, Zhiwei; Liu, Shuai; Zhan, Meng

    2013-09-01

    Robustness of weighted complex networks is analyzed from nonlinear dynamical point of view and with focus on different roles of high-degree and low-degree nodes. We find that the phenomenon for the low-degree nodes being the key nodes in the heterogeneous networks only appears in weakly weighted networks and for weak coupling. For all other parameters, the heterogeneous networks are always highly vulnerable to the failure of high-degree nodes; this point is the same as in the structural robustness analysis. We also find that with random inactivation, heterogeneous networks are always more robust than the corresponding homogeneous networks with the same average degree except for one special parameter. Thus our findings give an integrated picture for the dynamical robustness analysis on complex networks.

  12. Quality-assurance results for field pH and specific-conductance measurements, and for laboratory analysis, National Atmospheric Deposition Program and National Trends Network; January 1980-September 1984

    USGS Publications Warehouse

    Schroder, L.J.; Brooks, M.H.; Malo, B.A.; Willoughby, T.C.

    1986-01-01

    Five intersite comparison studies for the field determination of pH and specific conductance, using simulated-precipitation samples, were conducted by the U.S.G.S. for the National Atmospheric Deposition Program and National Trends Network. These comparisons were performed to estimate the precision of pH and specific conductance determinations made by sampling-site operators. Simulated-precipitation samples were prepared from nitric acid and deionized water. The estimated standard deviation for site-operator determination of pH was 0.25 for pH values ranging from 3.79 to 4.64; the estimated standard deviation for specific conductance was 4.6 microsiemens/cm at 25 C for specific-conductance values ranging from 10.4 to 59.0 microsiemens/cm at 25 C. Performance-audit samples with known analyte concentrations were prepared by the U.S.G.S.and distributed to the National Atmospheric Deposition Program 's Central Analytical Laboratory. The differences between the National Atmospheric Deposition Program and national Trends Network-reported analyte concentrations and known analyte concentrations were calculated, and the bias and precision were determined. For 1983, concentrations of calcium, magnesium, sodium, and chloride were biased at the 99% confidence limit; concentrations of potassium and sulfate were unbiased at the 99% confidence limit. Four analytical laboratories routinely analyzing precipitation were evaluated in their analysis of identical natural- and simulated precipitation samples. Analyte bias for each laboratory was examined using analysis of variance coupled with Duncan 's multiple-range test on data produced by these laboratories, from the analysis of identical simulated-precipitation samples. Analyte precision for each laboratory has been estimated by calculating a pooled variance for each analyte. Interlaboratory comparability results may be used to normalize natural-precipitation chemistry data obtained from two or more of these laboratories. (Author

  13. Using automatic programming for simulating reliability network models

    NASA Technical Reports Server (NTRS)

    Tseng, Fan T.; Schroer, Bernard J.; Zhang, S. X.; Wolfsberger, John W.

    1988-01-01

    This paper presents the development of an automatic programming system for assisting modelers of reliability networks to define problems and then automatically generate the corresponding code in the target simulation language GPSS/PC.

  14. NOA: a novel Network Ontology Analysis method

    PubMed Central

    Wang, Jiguang; Huang, Qiang; Liu, Zhi-Ping; Wang, Yong; Wu, Ling-Yun; Chen, Luonan; Zhang, Xiang-Sun

    2011-01-01

    Gene ontology analysis has become a popular and important tool in bioinformatics study, and current ontology analyses are mainly conducted in individual gene or a gene list. However, recent molecular network analysis reveals that the same list of genes with different interactions may perform different functions. Therefore, it is necessary to consider molecular interactions to correctly and specifically annotate biological networks. Here, we propose a novel Network Ontology Analysis (NOA) method to perform gene ontology enrichment analysis on biological networks. Specifically, NOA first defines link ontology that assigns functions to interactions based on the known annotations of joint genes via optimizing two novel indexes ‘Coverage’ and ‘Diversity’. Then, NOA generates two alternative reference sets to statistically rank the enriched functional terms for a given biological network. We compare NOA with traditional enrichment analysis methods in several biological networks, and find that: (i) NOA can capture the change of functions not only in dynamic transcription regulatory networks but also in rewiring protein interaction networks while the traditional methods cannot and (ii) NOA can find more relevant and specific functions than traditional methods in different types of static networks. Furthermore, a freely accessible web server for NOA has been developed at http://www.aporc.org/noa/. PMID:21543451

  15. The SURE Reliability Analysis Program

    NASA Technical Reports Server (NTRS)

    Butler, R. W.

    1986-01-01

    The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The program is based on computational methods recently developed for the NASA Langley Research Center. These methods provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

  16. MANAGER (Michigan Analysis Network and General Evaluation Report) Handbook.

    ERIC Educational Resources Information Center

    Grand Rapids Junior Coll., MI. Office of Curriculum Planning and Evaluation.

    The Michigan Analysis Network and General Evaluation Report (MANAGER) was developed as a component of the overall Michigan Community College Occupational Education Evaluation System (MCCOEES). Developed for use by college presidents and occupational program administrators and instructors, the handbook describes a six-step process for collecting,…

  17. Understanding Groups in Outdoor Adventure Education through Social Network Analysis

    ERIC Educational Resources Information Center

    Jostad, Jeremy; Sibthorp, Jim; Paisley, Karen

    2013-01-01

    Relationships are a critical component to the experience of an outdoor adventure education (OAE) program, therefore, more fruitful ways of investigating groups is needed. Social network analysis (SNA) is an effective tool to study the relationship structure of small groups. This paper provides an explanation of SNA and shows how it was used by the…

  18. NECAP - NASA's Energy Cost Analysis Program. Operations manual

    NASA Technical Reports Server (NTRS)

    Miner, D. L.

    1982-01-01

    The use of the NASA'S ENERGY COST ANALYSIS PROGRAM (NECAP) is described. Supplementary information on new capabilities and program options is also provided. The Control Data Corporation (CDC) NETWORK OPERATING SYSTEM (NOS) is discussed. The basic CDC NOS instructions which are required to successfully operate NECAP are provided.

  19. Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

    NASA Astrophysics Data System (ADS)

    Piao, Chunhui; Han, Xufang; Wu, Harris

    2010-08-01

    We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

  20. Styles Of Programming In Neural Networks And Expert Systems

    NASA Astrophysics Data System (ADS)

    Duda, Richard O.

    1989-03-01

    Neural networks and expert systems provide different ways to reduce the programming effort required to build complex systems. Adaptive neural networks are programmed merely by training them with examples. Rule-based expert system are developed incrementally merely by adding rules. Although neural networks seem best suited for low-level sensory processing and expert systems seem best suited for high-level symbolic processing, strikingly similar issues arise when these approaches are used in large-scale applications. Illustrative examples of such applications are presented and discussed.

  1. The Deep Space Network Advanced Systems Program

    NASA Technical Reports Server (NTRS)

    Davarian, Faramaz

    2010-01-01

    The deep space network (DSN)--with its three complexes in Goldstone, California, Madrid, Spain, and Canberra, Australia--provides the resources to track and communicate with planetary and deep space missions. Each complex consists of an array of capabilities for tracking probes almost anywhere in the solar system. A number of innovative hardware, software and procedural tools are used for day-to-day operations at DSN complexes as well as at the network control at the Jet Propulsion Laboratory (JPL). Systems and technologies employed by the network include large-aperture antennas (34-m and 70-m), cryogenically cooled receivers, high-power transmitters, stable frequency and timing distribution assemblies, modulation and coding schemes, spacecraft transponders, radiometric tracking techniques, etc. The DSN operates at multiple frequencies, including the 2-GHz band, the 7/8-GHz band, and the 32/34-GHz band.

  2. Mars Data Analysis Program

    NASA Technical Reports Server (NTRS)

    McGill, George E.

    2004-01-01

    Grant NAGS12158 addressed a major NASA objective concerning the possibility of a palm ocean or large lake in the northern lowlands of Mars. Our overall approach for this study was an analysis of the graben-bounded giant polygons of Utopia Planitia, but specifically those grabens that define circles rather than open polygons. These circular grabens overlie buried impact craters, and the grabens form because of differential compaction of the overlying material over crater rims and floors. Several years ago, I predicted that the graben circles would bound depressions, and that the depths of these depressions would scale with the diameters of the graben circles. These predictions have been verified by earlier analysis. During this one-year grant (with one-year no-cost extension) we greatly increased the sample size and validated the earlier research robustly. What remained unexplained was why most of the graben circles in Utopia Planitia were double. A new model, involving volumetric compaction rather than simply 2-D compaction, satisfactorily explains the double rings and also provides a measure of relative thickness of the cover material burying the craters as a function of radial distance from the center of the Utopia Basin. Only two materials are likely candidates for the compacting cover material: volcanic ash, or wet sediment. The water in the wet sediment is largely responsible for the volumetric compaction; dry ash will compact vertically but experiences very limited lateral shrinkage. Thus the depressions within the circular grabens and the model explaining the double rings strongly favor wet sediment and thus provide evidence in favor of a past body of standing water in the northern lowlands. Publications supported entirely or in part by this grant are listed below.

  3. Computer program for network synthesis by frequency response fit

    NASA Technical Reports Server (NTRS)

    Green, S.

    1967-01-01

    Computer program synthesizes a passive network by minimizing the difference in desired and actual frequency response. The program solves for the critical points of the error function /weighted least squares fit between calculated and desired frequency response/ by the multivariable Newton-Raphson method with components constrained to an admissible region.

  4. Stochastic flux analysis of chemical reaction networks

    PubMed Central

    2013-01-01

    Background Chemical reaction networks provide an abstraction scheme for a broad range of models in biology and ecology. The two common means for simulating these networks are the deterministic and the stochastic approaches. The traditional deterministic approach, based on differential equations, enjoys a rich set of analysis techniques, including a treatment of reaction fluxes. However, the discrete stochastic simulations, which provide advantages in some cases, lack a quantitative treatment of network fluxes. Results We describe a method for flux analysis of chemical reaction networks, where flux is given by the flow of species between reactions in stochastic simulations of the network. Extending discrete event simulation algorithms, our method constructs several data structures, and thereby reveals a variety of statistics about resource creation and consumption during the simulation. We use these structures to quantify the causal interdependence and relative importance of the reactions at arbitrary time intervals with respect to the network fluxes. This allows us to construct reduced networks that have the same flux-behavior, and compare these networks, also with respect to their time series. We demonstrate our approach on an extended example based on a published ODE model of the same network, that is, Rho GTP-binding proteins, and on other models from biology and ecology. Conclusions We provide a fully stochastic treatment of flux analysis. As in deterministic analysis, our method delivers the network behavior in terms of species transformations. Moreover, our stochastic analysis can be applied, not only at steady state, but at arbitrary time intervals, and used to identify the flow of specific species between specific reactions. Our cases study of Rho GTP-binding proteins reveals the role played by the cyclic reverse fluxes in tuning the behavior of this network. PMID:24314153

  5. Mercury Deposition Network Site Operator Training for the System Blank and Blind Audit Programs

    USGS Publications Warehouse

    Wetherbee, Gregory A.; Lehmann, Christopher M.B.

    2008-01-01

    The U.S. Geological Survey operates the external quality assurance project for the National Atmospheric Deposition Program/Mercury Deposition Network. The project includes the system blank and blind audit programs for assessment of total mercury concentration data quality for wet-deposition samples. This presentation was prepared to train new site operators and to refresh experienced site operators to successfully process and submit system blank and blind audit samples for chemical analysis. Analytical results are used to estimate chemical stability and contamination levels of National Atmospheric Deposition Program/Mercury Deposition Network samples and to evaluate laboratory variability and bias.

  6. Network for Translational Research - Cancer Imaging Program

    Cancer.gov

    Cooperative agreement (U54) awards to establish Specialized Research Resource Centers that will participate as members of a network of inter-disciplinary, inter-institutional research teams for the purpose of supporting translational research in optical imaging and/or spectroscopy in vivo, with an emphasis on multiple modalities.

  7. The NASA trend analysis program

    NASA Technical Reports Server (NTRS)

    Crawford, J. Larry; Weinstock, Robert

    1990-01-01

    The four main areas of the NASA trend analysis program (problem/reliability, performance, supportability, and programmatic trending) are defined and illustrated with examples from Space Shuttle applications. Emphasis is on the programmatic-trending component of the program and several of the statistical techniques used. Also described is the NASA safety, reliability, maintainability, and quality assurance management information center, used to focus management attention on key near-term launch concerns and long-range mission trend issues.

  8. Interchange. Program Improvement Products Identified through Networking.

    ERIC Educational Resources Information Center

    Ohio State Univ., Columbus. National Center for Research in Vocational Education.

    This catalog lists exemplary field-based program improvement products identified by the Dissemination and Utilization Products and Services Program (D&U) at the National Center for Research in Vocational Education. It is designed to increase awareness of these products among vocational educators and to provide information about them that…

  9. Analysis of complex networks using aggressive abstraction.

    SciTech Connect

    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.

  10. An online system for metabolic network analysis

    PubMed Central

    Cicek, Abdullah Ercument; Qi, Xinjian; Cakmak, Ali; Johnson, Stephen R.; Han, Xu; Alshalwi, Sami; Ozsoyoglu, Zehra Meral; Ozsoyoglu, Gultekin

    2014-01-01

    Metabolic networks have become one of the centers of attention in life sciences research with the advancements in the metabolomics field. A vast array of studies analyzes metabolites and their interrelations to seek explanations for various biological questions, and numerous genome-scale metabolic networks have been assembled to serve for this purpose. The increasing focus on this topic comes with the need for software systems that store, query, browse, analyze and visualize metabolic networks. PathCase Metabolomics Analysis Workbench (PathCaseMAW) is built, released and runs on a manually created generic mammalian metabolic network. The PathCaseMAW system provides a database-enabled framework and Web-based computational tools for browsing, querying, analyzing and visualizing stored metabolic networks. PathCaseMAW editor, with its user-friendly interface, can be used to create a new metabolic network and/or update an existing metabolic network. The network can also be created from an existing genome-scale reconstructed network using the PathCaseMAW SBML parser. The metabolic network can be accessed through a Web interface or an iPad application. For metabolomics analysis, steady-state metabolic network dynamics analysis (SMDA) algorithm is implemented and integrated with the system. SMDA tool is accessible through both the Web-based interface and the iPad application for metabolomics analysis based on a metabolic profile. PathCaseMAW is a comprehensive system with various data input and data access subsystems. It is easy to work with by design, and is a promising tool for metabolomics research and for educational purposes. Database URL: http://nashua.case.edu/PathwaysMAW/Web PMID:25267793

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

    ERIC Educational Resources Information Center

    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…

  12. The Holmes Scholars Network: A Networking Mentoring Program of the Holmes Partnership.

    ERIC Educational Resources Information Center

    Lamb, Sara

    1999-01-01

    Describes the Holmes Scholars Network, a national mentoring program for graduate students from racial and cultural groups currently underrepresented in the education professoriate who are preparing to become college faculty in teacher education. Describes how the network operates through the levels of the Holmes Partnerships organizational…

  13. Analysis and Testing of Mobile Wireless Networks

    NASA Technical Reports Server (NTRS)

    Alena, Richard; Evenson, Darin; Rundquist, Victor; Clancy, Daniel (Technical Monitor)

    2002-01-01

    Wireless networks are being used to connect mobile computing elements in more applications as the technology matures. There are now many products (such as 802.11 and 802.11b) which ran in the ISM frequency band and comply with wireless network standards. They are being used increasingly to link mobile Intranet into Wired networks. Standard methods of analyzing and testing their performance and compatibility are needed to determine the limits of the technology. This paper presents analytical and experimental methods of determining network throughput, range and coverage, and interference sources. Both radio frequency (BE) domain and network domain analysis have been applied to determine wireless network throughput and range in the outdoor environment- Comparison of field test data taken under optimal conditions, with performance predicted from RF analysis, yielded quantitative results applicable to future designs. Layering multiple wireless network- sooners can increase performance. Wireless network components can be set to different radio frequency-hopping sequences or spreading functions, allowing more than one sooner to coexist. Therefore, we ran multiple 802.11-compliant systems concurrently in the same geographical area to determine interference effects and scalability, The results can be used to design of more robust networks which have multiple layers of wireless data communication paths and provide increased throughput overall.

  14. Extending Stochastic Network Calculus to Loss Analysis

    PubMed Central

    Yu, Li; Zheng, Jun

    2013-01-01

    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. PMID:24228019

  15. Computer network environment planning and analysis

    NASA Technical Reports Server (NTRS)

    Dalphin, John F.

    1989-01-01

    The GSFC Computer Network Environment provides a broadband RF cable between campus buildings and ethernet spines in buildings for the interlinking of Local Area Networks (LANs). This system provides terminal and computer linkage among host and user systems thereby providing E-mail services, file exchange capability, and certain distributed computing opportunities. The Environment is designed to be transparent and supports multiple protocols. Networking at Goddard has a short history and has been under coordinated control of a Network Steering Committee for slightly more than two years; network growth has been rapid with more than 1500 nodes currently addressed and greater expansion expected. A new RF cable system with a different topology is being installed during summer 1989; consideration of a fiber optics system for the future will begin soon. Summmer study was directed toward Network Steering Committee operation and planning plus consideration of Center Network Environment analysis and modeling. Biweekly Steering Committee meetings were attended to learn the background of the network and the concerns of those managing it. Suggestions for historical data gathering have been made to support future planning and modeling. Data Systems Dynamic Simulator, a simulation package developed at NASA and maintained at GSFC was studied as a possible modeling tool for the network environment. A modeling concept based on a hierarchical model was hypothesized for further development. Such a model would allow input of newly updated parameters and would provide an estimation of the behavior of the network.

  16. Network interface unit design options performance analysis

    NASA Technical Reports Server (NTRS)

    Miller, Frank W.

    1991-01-01

    An analysis is presented of three design options for the Space Station Freedom (SSF) onboard Data Management System (DMS) Network Interface Unit (NIU). The NIU provides the interface from the Fiber Distributed Data Interface (FDDI) local area network (LAN) to the DMS processing elements. The FDDI LAN provides the primary means for command and control and low and medium rate telemetry data transfers on board the SSF. The results of this analysis provide the basis for the implementation of the NIU.

  17. Transient Analysis Generator /TAG/ simulates behavior of large class of electrical networks

    NASA Technical Reports Server (NTRS)

    Thomas, W. J.

    1967-01-01

    Transient Analysis Generator program simulates both transient and dc steady-state behavior of a large class of electrical networks. It generates a special analysis program for each circuit described in an easily understood and manipulated programming language. A generator or preprocessor and a simulation system make up the TAG system.

  18. WATER QUALITY ANALYSIS SIMULATION PROGRAM

    EPA Science Inventory

    The Water Quality Analysis Simulation Program (WASP6), an enhancement of the original WASP (Di Toro et al., 1983; Connolly and Winfield,1984; Ambrose, R.B. et al.,1988). This model helps users interpret and predict water quality responses to natural phenomena and man-made polluti...

  19. Performance Analysis of a NASA Integrated Network Array

    NASA Technical Reports Server (NTRS)

    Nessel, James A.

    2012-01-01

    The Space Communications and Navigation (SCaN) Program is planning to integrate its individual networks into a unified network which will function as a single entity to provide services to user missions. This integrated network architecture is expected to provide SCaN customers with the capabilities to seamlessly use any of the available SCaN assets to support their missions to efficiently meet the collective needs of Agency missions. One potential optimal application of these assets, based on this envisioned architecture, is that of arraying across existing networks to significantly enhance data rates and/or link availabilities. As such, this document provides an analysis of the transmit and receive performance of a proposed SCaN inter-network antenna array. From the study, it is determined that a fully integrated internetwork array does not provide any significant advantage over an intra-network array, one in which the assets of an individual network are arrayed for enhanced performance. Therefore, it is the recommendation of this study that NASA proceed with an arraying concept, with a fundamental focus on a network-centric arraying.

  20. Program Instrumentation and Trace Analysis

    NASA Technical Reports Server (NTRS)

    Havelund, Klaus; Goldberg, Allen; Filman, Robert; Rosu, Grigore; Koga, Dennis (Technical Monitor)

    2002-01-01

    Several attempts have been made recently to apply techniques such as model checking and theorem proving to the analysis of programs. This shall be seen as a current trend to analyze real software systems instead of just their designs. This includes our own effort to develop a model checker for Java, the Java PathFinder 1, one of the very first of its kind in 1998. However, model checking cannot handle very large programs without some kind of abstraction of the program. This paper describes a complementary scalable technique to handle such large programs. Our interest is turned on the observation part of the equation: How much information can be extracted about a program from observing a single execution trace? It is our intention to develop a technology that can be applied automatically and to large full-size applications, with minimal modification to the code. We present a tool, Java PathExplorer (JPaX), for exploring execution traces of Java programs. The tool prioritizes scalability for completeness, and is directed towards detecting errors in programs, not to prove correctness. One core element in JPaX is an instrumentation package that allows to instrument Java byte code files to log various events when executed. The instrumentation is driven by a user provided script that specifies what information to log. Examples of instructions that such a script can contain are: 'report name and arguments of all called methods defined in class C, together with a timestamp'; 'report all updates to all variables'; and 'report all acquisitions and releases of locks'. In more complex instructions one can specify that certain expressions should be evaluated and even that certain code should be executed under various conditions. The instrumentation package can hence be seen as implementing Aspect Oriented Programming for Java in the sense that one can add functionality to a Java program without explicitly changing the code of the original program, but one rather writes an

  1. Network and adaptive system of systems modeling and analysis.

    SciTech Connect

    Lawton, Craig R.; Campbell, James E. Dr.; Anderson, Dennis James; Eddy, John P.

    2007-05-01

    This report documents the results of an LDRD program entitled ''Network and Adaptive System of Systems Modeling and Analysis'' that was conducted during FY 2005 and FY 2006. The purpose of this study was to determine and implement ways to incorporate network communications modeling into existing System of Systems (SoS) modeling capabilities. Current SoS modeling, particularly for the Future Combat Systems (FCS) program, is conducted under the assumption that communication between the various systems is always possible and occurs instantaneously. A more realistic representation of these communications allows for better, more accurate simulation results. The current approach to meeting this objective has been to use existing capabilities to model network hardware reliability and adding capabilities to use that information to model the impact on the sustainment supply chain and operational availability.

  2. Network analysis of cosmic structures: network centrality and topological environment

    NASA Astrophysics Data System (ADS)

    Hong, Sungryong; Dey, Arjun

    2015-06-01

    We apply simple analyses techniques developed for the study of complex networks to the study of the cosmic web, the large-scale galaxy distribution. In this paper, we measure three network centralities (ranks of topological importance): degree centrality (DC), closeness centrality (CL), and betweenness centrality (BC) from a network built from the Cosmological Evolution Survey (COSMOS) catalogue. We define eight galaxy populations according to the centrality measures: void, wall, and cluster by DC; main branch and dangling leaf by BC; and kernel, backbone, and fracture by CL. We also define three populations by Voronoi tessellation density to compare these with the DC selection. We apply the topological selections to galaxies in the (photometric) redshift range 0.91 < z < 0.94 from the COSMOS survey, and explore whether the red and blue galaxy populations show differences in colour, star formation rate, and stellar mass in the different topological regions. Despite the limitations and uncertainties associated with using photometric redshift and indirect measurements of galactic parameters, the preliminary results illustrate the potential of network analysis. Future surveys will provide better statistical samples to test and improve this `network cosmology'.

  3. The International Trade Network: weighted network analysis and modelling

    NASA Astrophysics Data System (ADS)

    Bhattacharya, K.; Mukherjee, G.; Saramäki, J.; Kaski, K.; Manna, S. S.

    2008-02-01

    Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN.

  4. NEXCADE: perturbation analysis for complex networks.

    PubMed

    Yadav, Gitanjali; Babu, Suresh

    2012-01-01

    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. PMID:22870252

  5. NEXCADE: Perturbation Analysis for Complex Networks

    PubMed Central

    Yadav, Gitanjali; Babu, Suresh

    2012-01-01

    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. PMID:22870252

  6. Network Anomaly Detection Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

    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.

  7. HOST structural analysis program overview

    NASA Technical Reports Server (NTRS)

    Thompson, Robert L.

    1986-01-01

    Hot-section components of aircraft gas turbine engines are subjected to severe thermal structural loading conditions, especially during the startup and takeoff portions of the engine cycle. The most severe and damaging stresses and strains are those induced by the steep thermal gradients induced during the startup transient. These transient stresses and strains are also the most difficult to predict, in part because the temperature gradients and distributions are not well known or readily predictable and, in part, because the cyclic elastic-viscoplastic behavior of the materials at these extremes of temperature and strain are not well known or readily predictable. A broad spectrum of structures related technology programs is underway to address these deficiencies at the basic as well as the applied level. The three key program elements in the HOST structural analysis program are computations, constitutive modeling, and experiments for each research activity. Also shown are tables summarizing each of the activities.

  8. Cross-Disciplinary Detection and Analysis of Network Motifs

    PubMed Central

    Tran, Ngoc Tam L; DeLuccia, Luke; McDonald, Aidan F; Huang, Chun-Hsi

    2015-01-01

    The detection of network motifs has recently become an important part of network analysis across all disciplines. In this work, we detected and analyzed network motifs from undirected and directed networks of several different disciplines, including biological network, social network, ecological network, as well as other networks such as airlines, power grid, and co-purchase of political books networks. Our analysis revealed that undirected networks are similar at the basic three and four nodes, while the analysis of directed networks revealed the distinction between networks of different disciplines. The study showed that larger motifs contained the three-node motif as a subgraph. Topological analysis revealed that similar networks have similar small motifs, but as the motif size increases, differences arise. Pearson correlation coefficient showed strong positive relationship between some undirected networks but inverse relationship between some directed networks. The study suggests that the three-node motif is a building block of larger motifs. It also suggests that undirected networks share similar low-level structures. Moreover, similar networks share similar small motifs, but larger motifs define the unique structure of individuals. Pearson correlation coefficient suggests that protein structure networks, dolphin social network, and co-authorships in network science belong to a superfamily. In addition, yeast protein–protein interaction network, primary school contact network, Zachary’s karate club network, and co-purchase of political books network can be classified into a superfamily. PMID:25983553

  9. Cross-disciplinary detection and analysis of network motifs.

    PubMed

    Tran, Ngoc Tam L; DeLuccia, Luke; McDonald, Aidan F; Huang, Chun-Hsi

    2015-01-01

    The detection of network motifs has recently become an important part of network analysis across all disciplines. In this work, we detected and analyzed network motifs from undirected and directed networks of several different disciplines, including biological network, social network, ecological network, as well as other networks such as airlines, power grid, and co-purchase of political books networks. Our analysis revealed that undirected networks are similar at the basic three and four nodes, while the analysis of directed networks revealed the distinction between networks of different disciplines. The study showed that larger motifs contained the three-node motif as a subgraph. Topological analysis revealed that similar networks have similar small motifs, but as the motif size increases, differences arise. Pearson correlation coefficient showed strong positive relationship between some undirected networks but inverse relationship between some directed networks. The study suggests that the three-node motif is a building block of larger motifs. It also suggests that undirected networks share similar low-level structures. Moreover, similar networks share similar small motifs, but larger motifs define the unique structure of individuals. Pearson correlation coefficient suggests that protein structure networks, dolphin social network, and co-authorships in network science belong to a superfamily. In addition, yeast protein-protein interaction network, primary school contact network, Zachary's karate club network, and co-purchase of political books network can be classified into a superfamily. PMID:25983553

  10. Space Surveillance Network Sensor Development, Modification, and Sustainment Programs

    NASA Astrophysics Data System (ADS)

    Colarco, R.

    The paper and presentation will cover status of and plans for sensor development, modification, and sustainment programs supporting the Space Surveillance Network, including: Space Based Space Surveillance early orbit operations Space Surveillance Telescope development and expected performance FPS-85 radar service life extension program Haystack Ultra-Wideband Satellite Imaging Radar modification and expected performance improvement Space Fence development the future of GLOBUS II SSA Environmental Monitoring development Self-Awareness SSA development.

  11. Kinetic analysis of complex metabolic networks

    SciTech Connect

    Stephanopoulos, G.

    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.

  12. Medical image analysis with artificial neural networks.

    PubMed

    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. PMID:20713305

  13. A survey of current software for network analysis in molecular biology

    PubMed Central

    2010-01-01

    Software for network motifs and modules is briefly reviewed, along with programs for network comparison. The three major software packages for network analysis, CYTOSCAPE, INGENUITY and PATHWAY STUDIO, and their associated databases, are compared in detail. A comparative test evaluated how these software packages perform the search for key terms and the creation of network from those terms and from experimental expression data. PMID:20650822

  14. Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks

    NASA Technical Reports Server (NTRS)

    Cheung, Kar-Ming; Lee, Charles H.

    2012-01-01

    We developed framework and the mathematical formulation for optimizing communication network using mixed integer programming. The design yields a system that is much smaller, in search space size, when compared to the earlier approach. Our constrained network optimization takes into account the dynamics of link performance within the network along with mission and operation requirements. A unique penalty function is introduced to transform the mixed integer programming into the more manageable problem of searching in a continuous space. The constrained optimization problem was proposed to solve in two stages: first using the heuristic Particle Swarming Optimization algorithm to get a good initial starting point, and then feeding the result into the Sequential Quadratic Programming algorithm to achieve the final optimal schedule. We demonstrate the above planning and scheduling methodology with a scenario of 20 spacecraft and 3 ground stations of a Deep Space Network site. Our approach and framework have been simple and flexible so that problems with larger number of constraints and network can be easily adapted and solved.

  15. Engaging Adults in Literacy Programs at Neighborhood Networks Centers.

    ERIC Educational Resources Information Center

    Department of Housing and Urban Development, Washington, DC.

    This publication is designed to help Neighborhood Networks centers create programs that meet the goals of adult literacy learners. (The centers provide residents of federally assisted or insured properties with training in economic self-sufficiency.) Chapter 1 highlights the special characteristics of adult learners--the challenges they face and…

  16. Social Networking Tools to Facilitate Cross-Program Collaboration

    ERIC Educational Resources Information Center

    Wallace, Paul; Howard, Barbara

    2010-01-01

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

  17. Transforming Equity-Oriented Leaders: Principal Residency Network Program Evaluation

    ERIC Educational Resources Information Center

    Braun, Donna; Billups, Felice D.; Gable, Robert K.

    2013-01-01

    After 12 years focused on developing school leaders who act as change agents for educational equity, the Principal Residency Network (PRN) partnered with Johnson and Wales University's Center for Research and Evaluation to conduct a utilization-focused (Patton, 2002) program evaluation funded by a grant from the Rhode Island Foundation. The…

  18. Workshop: Western hemisphere network of bird banding programs

    USGS Publications Warehouse

    Celis-Murillo, A.

    2007-01-01

    Purpose: To promote collaboration among banding programs in the Americas. Introduction: Bird banding and marking provide indispensable tools for ornithological research, management, and conservation of migratory birds on migratory routes, breeding and non-breeding grounds. Many countries and organizations in Latin America and the Caribbean are in the process of developing or have expressed interest in developing national banding schemes and databases to support their research and management programs. Coordination of developing and existing banding programs is essential for effective data management, reporting, archiving and security, and most importantly, for gaining a fuller understanding of migratory bird conservation issues and how the banding data can help. Currently, there is a well established bird-banding program in the U.S.A. and Canada, and programs in other countries are being developed as well. Ornithologists in many Latin American countries and the Caribbean are interested in using banding and marking in their research programs. Many in the ornithological community are interested in establishing banding schemes and some countries have recently initiated independent banding programs. With the number of long term collaborative and international initiatives increasing, the time is ripe to discuss and explore opportunities for international collaboration, coordination, and administration of bird banding programs in the Western Hemisphere. We propose the second ?Western Hemisphere Network of Bird Banding Programs? workshop, in association with the SCSCB, to be an essential step in the progress to strengthen international partnerships and support migratory bird conservation in the Americas and beyond. This will be the second multi-national meeting to promote collaboration among banding programs in the Americas (the first meeting was held in October 8-9, 2006 in La Mancha, Veracruz, Mexico). The Second ?Western Hemisphere Network of Bird Banding Programs

  19. Reconstructing cerebrovascular networks under local physiological constraints by integer programming

    SciTech Connect

    Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D.; Xiao, Xianghui; Stock, Stuart R.; Klohs, Jan; Szekely, Gabor; Andres, Bjoern; Menze, Bjoern H.

    2015-04-23

    We introduce a probabilistic approach to vessel network extraction that enforces physiological constraints on the vessel structure. The method accounts for both image evidence and geometric relationships between vessels by solving an integer program, which is shown to yield the maximum a posteriori (MAP) estimate to the probabilistic model. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating the local geometry and the global connectivity of the graph. We utilize a high-resolution micro computed tomography (µCT) dataset of a cerebrovascular corrosion cast to obtain a reference network and learn the prior distributions of our probabilistic model. As a result, we perform experiments on micro magnetic resonance angiography (µMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.

  20. Reconstructing cerebrovascular networks under local physiological constraints by integer programming

    DOE PAGESBeta

    Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D.; Xiao, Xianghui; Stock, Stuart R.; Klohs, Jan; Szekely, Gabor; Andres, Bjoern; Menze, Bjoern H.

    2015-04-23

    We introduce a probabilistic approach to vessel network extraction that enforces physiological constraints on the vessel structure. The method accounts for both image evidence and geometric relationships between vessels by solving an integer program, which is shown to yield the maximum a posteriori (MAP) estimate to the probabilistic model. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating the local geometry and the global connectivity of the graph. We utilize a high-resolution micro computed tomography (µCT) dataset of a cerebrovascular corrosion cast to obtain a reference network and learn the prior distributions of ourmore » probabilistic model. As a result, we perform experiments on micro magnetic resonance angiography (µMRA) images of mouse brains and discuss properties of the networks obtained under different tracking and pruning approaches.« less

  1. A biologically inspired neural network for dynamic programming.

    PubMed

    Francelin Romero, R A; Kacpryzk, J; Gomide, F

    2001-12-01

    An artificial neural network with a two-layer feedback topology and generalized recurrent neurons, for solving nonlinear discrete dynamic optimization problems, is developed. A direct method to assign the weights of neural networks is presented. The method is based on Bellmann's Optimality Principle and on the interchange of information which occurs during the synaptic chemical processing among neurons. The neural network based algorithm is an advantageous approach for dynamic programming due to the inherent parallelism of the neural networks; further it reduces the severity of computational problems that can occur in methods like conventional methods. Some illustrative application examples are presented to show how this approach works out including the shortest path and fuzzy decision making problems. PMID:11852439

  2. Using social network analysis to inform disease control interventions.

    PubMed

    Marquetoux, Nelly; Stevenson, Mark A; Wilson, Peter; Ridler, Anne; Heuer, Cord

    2016-04-01

    Contact patterns between individuals are an important determinant for the spread of infectious diseases in populations. Social network analysis (SNA) describes contact patterns and thus indicates how infectious pathogens may be transmitted. Here we explore network characteristics that may inform the development of disease control programes. This study applies SNA methods to describe a livestock movement network of 180 farms in New Zealand from 2006 to 2010. We found that the number of contacts was overall consistent from year to year, while the choice of trading partners tended to vary. This livestock movement network illustrated how a small number of farms central to the network could play a potentially dominant role for the spread of infection in this population. However, fragmentation of the network could easily be achieved by "removing" a small proportion of farms serving as bridges between otherwise isolated clusters, thus decreasing the probability of large epidemics. This is the first example of a comprehensive analysis of pastoral livestock movements in New Zealand. We conclude that, for our system, recording and exploiting livestock movements can contribute towards risk-based control strategies to prevent and monitor the introduction and the spread of infectious diseases in animal populations. PMID:26883965

  3. Mathematical analysis techniques for modeling the space network activities

    NASA Technical Reports Server (NTRS)

    Foster, Lisa M.

    1992-01-01

    The objective of the present work was to explore and identify mathematical analysis techniques, and in particular, the use of linear programming. This topic was then applied to the Tracking and Data Relay Satellite System (TDRSS) in order to understand the space network better. Finally, a small scale version of the system was modeled, variables were identified, data was gathered, and comparisons were made between actual and theoretical data.

  4. Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

    PubMed Central

    2011-01-01

    Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis. PMID:22784571

  5. Genetic Network Programming with Intron-Like Nodes

    NASA Astrophysics Data System (ADS)

    Mabu, Shingo; Chen, Yan; Eto, Shinji; Shimada, Kaoru; Hirasawa, Kotaro

    Recently, Genetic Network Programming (GNP) has been proposed, which is an extension of Genetic Algorithm(GA) and Genetic Programming(GP). GNP can make compact programs and can memorize the past history in it implicitly, because it expresses the solution by directed graphs and therefore, it can reuse the nodes. In this research, intron-like nodes are introduced for improving the performance of GNP. The aim of introducing intron-like nodes is to use every node as much as possible. It is found from simulations that the intron-like nodes are useful for improving the training speed and generalization ability.

  6. NAPS: Network Analysis of Protein Structures.

    PubMed

    Chakrabarty, Broto; Parekh, Nita

    2016-07-01

    Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue-residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein-protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

  7. Program Aids Analysis And Optimization Of Design

    NASA Technical Reports Server (NTRS)

    Rogers, James L., Jr.; Lamarsh, William J., II

    1994-01-01

    NETS/ PROSSS (NETS Coupled With Programming System for Structural Synthesis) computer program developed to provide system for combining NETS (MSC-21588), neural-network application program and CONMIN (Constrained Function Minimization, ARC-10836), optimization program. Enables user to reach nearly optimal design. Design then used as starting point in normal optimization process, possibly enabling user to converge to optimal solution in significantly fewer iterations. NEWT/PROSSS written in C language and FORTRAN 77.

  8. Cosmic physics data analysis program

    NASA Technical Reports Server (NTRS)

    Wilkes, R. Jeffrey

    1993-01-01

    A data analysis program was carried out to investigate the intensity, propagation, and origin of primary Cosmic Ray Galactic electrons. Scanning was carried out on two new balloon flight experiments as well as the border area of previous experiments. The identification and evaluation of the energies of the primary electrons were carried out. A new analysis of these data were incorporated into an overall evaluation of the roll of electrons in the problem of the origin of cosmic rays. Recent measurements indicate that the earth may be within the expanding Geminga supernova shock wave which is expected to have a major effect upon the propagation and the energy spectrum of galactic electrons. Calculations with the Geminga model indicate that the cut-off energy may be very close to the observed highest energy electrons in our analysis.

  9. A FORTRAN Program for Discrete Discriminant Analysis

    ERIC Educational Resources Information Center

    Boone, James O.; Brewer, James K.

    1976-01-01

    A Fortran program is presented for discriminant analysis of discrete variables. The program assumes discrete, nominal data with no distributional, variance-covariance assumptions. The program handles a maximum of fifty predictor variables and twelve outcome groups. (Author/JKS)

  10. HOST structural analysis program overview

    NASA Technical Reports Server (NTRS)

    Johns, R. H.

    1983-01-01

    Hot section components of aircraft gas turbine engines are subjected to severe thermal structural loading conditions, especially during the start up and take off portions of the engine cycle. The most severe and damaging stresses and strains are those induced by the steep thermal gradients induced during the start up transient. These transient stresses and strains are also the most difficult to predict, in part because of the temperature gradients and distributions are not well known or readily predictable, and also because the cyclic elastic viscoplastic behavior of the materials at these extremes of temperature and strain are not well known or readily predictable. A broad spectrum of structures related technology programs is underway to address these deficiencies. One element of the structures program is developing improved time varying thermal mechanical load models for the entire engine mission cycle from start up to shutdown. Another major part of the program is the development of new and improved nonlinear 3-D finite elements and associated structural analysis programs, including the development of temporal elements with time dependent properties to account for creep effects in the materials and components.

  11. Program for Analyzing Flows in a Complex Network

    NASA Technical Reports Server (NTRS)

    Majumdar, Alok Kumar

    2006-01-01

    Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.

  12. Network analysis of eight industrial symbiosis systems

    NASA Astrophysics Data System (ADS)

    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).

  13. Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis.

    PubMed

    Cao, Mu-Shui; Liu, Bing-Ya; Dai, Wen-Tao; Zhou, Wei-Xin; Li, Yi-Xue; Li, Yuan-Yuan

    2015-01-01

    Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing

  14. Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis

    PubMed Central

    Cao, Mu-Shui; Liu, Bing-Ya; Dai, Wen-Tao; Zhou, Wei-Xin; Li, Yi-Xue; Li, Yuan-Yuan

    2015-01-01

    Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing

  15. Network analysis of an online community

    NASA Astrophysics Data System (ADS)

    Han, Sangman; Kim, Beom Jun

    2008-10-01

    We empirically study various network properties of an online community. The numbers of articles written by each user to the bulletin boards of each of the others are used to construct the directed and weighted network B, and gifting behaviors among users are also kept track of, to build the network G which is again directed and weighted. Detailed analysis reveals that B and G have very different network properties. In particular, whereas B contains many more bidirectional links than directed arcs, G shows the opposite characteristic. The number of writings on bulletin boards is found to decay with the distance from the hub vertex, which reflects the structural assortativeness in B. We also observe that the activities in writings and purchases are negatively correlated with each other for highly active users in B.

  16. DCS-Neural-Network Program for Aircraft Control and Testing

    NASA Technical Reports Server (NTRS)

    Jorgensen, Charles C.

    2006-01-01

    A computer program implements a dynamic-cell-structure (DCS) artificial neural network that can perform such tasks as learning selected aerodynamic characteristics of an airplane from wind-tunnel test data and computing real-time stability and control derivatives of the airplane for use in feedback linearized control. A DCS neural network is one of several types of neural networks that can incorporate additional nodes in order to rapidly learn increasingly complex relationships between inputs and outputs. In the DCS neural network implemented by the present program, the insertion of nodes is based on accumulated error. A competitive Hebbian learning rule (a supervised-learning rule in which connection weights are adjusted to minimize differences between actual and desired outputs for training examples) is used. A Kohonen-style learning rule (derived from a relatively simple training algorithm, implements a Delaunay triangulation layout of neurons) is used to adjust node positions during training. Neighborhood topology determines which nodes are used to estimate new values. The network learns, starting with two nodes, and adds new nodes sequentially in locations chosen to maximize reductions in global error. At any given time during learning, the error becomes homogeneously distributed over all nodes.

  17. Neural network programming in bioprocess variable estimation and state prediction.

    PubMed

    Linko, P; Zhu, Y H

    1991-12-01

    A neural network program with efficient learning ability for bioprocess variable estimation and state prediction was developed. A 3 layer, feed-forward neural network architecture was used, and the program was written in Quick C ver 2.5 for an IBM compatible computer with a 80486/33 MHz processor. A back propagation training algorithm was used based on learning by pattern and momentum in a combination as used to adjust the connection of weights of the neurons in adjacent layers. The delta rule was applied in a gradient descent search technique to minimize a cost function equal to the mean square difference between the target and the network output. A non-linear, sigmoidal logistic transfer function was used in squashing the weighted sum of the inputs of each neuron to a limited range output. A good neural network prediction model was obtained by training with a sequence of past time course data of a typical bioprocess. The well trained neural network estimated accurately and rapidly the state variables with or without noise even under varying process dynamics. PMID:1367695

  18. Developing an intelligence analysis process through social network analysis

    NASA Astrophysics Data System (ADS)

    Waskiewicz, Todd; LaMonica, Peter

    2008-04-01

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

  19. Conducting a SWOT Analysis for Program Improvement

    ERIC Educational Resources Information Center

    Orr, Betsy

    2013-01-01

    A SWOT (strengths, weaknesses, opportunities, and threats) analysis of a teacher education program, or any program, can be the driving force for implementing change. A SWOT analysis is used to assist faculty in initiating meaningful change in a program and to use the data for program improvement. This tool is useful in any undergraduate or degree…

  20. Differential Network Analysis in Human Cancer Research

    PubMed Central

    Gill, Ryan; Datta, Somnath; Datta, Susmita

    2016-01-01

    A complex disease like cancer is hardly caused by one gene or one protein singly. It is usually caused by the perturbation of the network formed by several genes or proteins. In the last decade several research teams have attempted to construct interaction maps of genes and proteins either experimentally or reverse engineer interaction maps using computational techniques. These networks were usually created under a certain condition such as an environmental condition, a particular disease, or a specific tissue type. Lately, however, there has been greater emphasis on finding the differential structure of the existing network topology under a novel condition or disease status to elucidate the perturbation in a biological system. In this review/tutorial article we briefly mention some of the research done in this area; we mainly illustrate the computational/statistical methods developed by our team in recent years for differential network analysis using publicly available gene expression data collected from a well known cancer study. This data includes a group of patients with acute lymphoblastic leukemia and a group with acute myeloid leukemia. In particular, we describe the statistical tests to detect the change in the network topology based on connectivity scores which measure the association or interaction between pairs of genes. The tests under various scores are applied to this data set to perform a differential network analysis on gene expression for human leukemia. We believe that, in the future, differential network analysis will be a standard way to view the changes in gene expression and protein expression data globally and these types of tests could be useful in analyzing the complex differential signatures. PMID:23530503

  1. Phylodynamic analysis of a viral infection network

    PubMed Central

    Shiino, Teiichiro

    2012-01-01

    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. PMID:22993510

  2. Safeguard Vulnerability Analysis Program (SVAP)

    SciTech Connect

    Gilman, F.M.; Dittmore, M.H.; Orvis, W.J.; Wahler, P.S.

    1980-06-23

    This report gives an overview of the Safeguard Vulnerability Analysis Program (SVAP) developed at Lawrence Livermore National Laboratory. SVAP was designed as an automated method of analyzing the safeguard systems at nuclear facilities for vulnerabilities relating to the theft or diversion of nuclear materials. SVAP addresses one class of safeguard threat: theft or diversion of nuclear materials by nonviolent insiders, acting individually or in collusion. SVAP is a user-oriented tool which uses an interactive input medium for preprocessing the large amounts of safeguards data. Its output includes concise summary data as well as detailed vulnerability information.

  3. Planetary Protection Bioburden Analysis Program

    NASA Technical Reports Server (NTRS)

    Beaudet, Robert A.

    2013-01-01

    This program is a Microsoft Access program that performed statistical analysis of the colony counts from assays performed on the Mars Science Laboratory (MSL) spacecraft to determine the bioburden density, 3-sigma biodensity, and the total bioburdens required for the MSL prelaunch reports. It also contains numerous tools that report the data in various ways to simplify the reports required. The program performs all the calculations directly in the MS Access program. Prior to this development, the data was exported to large Excel files that had to be cut and pasted to provide the desired results. The program contains a main menu and a number of submenus. Analyses can be performed by using either all the assays, or only the accountable assays that will be used in the final analysis. There are three options on the first menu: either calculate using (1) the old MER (Mars Exploration Rover) statistics, (2) the MSL statistics for all the assays, or This software implements penetration limit equations for common micrometeoroid and orbital debris (MMOD) shield configurations, windows, and thermal protection systems. Allowable MMOD risk is formulated in terms of the probability of penetration (PNP) of the spacecraft pressure hull. For calculating the risk, spacecraft geometry models, mission profiles, debris environment models, and penetration limit equations for installed shielding configurations are required. Risk assessment software such as NASA's BUMPERII is used to calculate mission PNP; however, they are unsuitable for use in shield design and preliminary analysis studies. The software defines a single equation for the design and performance evaluation of common MMOD shielding configurations, windows, and thermal protection systems, along with a description of their validity range and guidelines for their application. Recommendations are based on preliminary reviews of fundamental assumptions, and accuracy in predicting experimental impact test results. The software

  4. Multichannel Networked Phasemeter Readout and Analysis

    NASA Technical Reports Server (NTRS)

    Edmonds, Karina

    2008-01-01

    Netmeter software reads a data stream from up to 250 networked phasemeters, synchronizes the data, saves the reduced data to disk (after applying a low-pass filter), and provides a Web server interface for remote control. Unlike older phasemeter software that requires a special, real-time operating system, this program can run on any general-purpose computer. It needs about five percent of the CPU (central processing unit) to process 20 channels because it adds built-in data logging and network-based GUIs (graphical user interfaces) that are implemented in Scalable Vector Graphics (SVG). Netmeter runs on Linux and Windows. It displays the instantaneous displacements measured by several phasemeters at a user-selectable rate, up to 1 kHz. The program monitors the measure and reference channel frequencies. For ease of use, levels of status in Netmeter are color coded: green for normal operation, yellow for network errors, and red for optical misalignment problems. Netmeter includes user-selectable filters up to 4 k samples, and user-selectable averaging windows (after filtering). Before filtering, the program saves raw data to disk using a burst-write technique.

  5. 75 FR 57521 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-21

    ... FOUNDATION Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010... Coordination Office for Networking and Information Technology Research and Development (NITRD) requests... National Coordination Office for the Networking and Information Technology Research and Development...

  6. Fault tolerance analysis of the class of rearrangeable interconnection networks

    SciTech Connect

    Pakzad, S. . Dept. of Electrical Engineering)

    1989-08-01

    This paper analyzes the fault tolerance characteristics of a range or rearrangeable {beta}-networks based on the concepts and the framework developed by S. Pakzad and S. Lakshmivarahan. These rearrangeable {beta}-networks include the Benes network, the Waksman network, the Joel network, and the serial network. In addition, this paper presents a comparative analysis of the aforementioned networks according to their hardware cost, performance, and degree of fault tolerance.

  7. Mapping Creativity: Creativity Measurements Network Analysis

    ERIC Educational Resources Information Center

    Pinheiro, Igor Reszka; Cruz, Roberto Moraes

    2014-01-01

    This article borrowed network analysis tools to discover how the construct formed by the set of all measures of creativity configures itself. To this end, using a variant of the meta-analytical method, a database was compiled simulating 42,381 responses to 974 variables centered on 64 creativity measures. Results, although preliminary, indicate…

  8. Nonlinear Time Series Analysis via Neural Networks

    NASA Astrophysics Data System (ADS)

    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.

  9. Neural network analysis of W UMa eclipsing binaries

    NASA Astrophysics Data System (ADS)

    Zeraatgari, F. Z.; Abedi, A.; Farshad, M.; Ebadian, M.; Riazi, N.

    2015-04-01

    We try five different artificial neural models, four models based on PNN (Perceptron Neural Network), and one using GRNN (Generalized Regression Neural Network) as tools for the automated light curve analysis of W UMa-type eclipsing binary systems. These algorithms, which are inspired by the Rucinski method, are designed and trained using MATLAB 7.6. A total of 17,820 generated contact binary light curves are first analyzed using a truncated cosine series with 11 coefficients and the most significant coefficients are applied as inputs of the neural models. The required sample light curves are systematically generated, using the WD2007 program (Wilson and Devinney 2007). The trained neural models are then applied to estimate the geometrical parameters of seven W UMa-type systems. The efficiency of different neural network models are then evaluated and compared to find the most efficient one.

  10. Diversity Performance Analysis on Multiple HAP Networks.

    PubMed

    Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

    2015-01-01

    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. PMID:26134102

  11. Analysis of Social Networks by Tensor Decomposition

    NASA Astrophysics Data System (ADS)

    Sizov, Sergej; Staab, Steffen; Franz, Thomas

    The Social Web fosters novel applications targeting a more efficient and satisfying user guidance in modern social networks, e.g., for identifying thematically focused communities, or finding users with similar interests. Large scale and high diversity of users in social networks poses the challenging question of appropriate relevance/authority ranking, for producing fine-grained and rich descriptions of available partners, e.g., to guide the user along most promising groups of interest. Existing methods for graph-based authority ranking lack support for fine-grained latent coherence between user relations and content (i.e., support for edge semantics in graph-based social network models). We present TweetRank, a novel approach for faceted authority ranking in the context of social networks. TweetRank captures the additional latent semantics of social networks by means of statistical methods in order to produce richer descriptions of user relations. We model the social network by a 3-dimensional tensor that enables the seamless representation of arbitrary semantic relations. For the analysis of that model, we apply the PARAFAC decomposition, which can be seen as a multi-modal counterpart to common Web authority ranking with HITS. The result are groupings of users and terms, characterized by authority and navigational (hub) scores with respect to the identified latent topics. Sample experiments with life data of the Twitter community demonstrate the ability of TweetRank to produce richer and more comprehensive contact recommendations than other existing methods for social authority ranking.

  12. Diversity Performance Analysis on Multiple HAP Networks

    PubMed Central

    Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue

    2015-01-01

    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. PMID:26134102

  13. National Ignition Facility (NIF) Control Network Design and Analysis

    SciTech Connect

    Bryant, R M; Carey, R W; Claybourn, R V; Pavel, G; Schaefer, W J

    2001-10-19

    The control network for the National Ignition Facility (NIF) is designed to meet the needs for common object request broker architecture (CORBA) inter-process communication, multicast video transport, device triggering, and general TCP/IP communication within the NIF facility. The network will interconnect approximately 650 systems, including the embedded controllers, front-end processors (FEPs), supervisory systems, and centralized servers involved in operation of the NIF. All systems are networked with Ethernet to serve the majority of communication needs, and asynchronous transfer mode (ATM) is used to transport multicast video and synchronization triggers. CORBA software infra-structure provides location-independent communication services over TCP/IP between the application processes in the 15 supervisory and 300 FEP systems. Video images sampled from 500 video cameras at a 10-Hz frame rate will be multicast using direct ATM Application Programming Interface (API) communication from video FEPs to any selected operator console. The Ethernet and ATM control networks are used to broadcast two types of device triggers for last-second functions in a large number of FEPs, thus eliminating the need for a separate infrastructure for these functions. Analysis, design, modeling, and testing of the NIF network has been performed to provide confidence that the network design will meet NIF control requirements.

  14. Vulnerability analysis methods for road networks

    NASA Astrophysics Data System (ADS)

    Bíl, Michal; Vodák, Rostislav; Kubeček, Jan; Rebok, Tomáš; Svoboda, Tomáš

    2014-05-01

    Road networks rank among the most important lifelines of modern society. They can be damaged by either random or intentional events. Roads are also often affected by natural hazards, the impacts of which are both direct and indirect. Whereas direct impacts (e.g. roads damaged by a landslide or due to flooding) are localized in close proximity to the natural hazard occurrence, the indirect impacts can entail widespread service disabilities and considerable travel delays. The change in flows in the network may affect the population living far from the places originally impacted by the natural disaster. These effects are primarily possible due to the intrinsic nature of this system. The consequences and extent of the indirect costs also depend on the set of road links which were damaged, because the road links differ in terms of their importance. The more robust (interconnected) the road network is, the less time is usually needed to secure the serviceability of an area hit by a disaster. These kinds of networks also demonstrate a higher degree of resilience. Evaluating road network structures is therefore essential in any type of vulnerability and resilience analysis. There are a range of approaches used for evaluation of the vulnerability of a network and for identification of the weakest road links. Only few of them are, however, capable of simulating the impacts of the simultaneous closure of numerous links, which often occurs during a disaster. The primary problem is that in the case of a disaster, which usually has a large regional extent, the road network may remain disconnected. The majority of the commonly used indices use direct computation of the shortest paths or time between OD (origin - destination) pairs and therefore cannot be applied when the network breaks up into two or more components. Since extensive break-ups often occur in cases of major disasters, it is important to study the network vulnerability in these cases as well, so that appropriate

  15. Centrality Analysis Methods for Biological Networks and Their Application to Gene Regulatory Networks

    PubMed Central

    Koschützki, Dirk; Schreiber, Falk

    2008-01-01

    The structural analysis of biological networks includes the ranking of the vertices based on the connection structure of a network. To support this analysis we discuss centrality measures which indicate the importance of vertices, and demonstrate their applicability on a gene regulatory network. We show that common centrality measures result in different valuations of the vertices and that novel measures tailored to specific biological investigations are useful for the analysis of biological networks, in particular gene regulatory networks. PMID:19787083

  16. Pathway and network analysis of cancer genomes.

    PubMed

    2015-07-01

    Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations. PMID:26125594

  17. Pathway and Network Analysis of Cancer Genomes

    PubMed Central

    Haider, Syed; Wu, Guanming; Shibata, Tatsuhiro; Vazquez, Miguel; Mustonen, Ville; Gonzalez-Perez, Abel; Pearson, John; Sander, Chris; Raphael, Benjamin J.; Marks, Debora S.; Ouellette, B.F. Francis; Valencia, Alfonso; Bader, Gary D.; Boutros, Paul C.; Stuart, Joshua M.; Linding, Rune; Lopez-Bigas, Nuria; Stein, Lincoln D.

    2016-01-01

    Genomic information on tumors from 50 cancer types catalogued by The International Cancer Genome Consortium (ICGC) shows that only few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been large interest in developing pathway and network analysis methods that group genes and illuminate the processes involved. We provide an overview of these analysis techniques and show where they guide mechanistic and translational investigations. PMID:26125594

  18. Personal Computer Transport Analysis Program

    NASA Technical Reports Server (NTRS)

    DiStefano, Frank, III; Wobick, Craig; Chapman, Kirt; McCloud, Peter

    2012-01-01

    The Personal Computer Transport Analysis Program (PCTAP) is C++ software used for analysis of thermal fluid systems. The program predicts thermal fluid system and component transients. The output consists of temperatures, flow rates, pressures, delta pressures, tank quantities, and gas quantities in the air, along with air scrubbing component performance. PCTAP s solution process assumes that the tubes in the system are well insulated so that only the heat transfer between fluid and tube wall and between adjacent tubes is modeled. The system described in the model file is broken down into its individual components; i.e., tubes, cold plates, heat exchangers, etc. A solution vector is built from the components and a flow is then simulated with fluid being transferred from one component to the next. The solution vector of components in the model file is built at the initiation of the run. This solution vector is simply a list of components in the order of their inlet dependency on other components. The component parameters are updated in the order in which they appear in the list at every time step. Once the solution vectors have been determined, PCTAP cycles through the components in the solution vector, executing their outlet function for each time-step increment.

  19. Metabolomics integrated elementary flux mode analysis in large metabolic networks

    PubMed Central

    Gerstl, Matthias P.; Ruckerbauer, David E.; Mattanovich, Diethard; Jungreuthmayer, Christian; Zanghellini, Jürgen

    2015-01-01

    Elementary flux modes (EFMs) are non-decomposable steady-state pathways in metabolic networks. They characterize phenotypes, quantify robustness or identify engineering targets. An EFM analysis (EFMA) is currently restricted to medium-scale models, as the number of EFMs explodes with the network's size. However, many topologically feasible EFMs are biologically irrelevant. We present thermodynamic EFMA (tEFMA), which calculates only the small(er) subset of thermodynamically feasible EFMs. We integrate network embedded thermodynamics into EFMA and show that we can use the metabolome to identify and remove thermodynamically infeasible EFMs during an EFMA without losing biologically relevant EFMs. Calculating only the thermodynamically feasible EFMs strongly reduces memory consumption and program runtime, allowing the analysis of larger networks. We apply tEFMA to study the central carbon metabolism of E. coli and find that up to 80% of its EFMs are thermodynamically infeasible. Moreover, we identify glutamate dehydrogenase as a bottleneck, when E. coli is grown on glucose and explain its inactivity as a consequence of network embedded thermodynamics. We implemented tEFMA as a Java package which is available for download at https://github.com/mpgerstl/tEFMA. PMID:25754258

  20. Momentum Integral Network Method for Thermal-Hydraulic Systems Analysis.

    Energy Science and Technology Software Center (ESTSC)

    2000-11-20

    EPIPE is used for design or design evaluation of complex large piping systems. The piping systems can be viewed as a network of straight pipe elements (or tangents) and curved elements (pipe bends) interconnected at joints (or nodes) with intermediate supports and anchors. The system may be subject to static loads such as thermal, dead weight, internal pressure, or dynamic loads such as earthquake motions and flow-induced vibrations, or any combination of these. MINET (Momentummore » Integral NETwork) was developed for the transient analysis of intricate fluid flow and heat transfer networks, such as those found in the balance of plant in power generating facilities. It can be utilized as a stand-alone program or interfaced to another computer program for concurrent analysis. Through such coupling, a computer code limited by either the lack of required component models or large computational needs can be extended to more fully represent the thermal hydraulic system thereby reducing the need for estimating essential transient boundary conditions. The MINET representation of a system is one or more networks of volumes, segments, and boundaries linked together via heat exchangers only, i.e., heat can transfer between networks, but fluids cannot. Volumes are used to represent tanks or other volume components, as well as locations in the system where significant flow divisions or combinations occur. Segments are composed of one or more pipes, pumps, heat exchangers, turbines, and/or valves each represented by one or more nodes. Boundaries are simply points where the network interfaces with the user or another computer code. Several fluids can be simulated, including water, sodium, NaK, and air.« less

  1. Momentum Integral Network Method for Thermal-Hydraulic Systems Analysis.

    SciTech Connect

    2000-11-20

    EPIPE is used for design or design evaluation of complex large piping systems. The piping systems can be viewed as a network of straight pipe elements (or tangents) and curved elements (pipe bends) interconnected at joints (or nodes) with intermediate supports and anchors. The system may be subject to static loads such as thermal, dead weight, internal pressure, or dynamic loads such as earthquake motions and flow-induced vibrations, or any combination of these. MINET (Momentum Integral NETwork) was developed for the transient analysis of intricate fluid flow and heat transfer networks, such as those found in the balance of plant in power generating facilities. It can be utilized as a stand-alone program or interfaced to another computer program for concurrent analysis. Through such coupling, a computer code limited by either the lack of required component models or large computational needs can be extended to more fully represent the thermal hydraulic system thereby reducing the need for estimating essential transient boundary conditions. The MINET representation of a system is one or more networks of volumes, segments, and boundaries linked together via heat exchangers only, i.e., heat can transfer between networks, but fluids cannot. Volumes are used to represent tanks or other volume components, as well as locations in the system where significant flow divisions or combinations occur. Segments are composed of one or more pipes, pumps, heat exchangers, turbines, and/or valves each represented by one or more nodes. Boundaries are simply points where the network interfaces with the user or another computer code. Several fluids can be simulated, including water, sodium, NaK, and air.

  2. The Portals 4.0 network programming interface.

    SciTech Connect

    Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin Thomas Tauke; Wheeler, Kyle Bruce; Hemmert, Karl Scott; Riesen, Rolf E.; Underwood, Keith Douglas; Maccabe, Arthur Bernard; Hudson, Trammell B.

    2012-11-01

    This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities.

  3. The portals 4.0.1 network programming interface.

    SciTech Connect

    Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin Thomas Tauke; Wheeler, Kyle Bruce; Hemmert, Karl Scott; Riesen, Rolf E.; Underwood, Keith Douglas; Maccabe, Arthur Bernard; Hudson, Trammell B.

    2013-04-01

    This report presents a specification for the Portals 4.0 network programming interface. Portals 4.0 is intended to allow scalable, high-performance network communication between nodes of a parallel computing system. Portals 4.0 is well suited to massively parallel processing and embedded systems. Portals 4.0 represents an adaption of the data movement layer developed for massively parallel processing platforms, such as the 4500-node Intel TeraFLOPS machine. Sandia's Cplant cluster project motivated the development of Version 3.0, which was later extended to Version 3.3 as part of the Cray Red Storm machine and XT line. Version 4.0 is targeted to the next generation of machines employing advanced network interface architectures that support enhanced offload capabilities. 3

  4. Time series analysis of temporal networks

    NASA Astrophysics Data System (ADS)

    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

  5. The New Algorithm for Symbolic Network Analysis.

    NASA Astrophysics Data System (ADS)

    Chow, John Tsai-Chiang

    A new and highly efficient tree identification algorithm is derived here for obtaining the determinant and the cofactors of a circuit's node admittance matrix, and hence, for obtaining various symbolic network functions for one-port and two-port reciprocal and nonreciprocal networks, with the network's topological description as its input. The algorithm is so devised that it is practically memory-storage free, and it is simple enough that even a microcomputer can obtain symbolic network functions for a fairly large circuit in a reasonably short time. It is worth noting that the algorithm can handle topological branches with infinite admittance values. Making use of this special feature, we have derived a simple topological model for the ideal operational amplifier, hence providing the ability to obtain various topological formulas of operational amplifier circuits in a reasonable time. By choosing appropriate symbolic network functions, along with some measured transfer function data, the circuit's nominal element values, and a nonlinear-equation solving subroutine, we have constructed a computer program to perform analog circuit fault diagnosis. This program can identify which of a circuit's elements are faulty or out of design tolerances. In the course of this research we have also identified an application to a biological problem, one in which the resistor values of an electrical model of the guinea-pig cochlea can easily be deduced even when some nodes are inaccessible for measurements. All these features have been implemented on a very modest microcomputer, the Apple II. Obviously, a larger computer will not only accomplish the same result faster but also it will be capable of analyzing much larger circuits.

  6. The Lunar Quest Program and the International Lunar Network (ILN)

    NASA Technical Reports Server (NTRS)

    Cohen, Barbara A.

    2009-01-01

    The Lunar and Planetary Science group at Marshall provides core capabilities to support the Agency's lunar exploration goals. ILN Anchor Nodes are currently in development by MSFC and APL under the Lunar Quest Program at MSFC. The Science objectives of the network are to understand the interior structure and composition of the moon. Pre-phase A engineering assessments are complete, showing a design that can achieve the science requirements, either on their own (if 4 launched) or in concert with international partners. Risk reduction activities are ongoing. The Lunar Quest Program is a Science-based program with the following goals: a) Fly small/medium science missions to accomplish key science goals; b) Build a strong lunar science community; c) Provide opportunities to demonstrate new technologies; and d) Where possible, help ESMD and SOMG goals and enhance presence of science in the implementation of the VSE. The Lunar Quest Program will be guided by recommendations from community reports.

  7. Response Neighborhoods in Online Learning Networks: A Quantitative Analysis

    ERIC Educational Resources Information Center

    Aviv, Reuven; Erlich, Zippy; Ravid, Gilad

    2005-01-01

    Theoretical foundation of Response mechanisms in networks of online learners are revealed by Statistical Analysis of p* Markov Models for the Networks. Our comparative analysis of two networks shows that the minimal-effort hunt-for-social-capital mechanism controls a major behavior of both networks: negative tendency to respond. Differences in…

  8. ASAP- ARTIFICIAL SATELLITE ANALYSIS PROGRAM

    NASA Technical Reports Server (NTRS)

    Kwok, J.

    1994-01-01

    The Artificial Satellite Analysis Program (ASAP) is a general orbit prediction program which incorporates sufficient orbit modeling accuracy for mission design, maneuver analysis, and mission planning. ASAP is suitable for studying planetary orbit missions with spacecraft trajectories of reconnaissance (flyby) and exploratory (mapping) nature. Sample data is included for a geosynchronous station drift cycle study, a Venus radar mapping strategy, a frozen orbit about Mars, and a repeat ground trace orbit. ASAP uses Cowell's method in the numerical integration of the equations of motion. The orbital mechanics calculation contains perturbations due to non-sphericity (up to a 40 X 40 field) of the planet, lunar and solar effects, and drag and solar radiation pressure. An 8th order Runge-Kutta integration scheme with variable step size control is used for efficient propagation. The input includes the classical osculating elements, orbital elements of the sun relative to the planet, reference time and dates, drag coefficient, gravitational constants, and planet radius, rotation rate, etc. The printed output contains Cartesian coordinates, velocity, equinoctial elements, and classical elements for each time step or event step. At each step, selected output is added to a plot file. The ASAP package includes a program for sorting this plot file. LOTUS 1-2-3 is used in the supplied examples to graph the results, but any graphics software package could be used to process the plot file. ASAP is not written to be mission-specific. Instead, it is intended to be used for most planetary orbiting missions. As a consequence, the user has to have some basic understanding of orbital mechanics to provide the correct input and interpret the subsequent output. ASAP is written in FORTRAN 77 for batch execution and has been implemented on an IBM PC compatible computer operating under MS-DOS. The ASAP package requires a math coprocessor and a minimum of 256K RAM. This program was last

  9. Construction and analysis of biochemical networks

    NASA Astrophysics Data System (ADS)

    Binns, Michael; Theodoropoulos, Constantinos

    2012-09-01

    Bioprocesses are being implemented for a range of different applications including the production of fuels, chemicals and drugs. Hence, it is becoming increasingly important to understand and model how they function and how they can be modified or designed to give the optimal performance. Here we discuss the construction and analysis of biochemical networks which are the first logical steps towards this goal. The construction of a reaction network is possible through reconstruction: extracting information from literature and from databases. This can be supplemented by reaction prediction methods which can identify steps which are missing from the current knowledge base. Analysis of biochemical systems generally requires some experimental input but can be used to identify important reactions and targets for enhancing the performance of the organism involved. Metabolic flux, pathway and metabolic control analysis can be used to determine the limits, capabilities and potential targets for enhancement respectively.

  10. Transportability in Network Meta-analysis.

    PubMed

    Kabali, Conrad; Ghazipura, Marya

    2016-07-01

    Network meta-analysis is an extension of the conventional pair wise meta-analysis to include treatments that have not been compared head to head. It has in recent years caught the interest of clinical investigators in comparative effectiveness research. While allowing a simultaneous comparison of a large number of treatment effects, an inclusion of indirect effects (i.e., estimating effects using treatments that have not been randomized head to head) may introduce bias. This bias occurs from not accounting for covariates differences in the analysis, in a way that allows transfer of causal information across trials. Although this problem might not be entirely new to network meta-analysis researchers, it has not been given a formal treatment. Occasionally it is tackled by fitting a meta-regression model to account for imbalance of covariates. However, this approach may still produce biased estimates if covariates responsible for disparity across studies are post-treatment variables. To address the problem, we use the graphical method known as transportability to demonstrate whether and how indirect treatment effects can validly be estimated in network meta-analysis. See Video Abstract at http://links.lww.com/EDE/B37. PMID:26963292

  11. Network design for heavy rainfall analysis

    NASA Astrophysics Data System (ADS)

    Rietsch, T.; Naveau, P.; Gilardi, N.; Guillou, A.

    2013-12-01

    The analysis of heavy rainfall distributional properties is a complex object of study in hydrology and climatology, and it is essential for impact studies. In this paper, we investigate the question of how to optimize the spatial design of a network of existing weather stations. Our main criterion for such an inquiry is the capability of the network to capture the statistical properties of heavy rainfall described by the Extreme Value Theory. We combine this theory with a machine learning algorithm based on neural networks and a Query By Committee approach. Our resulting algorithm is tested on simulated data and applied to high-quality extreme daily precipitation measurements recorded in France at 331 weather stations during the time period 1980-2010.

  12. Micro-macro analysis of complex networks.

    PubMed

    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. PMID:25635812

  13. Micro-Macro Analysis of Complex Networks

    PubMed Central

    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. PMID:25635812

  14. Analysis of Cascading Failure in Gene Networks

    PubMed Central

    Sun, Longxiao; Wang, Shudong; Li, Kaikai; Meng, Dazhi

    2012-01-01

    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. 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. PMID:23248647

  15. ROOT CAUSE ANALYSIS PROGRAM MANUAL

    SciTech Connect

    Gravois, Melanie C.

    2007-05-02

    Root Cause Analysis (RCA) identifies the cause of an adverse condition that, if corrected, will preclude recurrence or greatly reduce the probability of recurrence of the same or similar adverse conditions and thereby protect the health and safety of the public, the workers, and the environment. This procedure sets forth the requirements for management determination and the selection of RCA methods and implementation of RCAs that are a result of significant findings from Price-Anderson Amendments Act (PAAA) violations, occurrences/events, Significant Adverse Conditions, and external oversight Corrective Action Requests (CARs) generated by the Office of Enforcement (PAAA headquarters), the U.S. Environmental Protection Agency, and other oversight entities against Lawrence Berkeley National Laboratory (LBNL). Performance of an RCA may result in the identification of issues that should be reported in accordance with the Issues Management Program Manual.

  16. 13C NMR Metabolomics: INADEQUATE Network Analysis

    PubMed Central

    Clendinen, Chaevien S.; Pasquel, Christian; Ajredini, Ramadan; Edison, Arthur S.

    2015-01-01

    The many advantages of 13C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, 13C NMR offers a straightforward measurement of these compounds. Two-dimensional 13C-13C correlation experiments like INADEQUATE (incredible natural abundance double quantum transfer experiment) are ideal for the structural elucidation of natural products and have great but untapped potential for metabolomics analysis. We demonstrate a new and semi-automated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE datasets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures. PMID:25932900

  17. An improved viscous characteristics analysis program

    NASA Technical Reports Server (NTRS)

    Jenkins, R. V.

    1978-01-01

    An improved two dimensional characteristics analysis program is presented. The program is built upon the foundation of a FORTRAN program entitled Analysis of Supersonic Combustion Flow Fields With Embedded Subsonic Regions. The major improvements are described and a listing of the new program is provided. The subroutines and their functions are given as well as the input required for the program. Several applications of the program to real problems are qualitatively described. Three runs obtained in the investigation of a real problem are presented to provide insight for the input and output of the program.

  18. Value flow mapping: Using networks to inform stakeholder analysis

    NASA Astrophysics Data System (ADS)

    Cameron, Bruce G.; Crawley, Edward F.; Loureiro, Geilson; Rebentisch, Eric S.

    2008-02-01

    Stakeholder theory has garnered significant interest from the corporate community, but has proved difficult to apply to large government programs. A detailed value flow exercise was conducted to identify the value delivery mechanisms among stakeholders for the current Vision for Space Exploration. We propose a method for capturing stakeholder needs that explicitly recognizes the outcomes required of the value creating organization. The captured stakeholder needs are then translated into input-output models for each stakeholder, which are then aggregated into a network model. Analysis of this network suggests that benefits are infrequently linked to the root provider of value. Furthermore, it is noted that requirements should not only be written to influence the organization's outputs, but also to influence the propagation of benefit further along the value chain. A number of future applications of this model to systems architecture and requirement analysis are discussed.

  19. Static analysis of cable networks and their supporting structures

    SciTech Connect

    Mitsugi, J.

    1994-04-01

    A nonlinear static analysis method for cable structures, particularly emphasizing cable networks, is presented. Cable strains are measured from the current geometry and compressed cables are analytically disassembled with the construction of the equilibrium equation and the stiffness matrix. Finite rotations of cable intersections, referred to as nodes, and cable elements passing through more than two nodes are included in the formulation. An integrated analysis with a linear finite element method is also presented to account for the elastic deformations of supporting structures for the cable networks. The formulation is programmed for a CRAY2 supercomputer using parallel processing to solve the linear equations. Applications of the method used for mesh antenna development are also presented. 13 refs.

  20. Automatic analysis of the control of metabolic networks.

    PubMed

    Bayram, M

    1996-09-01

    In this paper we apply computer algebra techniques to analyze the control of metabolic networks. For this purpose, a computer program based on metabolic control theory was developed. When a stoichiometry matrix of the metabolic networks is given, the program calculates all the control coefficients (flux and metabolic control coefficients, summation and connectivity relationships) using elasticity coefficients. The program can be applied to any metabolic network which includes unlimited steps and intermediate metabolites. PMID:8889337

  1. Visual Analysis of Complex Networks and Community Structure

    NASA Astrophysics Data System (ADS)

    Wu, Bin; Ye, Qi; Wang, Yi; Bi, Ran; Suo, Lijun; Hu, Deyong; Yang, Shengqi

    Many real-world domains can be represented as complex networks.A good visualization of a large and complex network is worth more than millions of words. Visual depictions of networks, which exploit human visual processing, are more prone to cognition of the structure of such complex networks than the computational representation. We star by briefly introducing some key technologies of network visualization, such as graph drawing algorithm and community discovery methods. The typical tools for network visualization are also reviewed. A newly developed software framework JSNVA for network visual analysis is introduced. Finally,the applications of JSNVA in bibliometric analysis and mobile call graph analysis are presented.

  2. Statistical energy analysis computer program, user's guide

    NASA Technical Reports Server (NTRS)

    Trudell, R. W.; Yano, L. I.

    1981-01-01

    A high frequency random vibration analysis, (statistical energy analysis (SEA) method) is examined. The SEA method accomplishes high frequency prediction of arbitrary structural configurations. A general SEA computer program is described. A summary of SEA theory, example problems of SEA program application, and complete program listing are presented.

  3. Use of Some "Discriminant Analysis" Computer Programs

    ERIC Educational Resources Information Center

    Huberty, Carl J.

    1977-01-01

    The objective of this paper is to review the outputs of selected computer programs often used to carry out a "discriminant analysis" with respect to two purposes of such an analysis, discrimination and classification. The programs selected are three BMD programs. (Author/JKS)

  4. Computer Programming in a Spatial Analysis Course.

    ERIC Educational Resources Information Center

    Gesler, Wilbert; Kaplan, Abram

    1993-01-01

    Contends that students in spatial analysis courses generally are familiar with computer use and programs but lack basic computer programing skills. Describes four exercises in which students learn programing using BASIC and dBASE. Asserts that programming exercises help students clarify concepts, understand the rationale behind calculations, use…

  5. Computer aided nonlinear electrical networks analysis

    NASA Technical Reports Server (NTRS)

    Slapnicar, P.

    1977-01-01

    Techniques used in simulating an electrical circuit with nonlinear elements for use in computer-aided circuit analysis programs are described. Elements of the circuit include capacitors, resistors, inductors, transistors, diodes, and voltage and current sources (constant or time varying). Simulation features are discussed for dc, ac, and/or transient circuit analysis. Calculations are based on the model approach of formulating the circuit equations. A particular solution of transient analysis for nonlinear storage elements is described.

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

    NASA Astrophysics Data System (ADS)

    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.

  7. Dataflow Analysis for Datarace-Free Programs

    NASA Astrophysics Data System (ADS)

    de, Arnab; D'Souza, Deepak; Nasre, Rupesh

    Memory models for shared-memory concurrent programming languages typically guarantee sequential consistency (SC) semantics for datarace-free (DRF) programs, while providing very weak or no guarantees for non-DRF programs. In effect programmers are expected to write only DRF programs, which are then executed with SC semantics. With this in mind, we propose a novel scalable solution for dataflow analysis of concurrent programs, which is proved to be sound for DRF programs with SC semantics. We use the synchronization structure of the program to propagate dataflow information among threads without requiring to consider all interleavings explicitly. Given a dataflow analysis that is sound for sequential programs and meets certain criteria, our technique automatically converts it to an analysis for concurrent programs.

  8. The Application of Social Network Analysis to Team Sports

    ERIC Educational Resources Information Center

    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…

  9. A calculus for network delay. I - Network elements in isolation. II - Network analysis

    NASA Astrophysics Data System (ADS)

    Cruz, Rene L.

    1991-01-01

    A calculus is developed to obtain bounds on delay and buffering requirements in a packet-switched communication network operating under a fixed routing strategy. This theory differs from traditional delay-analysis approaches because the model used to describe the entry of data into the network is nonprobabilistic. It is supposed that the data stream entered into the network by a user satisfies burstiness constraints; i.e., the quantity of data in any interval of time is less than a value that depends on the length of the interval. Several network elements are defined that can be used as building blocks to model a wide variety of communication networks. Each type of element is analyzed by assuming that the traffic entering it satisfies burstiness constraints, and bounds on element delay and buffering requirements are obtained. Burstiness constraints satisfied by the traffic that exits the element are derived, and the effectiveness of the regulator elements in reducing maximum network delay is demonstrated with examples.

  10. 77 FR 55479 - Medicare, Medicaid, and CHIP Programs: Research and Analysis on Impact of CMS Programs on the...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-10

    ... and Analysis on Impact of CMS Programs on the Indian Health Care System AGENCY: Centers for Medicare... expansion of research on the impact of CMS programs on the Indian health care system through a single source... health care services to American Indian/ Alaska Native (AI/AN) people through a network of...

  11. Program Support Communications Network (PSCN) facsimile system directory

    NASA Technical Reports Server (NTRS)

    1992-01-01

    This directory provides a system description, a station listing, and operating procedures for the Program Support Communications Network (PSCN) NASA Facsimile System. The NASA Facsimile System is a convenient and efficient means of spanning the distance, time, and cost of transmitting documents from one person to another. In the spectrum of communication techniques, facsimile bridges the gap between mail and data transmission. Facsimile can transmit in a matter of minutes or seconds what would take a day or more by mail delivery. The NASA Facsimile System is composed of several makes and models of facsimile machines. The system also supports the 3M FaxXchange network controllers located at Marshall Space Flight Center (MSFC).

  12. Thermal-Hydraulic-Analysis Program

    NASA Technical Reports Server (NTRS)

    Walton, J. T.

    1993-01-01

    ELM computer program is simple computational tool for modeling steady-state thermal hydraulics of flows of propellants through fuel-element-coolant channels in nuclear thermal rockets. Evaluates various heat-transfer-coefficient and friction-factor correlations available for turbulent pipe flow with addition of heat. Comparisons possible within one program. Machine-independent program written in FORTRAN 77.

  13. NIF ICCS network design and loading analysis

    SciTech Connect

    Tietbohl, G; Bryant, R

    1998-02-20

    The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738).

  14. Distinguishing manipulated stocks via trading network analysis

    NASA Astrophysics Data System (ADS)

    Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang

    2011-10-01

    Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.

  15. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ....658, see the List of CFR Sections Affected which appears in the Finding Aids section of the printed... 47 Telecommunication 4 2010-10-01 2010-10-01 false Affiliation agreements and network program practices; territorial exclusivity in non-network program arrangements. 73.658 Section...

  16. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ....658, see the List of CFR Sections Affected which appears in the Finding Aids section of the printed... 47 Telecommunication 4 2011-10-01 2011-10-01 false Affiliation agreements and network program practices; territorial exclusivity in non-network program arrangements. 73.658 Section...

  17. Network Enrichment Analysis in Complex Experiments*

    PubMed Central

    Shojaie, Ali; Michailidis, George

    2010-01-01

    Cellular functions of living organisms are carried out through complex systems of interacting components. Including such interactions in the analysis, and considering sub-systems defined by biological pathways instead of individual components (e.g. genes), can lead to new findings about complex biological mechanisms. Networks are often used to capture such interactions and can be incorporated in models to improve the efficiency in estimation and inference. In this paper, we propose a model for incorporating external information about interactions among genes (proteins/metabolites) in differential analysis of gene sets. We exploit the framework of mixed linear models and propose a flexible inference procedure for analysis of changes in biological pathways. The proposed method facilitates the analysis of complex experiments, including multiple experimental conditions and temporal correlations among observations. We propose an efficient iterative algorithm for estimation of the model parameters and show that the proposed framework is asymptotically robust to the presence of noise in the network information. The performance of the proposed model is illustrated through the analysis of gene expression data for environmental stress response (ESR) in yeast, as well as simulated data sets. PMID:20597848

  18. FORTRAN program for induction motor analysis

    NASA Technical Reports Server (NTRS)

    Bollenbacher, G.

    1976-01-01

    A FORTRAN program for induction motor analysis is described. The analysis includes calculations of torque-speed characteristics, efficiency, losses, magnetic flux densities, weights, and various electrical parameters. The program is limited to three-phase Y-connected, squirrel-cage motors. Detailed instructions for using the program are given. The analysis equations are documented, and the sources of the equations are referenced. The appendixes include a FORTRAN symbol list, a complete explanation of input requirements, and a list of error messages.

  19. A comparative analysis of network robustness against different link attacks

    NASA Astrophysics Data System (ADS)

    Duan, Boping; Liu, Jing; Zhou, Mingxing; Ma, Liangliang

    2016-04-01

    Recently, the study of optimizing network robustness has attracted increasing attentions, and the constraint that every node's degree cannot be changed is considered. Although this constraint maintains the node degree distribution consistently in order to reserve the structure of networks, it makes the network structure be lack of flexibility since many network structure always transform in the modern society. Given this consideration, in this paper, we analyze the robustness of networks through setting a new constraint; that is, only the number of edges should be unchanged. Then, we use the link-robustness index (Rl) as the measure of the network robustness against either random failures or intentional attacks, and make a comparative analysis of network robustness against different types of link attacks. Moreover, we use four types of networks as initial networks, namely scale-free networks, random networks, regular networks, and small-world networks. The experimental results show that the values of robustness measures for the optimized networks starting from different initial networks are similar under different link attacks, but the network topologies may be different. That is to say, networks with different topologies may have similar robustness in terms of the robustness measures. We also find that the optimized networks obtained by one link attack may not robust against other link attacks, sometimes, even weaker than the original networks. Therefore, before building networks, it is better to study which type of link attacks may happen.

  20. Applications of Complex Networks on Analysis of World Trade Network

    NASA Astrophysics Data System (ADS)

    Lee, Jae Woo; Maeng, Seong Eun; Ha, Gyeong-Gyun; Hyeok Lee, Moon; Cho, Eun Seong

    2013-02-01

    We consider the wealth and the money flow of the world trade data. We analyze the world trade data from year 1948 to 2000 which include the total amounts of the import and export for every country per year. We apply the analyzing methods of the complex networks to the world trade network. We define the wealth as the gross domestic products (GDP) of each country. We defined the backbone network of the world trade network. We generate the backbone network keeping the link with the largest wealth flowing out each country by the import and deleting all remaining links. We observed that the wealth was transferred from the poorer countries to the wealthier countries. We found the asymmetry of the world trade flow by the disparity of the networks. From the backbone network of the world trade we can identify the regional economic connections and wealth flow among the countries.

  1. Outcome of the Gynecologic Oncology Patients Surveillance Network Program.

    PubMed

    Suprasert, Prapaporn; Suwansirikul, Songkiat; Charoenkwan, Kittipat; Cheewakriangkrai, Chalong; Suwansirikul, Songkiat

    2015-01-01

    The gynecologic oncology patients surveillance network program was conducted with the collaboration of 5 provincial hospitals located in the north of Thailand (Chiang Rai, Lamphun Nan, Phayao and Phrae). The aim was to identify ways of reducing the burden and the cost to the gynecologic cancer patients who needed to travel to the tertiary care hospital for follow up. The clinical data of each patient was transferred to the provincial hospital by the internet via the website www.gogcmu.or.th. All the general gynecologists who participated in this project attended the training course set up for the program. From January 2011 to February 2014, 854 patients who were willing to have their next follow-up at the network hospitals close to their home were enrolled this project. Almost of them were residents in Chiang Rai province and the most common disease was cervical cancer. After the project had been running for 1 year, 604 of the enrolled patients and 21 health-care personnel who had participated in this project were interviewed to assess its success. Some 85.3% of the patients and 100% of the health-care personnel were satisfied with this project. However, 60 patients had withdrawn, the most common reason being the lack of confidence in the follow up at the local provincial hospital. In conclusion, it is possible to initiate a gynecologic oncology patients' surveillance network program and the initiation could reduce the problems associated with and the cost the patients incurred as they journeyed to the tertiary care hospital. PMID:26163612

  2. Pathway and Network Analysis in Proteomics

    PubMed Central

    Wu, Xiaogang; Hasan, Mohammad Al; Chen, Jake Yue

    2014-01-01

    Proteomics is inherently a systems science that studies not only measured protein and their expressions in a cell, but also the interplay of proteins, protein complexes, signaling pathways, and network modules. There is a rapid accumulation of Proteomics data in recent years. However, Proteomics data are highly variable, with results being sensitive to data preparation methods, sample condition, instrument types, and analytical method. To address this challenge in Proteomics data analysis, we review common approaches developed to incorporate biological function and network topological information. We categorize existing tools into four categories: tools with basic functional information and little topological features (e.g., GO category analysis), tools with rich functional information and little topological features (e.g., GSEA), tools with basic functional information and rich topological features (e.g., Cytoscape), and tools with rich functional information and rich topological features (e.g., PathwayExpress). We review the general application potential of these tools to Proteomics. In addition, we also review tools that can achieve automated learning of pathway modules and features, and tools that help perform integrated network visual analytics. PMID:24911777

  3. Image analysis for measuring rod network properties

    NASA Astrophysics Data System (ADS)

    Kim, Dongjae; Choi, Jungkyu; Nam, Jaewook

    2015-12-01

    In recent years, metallic nanowires have been attracting significant attention as next-generation flexible transparent conductive films. The performance of films depends on the network structure created by nanowires. Gaining an understanding of their structure, such as connectivity, coverage, and alignment of nanowires, requires the knowledge of individual nanowires inside the microscopic images taken from the film. Although nanowires are flexible up to a certain extent, they are usually depicted as rigid rods in many analysis and computational studies. Herein, we propose a simple and straightforward algorithm based on the filtering in the frequency domain for detecting the rod-shape objects inside binary images. The proposed algorithm uses a specially designed filter in the frequency domain to detect image segments, namely, the connected components aligned in a certain direction. Those components are post-processed to be combined under a given merging rule in a single rod object. In this study, the microscopic properties of the rod networks relevant to the analysis of nanowire networks were measured for investigating the opto-electric performance of transparent conductive films and their alignment distribution, length distribution, and area fraction. To verify and find the optimum parameters for the proposed algorithm, numerical experiments were performed on synthetic images with predefined properties. By selecting proper parameters, the algorithm was used to investigate silver nanowire transparent conductive films fabricated by the dip coating method.

  4. Design Criteria For Networked Image Analysis System

    NASA Astrophysics Data System (ADS)

    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.

  5. Network-based modular latent structure analysis

    PubMed Central

    2014-01-01

    Background High-throughput expression data, such as gene expression and metabolomics data, exhibit modular structures. Groups of features in each module follow a latent factor model, while between modules, the latent factors are quasi-independent. Recovering the latent factors can shed light on the hidden regulation patterns of the expression. The difficulty in detecting such modules and recovering the latent factors lies in the high dimensionality of the data, and the lack of knowledge in module membership. Methods Here we describe a method based on community detection in the co-expression network. It consists of inference-based network construction, module detection, and interacting latent factor detection from modules. Results In simulations, the method outperformed projection-based modular latent factor discovery when the input signals were not Gaussian. We also demonstrate the method's value in real data analysis. Conclusions The new method nMLSA (network-based modular latent structure analysis) is effective in detecting latent structures, and is easy to extend to non-linear cases. The method is available as R code at http://web1.sph.emory.edu/users/tyu8/nMLSA/. PMID:25435002

  6. Pathway and network analysis in proteomics.

    PubMed

    Wu, Xiaogang; Hasan, Mohammad Al; Chen, Jake Yue

    2014-12-01

    Proteomics is inherently a systems science that studies not only measured protein and their expressions in a cell, but also the interplay of proteins, protein complexes, signaling pathways, and network modules. There is a rapid accumulation of Proteomics data in recent years. However, Proteomics data are highly variable, with results sensitive to data preparation methods, sample condition, instrument types, and analytical methods. To address the challenge in Proteomics data analysis, we review current tools being developed to incorporate biological function and network topological information. We categorize these tools into four types: tools with basic functional information and little topological features (e.g., GO category analysis), tools with rich functional information and little topological features (e.g., GSEA), tools with basic functional information and rich topological features (e.g., Cytoscape), and tools with rich functional information and rich topological features (e.g., PathwayExpress). We first review the potential application of these tools to Proteomics; then we review tools that can achieve automated learning of pathway modules and features, and tools that help perform integrated network visual analytics. PMID:24911777

  7. Utility green pricing programs: A statistical analysis of program effectiveness

    SciTech Connect

    Wiser, Ryan; Olson, Scott; Bird, Lori; Swezey, Blair

    2004-02-01

    Development of renewable energy. Such programs have grown in number in recent years. The design features and effectiveness of these programs varies considerably, however, leading a variety of stakeholders to suggest specific marketing and program design features that might improve customer response and renewable energy sales. This report analyzes actual utility green pricing program data to provide further insight into which program features might help maximize both customer participation in green pricing programs and the amount of renewable energy purchased by customers in those programs. Statistical analysis is performed on both the residential and non-residential customer segments. Data comes from information gathered through a questionnaire completed for 66 utility green pricing programs in early 2003. The questionnaire specifically gathered data on residential and non-residential participation, amount of renewable energy sold, program length, the type of renewable supply used, program price/cost premiums, types of consumer research and program evaluation performed, different sign-up options available, program marketing efforts, and ancillary benefits offered to participants.

  8. Application of a neural network to simulate analysis in an optimization process

    NASA Technical Reports Server (NTRS)

    Rogers, James L.; Lamarsh, William J., II

    1992-01-01

    A new experimental software package called NETS/PROSSS aimed at reducing the computing time required to solve a complex design problem is described. The software combines a neural network for simulating the analysis program with an optimization program. The neural network is applied to approximate results of a finite element analysis program to quickly obtain a near-optimal solution. Results of the NETS/PROSSS optimization process can also be used as an initial design in a normal optimization process and make it possible to converge to an optimum solution with significantly fewer iterations.

  9. Network-analysis-guided synthesis of weisaconitine D and liljestrandinine

    NASA Astrophysics Data System (ADS)

    Marth, C. J.; Gallego, G. M.; Lee, J. C.; Lebold, T. P.; Kulyk, S.; Kou, K. G. M.; Qin, J.; Lilien, R.; Sarpong, R.

    2015-12-01

    General strategies for the chemical synthesis of organic compounds, especially of architecturally complex natural products, are not easily identified. Here we present a method to establish a strategy for such syntheses, which uses network analysis. This approach has led to the identification of a versatile synthetic intermediate that facilitated syntheses of the diterpenoid alkaloids weisaconitine D and liljestrandinine, and the core of gomandonine. We also developed a web-based graphing program that allows network analysis to be easily performed on molecules with complex frameworks. The diterpenoid alkaloids comprise some of the most architecturally complex and functional-group-dense secondary metabolites isolated. Consequently, they present a substantial challenge for chemical synthesis. The synthesis approach described here is a notable departure from other single-target-focused strategies adopted for the syntheses of related structures. Specifically, it affords not only the targeted natural products, but also intermediates and derivatives in the three subfamilies of diterpenoid alkaloids (C-18, C-19 and C-20), and so provides a unified synthetic strategy for these natural products. This work validates the utility of network analysis as a starting point for identifying strategies for the syntheses of architecturally complex secondary metabolites.

  10. Network-analysis-guided synthesis of weisaconitine D and liljestrandinine.

    PubMed

    Marth, C J; Gallego, G M; Lee, J C; Lebold, T P; Kulyk, S; Kou, K G M; Qin, J; Lilien, R; Sarpong, R

    2015-12-24

    General strategies for the chemical synthesis of organic compounds, especially of architecturally complex natural products, are not easily identified. Here we present a method to establish a strategy for such syntheses, which uses network analysis. This approach has led to the identification of a versatile synthetic intermediate that facilitated syntheses of the diterpenoid alkaloids weisaconitine D and liljestrandinine, and the core of gomandonine. We also developed a web-based graphing program that allows network analysis to be easily performed on molecules with complex frameworks. The diterpenoid alkaloids comprise some of the most architecturally complex and functional-group-dense secondary metabolites isolated. Consequently, they present a substantial challenge for chemical synthesis. The synthesis approach described here is a notable departure from other single-target-focused strategies adopted for the syntheses of related structures. Specifically, it affords not only the targeted natural products, but also intermediates and derivatives in the three families of diterpenoid alkaloids (C-18, C-19 and C-20), and so provides a unified synthetic strategy for these natural products. This work validates the utility of network analysis as a starting point for identifying strategies for the syntheses of architecturally complex secondary metabolites. PMID:26675722

  11. A Korean Space Situational Awareness Program : OWL Network

    NASA Astrophysics Data System (ADS)

    Park, J.; Choi, Y.; Jo, J.; Moon, H.; Im, H.; Park, J.

    2012-09-01

    We are going to present a brief introduction to the OWL (Optical Wide-field patroL) network, one of Korean space situational awareness facilities. Primary objectives of the OWL network are 1) to obtain orbital information of Korean domestic LEOs using optical method, 2) to monitor GEO-belt over territory of Korea, and 3) to alleviate collisional risks posed to Korean satellites from space debris. For these purposes, we are planning to build a global network of telescopes which consists of five small wide-field telescopes and one 2m class telescope. The network of small telescopes will be dedicated mainly to the observation of domestic LEOs, but many slots will be open to other scientific programs such as GRB follow-up observations. Main targets of 2m telescope not only include artificial objects such as GEO debris and LEO debris with low inclination and high eccentricity, but also natural objects such as near Earth asteroids. We expect to monitor space objects down to 10cm in size in GEO using the 2m telescope system. Main research topics include size distribution and evolution of space debris. We also expect to utilize this facility for physical characterization and population study of near Earth asteroids. The aperture size of the small telescope system is 0.5m with Rechey-Cretian configuration and its field of view is 1.75 deg x 1.75 deg. It is equipped with 4K CCD with 9um pixel size, and its plate scale is 1.3 arcsec/pixel. A chopper wheel is employed to maximize astrometric solutions in a single CCD frame, and a de-rotator is used to compensate field rotation of the alt-az type mount. We have designed a compact end unit in which three rotating parts (chopper wheel, filter wheel, de-rotator) and a CCD camera are integrated, and dedicated telescope/site control boards for the OWL network. The design of 2m class telescope is still under discussion yet is expected to be fixed in the first half of 2013 at the latest. The OWL network will be operated in a fully

  12. DYNAVAC: a transient-vacuum-network analysis code

    SciTech Connect

    Deis, G.A.

    1980-07-08

    This report discusses the structure and use of the program DYNAVAC, a new transient-vacuum-network analysis code implemented on the NMFECC CDC-7600 computer. DYNAVAC solves for the transient pressures in a network of up to twenty lumped volumes, interconnected in any configuration by specified conductances. Each volume can have an internal gas source, a pumping speed, and any initial pressure. The gas-source rates can vary with time in any piecewise-linear manner, and up to twenty different time variations can be included in a single problem. In addition, the pumping speed in each volume can vary with the total gas pumped in the volume, thus simulating the saturation of surface pumping. This report is intended to be both a general description and a user's manual for DYNAVAC.

  13. Exploiting parallel computing with limited program changes using a network of microcomputers

    NASA Technical Reports Server (NTRS)

    Rogers, J. L., Jr.; Sobieszczanski-Sobieski, J.

    1985-01-01

    Network computing and multiprocessor computers are two discernible trends in parallel processing. The computational behavior of an iterative distributed process in which some subtasks are completed later than others because of an imbalance in computational requirements is of significant interest. The effects of asynchronus processing was studied. A small existing program was converted to perform finite element analysis by distributing substructure analysis over a network of four Apple IIe microcomputers connected to a shared disk, simulating a parallel computer. The substructure analysis uses an iterative, fully stressed, structural resizing procedure. A framework of beams divided into three substructures is used as the finite element model. The effects of asynchronous processing on the convergence of the design variables are determined by not resizing particular substructures on various iterations.

  14. 77 FR 35711 - Strong Cities, Strong Communities National Resource Network Pilot Program Advance Notice and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-14

    ... URBAN DEVELOPMENT Strong Cities, Strong Communities National Resource Network Pilot Program Advance..., Strong Communities National Resource Network pilot program with its 19 federal agency and subagency... Resource Network, HUD and its partners will offer a central portal to connect America's most...

  15. 78 FR 57845 - Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program Environmental...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-20

    ... of the Secretary Notice of Availability (NOA) for Strategic Network Optimization (SNO) Program... Strategic Network Optimization (SNO) Program Environmental Assessment. SUMMARY: The Defense Logistics Agency... distribution network for the Department of Defense (DoD). The EA has been prepared as required under...

  16. The USA-National Phenology Network Biophysical Program

    NASA Astrophysics Data System (ADS)

    Losleben, M. V.; Crimmins, T. M.; Weltzin, J. F.

    2009-12-01

    On January 1, 2009, the USA National Phenology Network (USA-NPN, www.usanpn.org) launched the USA-NPN Biophysical Program. The overarching goal of the Biophysical Program (BP) is to link phenology, the study of recurring plant and animal life cycle stages, with climate through the integration of phenology observations, meteorological, and spectral remote sensing measurements at sites across a broad a spectrum of environments. Phenology is critical for understanding a changing world. Many of the recurring plant and animal life cycle stages such as leafing and flowering of plants, maturation of agricultural crops, emergence of insects, and migration of birds are sensitive to climatic variation and change, and are simple to observe and record. Such changes can effect, for example, timing mismatches between the emergence of food sources and the arrival of migrating populations, or create new disease and invasive species vectors via increasingly suitable growing seasons relative to the climatic life cycle requirements of hosts or the organisms themselves. New vectors or crashing populations can have major repercussions on entire ecosystems and regional economics. Thus, to track phenology and build a national database, the USA-NPN is providing standard phenology monitoring protocols. Further, the integration of weather stations with phenological data provides an opportunity to understand how a changing climate is altering phenology. Thus, the USA-NPN Biophysical Program is developing an integrative biology-climate site template for widespread dissemination, in collaboration with the Rocky Mountain Biological Laboratory (RMBL, http://rmbl.org/rockymountainbiolab/). This poster presents the USA-NPN Biophysical Program, and the results of the collaboration with RMBL during the summer of 2009, including the installation of an elevational network of climate stations. The National Science Foundation’s Major Research Instrumentation (NSF’s MRI) program provides funding

  17. Reverse engineering GTPase programming languages with reconstituted signaling networks.

    PubMed

    Coyle, Scott M

    2016-07-01

    The Ras superfamily GTPases represent one of the most prolific signaling currencies used in Eukaryotes. With these remarkable molecules, evolution has built GTPase networks that control diverse cellular processes such as growth, morphology, motility and trafficking. (1-4) Our knowledge of the individual players that underlie the function of these networks is deep; decades of biochemical and structural data has provided a mechanistic understanding of the molecules that turn GTPases ON and OFF, as well as how those GTPase states signal by controlling the assembly of downstream effectors. However, we know less about how these different activities work together as a system to specify complex dynamic signaling outcomes. Decoding this molecular "programming language" would help us understand how different species and cell types have used the same GTPase machinery in different ways to accomplish different tasks, and would also provide new insights as to how mutations to these networks can cause disease. We recently developed a bead-based microscopy assay to watch reconstituted H-Ras signaling systems at work under arbitrary configurations of regulators and effectors. (5) Here we highlight key observations and insights from this study and propose extensions to our method to further study this and other GTPase signaling systems. PMID:27128855

  18. Network enrichment analysis: extension of gene-set enrichment analysis to gene networks

    PubMed Central

    2012-01-01

    Background Gene-set enrichment analyses (GEA or GSEA) are commonly used for biological characterization of an experimental gene-set. This is done by finding known functional categories, such as pathways or Gene Ontology terms, that are over-represented in the experimental set; the assessment is based on an overlap statistic. Rich biological information in terms of gene interaction network is now widely available, but this topological information is not used by GEA, so there is a need for methods that exploit this type of information in high-throughput data analysis. Results We developed a method of network enrichment analysis (NEA) that extends the overlap statistic in GEA to network links between genes in the experimental set and those in the functional categories. For the crucial step in statistical inference, we developed a fast network randomization algorithm in order to obtain the distribution of any network statistic under the null hypothesis of no association between an experimental gene-set and a functional category. We illustrate the NEA method using gene and protein expression data from a lung cancer study. Conclusions The results indicate that the NEA method is more powerful than the traditional GEA, primarily because the relationships between gene sets were more strongly captured by network connectivity rather than by simple overlaps. PMID:22966941

  19. The Algerian Seismic Network: Performance from data quality analysis

    NASA Astrophysics Data System (ADS)

    Yelles, Abdelkarim; Allili, Toufik; Alili, Azouaou

    2013-04-01

    Seismic monitoring in Algeria has seen a great change after the Boumerdes earthquake of May 21st, 2003. Indeed the installation of a New Digital seismic network (ADSN) upgrade drastically the previous analog telemetry network. During the last four years, the number of stations in operation has greatly increased to 66 stations with 15 Broad Band, 02 Very Broad band, 47 Short period and 21 accelerometers connected in real time using various mode of transmission ( VSAT, ADSL, GSM, ...) and managed by Antelope software. The spatial distribution of these stations covers most of northern Algeria from east to west. Since the operation of the network, significant number of local, regional and tele-seismic events was located by the automatic processing, revised and archived in databases. This new set of data is characterized by the accuracy of the automatic location of local seismicity and the ability to determine its focal mechanisms. Periodically, data recorded including earthquakes, calibration pulse and cultural noise are checked using PSD (Power Spectral Density) analysis to determine the noise level. ADSN Broadband stations data quality is controlled in quasi real time using the "PQLX" software by computing PDFs and PSDs of the recordings. Some other tools and programs allow the monitoring and the maintenance of the entire electronic system for example to check the power state of the system, the mass position of the sensors and the environment conditions (Temperature, Humidity, Air Pressure) inside the vaults. The new design of the network allows management of many aspects of real time seismology: seismic monitoring, rapid determination of earthquake, message alert, moment tensor estimation, seismic source determination, shakemaps calculation, etc. The international standards permit to contribute in regional seismic monitoring and the Mediterranean warning system. The next two years with the acquisition of new seismic equipment to reach 50 new BB stations led to

  20. Technical and analytical support to the ARPA Artificial Neural Network Technology Program

    SciTech Connect

    1995-09-16

    Strategic Analysis (SA) has provided ongoing work for the Advanced Research Projects Agency (ARPA) Artificial Neural Network (ANN) technology program. This effort provides technical and analytical support to the ARPA ANN technology program in support of the following information areas of interest: (1) Alternative approaches for application of ANN technology, hardware approaches that utilize the inherent massive parallelism of ANN technology, and novel ANN theory and modeling analyses. (2) Promising military applications for ANN technology. (3) Measures to use in judging success of ANN technology research and development. (4) Alternative strategies for ARPA involvement in ANN technology R&D. These objectives were accomplished through the development of novel information management tools, strong SA knowledge base, and effective communication with contractors, agents, and other program participants. These goals have been realized. Through enhanced tracking and coordination of research, the ANN program is healthy and recharged for future technological breakthroughs.

  1. Robustness analysis of biochemical network models.

    PubMed

    Kim, J; Bates, D G; Postlethwaite, I; Ma, L; Iglesias, P A

    2006-05-01

    Biological systems that have been experimentally verified to be robust to significant changes in their environments require mathematical models that are themselves robust. In this context, a necessary condition for model robustness is that the model dynamics should not be sensitive to small variations in the model's parameters. Robustness analysis problems of this type have been extensively studied in the field of robust control theory and have been found to be very difficult to solve in general. The authors describe how some tools from robust control theory and nonlinear optimisation can be used to analyse the robustness of a recently proposed model of the molecular network underlying adenosine 3',5'-cyclic monophosphate (cAMP) oscillations observed in fields of chemotactic Dictyostelium cells. The network model, which consists of a system of seven coupled nonlinear differential equations, accurately reproduces the spontaneous oscillations in cAMP observed during the early development of D. discoideum. The analysis by the authors reveals, however, that very small variations in the model parameters can effectively destroy the required oscillatory dynamics. A biological interpretation of the analysis results is that correct functioning of a particular positive feedback loop in the proposed model is crucial to maintaining the required oscillatory dynamics. PMID:16984084

  2. [Basic concepts for network meta-analysis].

    PubMed

    Catalá-López, Ferrán; Tobías, Aurelio; Roqué, Marta

    2014-12-01

    Systematic reviews and meta-analyses have long been fundamental tools for evidence-based clinical practice. Initially, meta-analyses were proposed as a technique that could improve the accuracy and the statistical power of previous research from individual studies with small sample size. However, one of its main limitations has been the fact of being able to compare no more than two treatments in an analysis, even when the clinical research question necessitates that we compare multiple interventions. Network meta-analysis (NMA) uses novel statistical methods that incorporate information from both direct and indirect treatment comparisons in a network of studies examining the effects of various competing treatments, estimating comparisons between many treatments in a single analysis. Despite its potential limitations, NMA applications in clinical epidemiology can be of great value in situations where there are several treatments that have been compared against a common comparator. Also, NMA can be relevant to a research or clinical question when many treatments must be considered or when there is a mix of both direct and indirect information in the body of evidence. PMID:24796656

  3. Lists2Networks: Integrated analysis of gene/protein lists

    PubMed Central

    2010-01-01

    Background Systems biologists are faced with the difficultly of analyzing results from large-scale studies that profile the activity of many genes, RNAs and proteins, applied in different experiments, under different conditions, and reported in different publications. To address this challenge it is desirable to compare the results from different related studies such as mRNA expression microarrays, genome-wide ChIP-X, RNAi screens, proteomics and phosphoproteomics experiments in a coherent global framework. In addition, linking high-content multilayered experimental results with prior biological knowledge can be useful for identifying functional themes and form novel hypotheses. Results We present Lists2Networks, a web-based system that allows users to upload lists of mammalian genes/proteins onto a server-based program for integrated analysis. The system includes web-based tools to manipulate lists with different set operations, to expand lists using existing mammalian networks of protein-protein interactions, co-expression correlation, or background knowledge co-annotation correlation, as well as to apply gene-list enrichment analyses against many gene-list libraries of prior biological knowledge such as pathways, gene ontology terms, kinase-substrate, microRNA-mRAN, and protein-protein interactions, metabolites, and protein domains. Such analyses can be applied to several lists at once against many prior knowledge libraries of gene-lists associated with specific annotations. The system also contains features that allow users to export networks and share lists with other users of the system. Conclusions Lists2Networks is a user friendly web-based software system expected to significantly ease the computational analysis process for experimental systems biologists employing high-throughput experiments at multiple layers of regulation. The system is freely available at http://www.lists2networks.org. PMID:20152038

  4. Analysis of complex systems using neural networks

    SciTech Connect

    Uhrig, R.E. . Dept. of Nuclear Engineering Oak Ridge National Lab., TN )

    1992-01-01

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems.

  5. Analysis of complex systems using neural networks

    SciTech Connect

    Uhrig, R.E. |

    1992-12-31

    The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems.

  6. Artificial neural networks and Abelian harmonic analysis

    NASA Astrophysics Data System (ADS)

    Rodriguez, Domingo; Pertuz-Campo, Jairo

    1991-12-01

    This work deals with the use of artificial neural networks (ANN) for the digital processing of finite discrete time signals. The effort concentrates on the efficient replacement of fast Fourier transform (FFT) algorithms with ANN algorithms in certain engineering and scientific applications. The FFT algorithms are efficient methods of computing the discrete Fourier transform (DFT). The ubiquitous DFT is utilized in almost every digital signal processing application where harmonic analysis information is needed. Applications abound in areas such as audio acoustics, geophysics, biomedicine, telecommunications, astrophysics, etc. To identify more efficient methods to obtain a desired spectral information will result in a reduction in the computational effort required to implement these applications.

  7. A national streamflow network gap analysis

    USGS Publications Warehouse

    Kiang, Julie E.; Stewart, David W.; Archfield, Stacey A.; Osborne, Emily B.; Eng, Ken

    2013-01-01

    The U.S. Geological Survey (USGS) conducted a gap analysis to evaluate how well the USGS streamgage network meets a variety of needs, focusing on the ability to calculate various statistics at locations that have streamgages (gaged) and that do not have streamgages (ungaged). This report presents the results of analysis to determine where there are gaps in the network of gaged locations, how accurately desired statistics can be calculated with a given length of record, and whether the current network allows for estimation of these statistics at ungaged locations. The analysis indicated that there is variability across the Nation’s streamflow data-collection network in terms of the spatial and temporal coverage of streamgages. In general, the Eastern United States has better coverage than the Western United States. The arid Southwestern United States, Alaska, and Hawaii were observed to have the poorest spatial coverage, using the dataset assembled for this study. Except in Hawaii, these areas also tended to have short streamflow records. Differences in hydrology lead to differences in the uncertainty of statistics calculated in different regions of the country. Arid and semiarid areas of the Central and Southwestern United States generally exhibited the highest levels of interannual variability in flow, leading to larger uncertainty in flow statistics. At ungaged locations, information can be transferred from nearby streamgages if there is sufficient similarity between the gaged watersheds and the ungaged watersheds of interest. Areas where streamgages exhibit high correlation are most likely to be suitable for this type of information transfer. The areas with the most highly correlated streamgages appear to coincide with mountainous areas of the United States. Lower correlations are found in the Central United States and coastal areas of the Southeastern United States. Information transfer from gaged basins to ungaged basins is also most likely to be successful

  8. FORTRAN computer program for seismic risk analysis

    USGS Publications Warehouse

    McGuire, Robin K.

    1976-01-01

    A program for seismic risk analysis is described which combines generality of application, efficiency and accuracy of operation, and the advantage of small storage requirements. The theoretical basis for the program is first reviewed, and the computational algorithms used to apply this theory are described. The information required for running the program is listed. Published attenuation functions describing the variation with earthquake magnitude and distance of expected values for various ground motion parameters are summarized for reference by the program user. Finally, suggestions for use of the program are made, an example problem is described (along with example problem input and output) and the program is listed.

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

    ERIC Educational Resources Information Center

    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,…

  10. Social network analysis and agent-based modeling in social epidemiology

    PubMed Central

    2012-01-01

    The past five years have seen a growth in the interest in systems approaches in epidemiologic research. These approaches may be particularly appropriate for social epidemiology. Social network analysis and agent-based models (ABMs) are two approaches that have been used in the epidemiologic literature. Social network analysis involves the characterization of social networks to yield inference about how network structures may influence risk exposures among those in the network. ABMs can promote population-level inference from explicitly programmed, micro-level rules in simulated populations over time and space. In this paper, we discuss the implementation of these models in social epidemiologic research, highlighting the strengths and weaknesses of each approach. Network analysis may be ideal for understanding social contagion, as well as the influences of social interaction on population health. However, network analysis requires network data, which may sacrifice generalizability, and causal inference from current network analytic methods is limited. ABMs are uniquely suited for the assessment of health determinants at multiple levels of influence that may couple with social interaction to produce population health. ABMs allow for the exploration of feedback and reciprocity between exposures and outcomes in the etiology of complex diseases. They may also provide the opportunity for counterfactual simulation. However, appropriate implementation of ABMs requires a balance between mechanistic rigor and model parsimony, and the precision of output from complex models is limited. Social network and agent-based approaches are promising in social epidemiology, but continued development of each approach is needed. PMID:22296660

  11. 75 FR 55360 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-10

    ... Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010 Strategic Plan AGENCY: The National Coordination Office (NCO) for Networking and Information Technology Research... and Information Technology Research and Development (NITRD) requests comments from the...

  12. 76 FR 12983 - Notice of Proposed Information Collection: Comment Request; Tenant Resource Network Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-09

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT Notice of Proposed Information Collection: Comment Request; Tenant Resource Network... information: Title of Proposal: Tenant Resource Network Program. OMB Control Number, if applicable:...

  13. 76 FR 39417 - Notice of Submission of Proposed Information Collection to OMB Tenant Resource Network Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-06

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF HOUSING AND URBAN DEVELOPMENT Notice of Submission of Proposed Information Collection to OMB Tenant Resource Network... following information: Title of Proposal: Tenant Resource Network Program. OMB Approval Number:...

  14. Network integration and graph analysis in mammalian molecular systems biology

    PubMed Central

    Ma'ayan, A.

    2009-01-01

    Abstraction of intracellular biomolecular interactions into networks is useful for data integration and graph analysis. Network analysis tools facilitate predictions of novel functions for proteins, prediction of functional interactions and identification of intracellular modules. These efforts are linked with drug and phenotype data to accelerate drug-target and biomarker discovery. This review highlights the currently available varieties of mammalian biomolecular networks, and surveys methods and tools to construct, compare, integrate, visualise and analyse such networks. PMID:19045817

  15. A General Questionnaire Analysis Program

    ERIC Educational Resources Information Center

    Aiken, Lewis R.

    1978-01-01

    A general FORTRAN computer program for analyzing categorical or frequency data obtained from questionnaires is described. A variety of descriptive statistics, chi square, Kendall's tau and Cramer's statistic are provided. (Author/JKS)

  16. Artificial Satellite Analysis Program (ASAP)

    NASA Technical Reports Server (NTRS)

    Kwok, Johnny H.

    1990-01-01

    Program suited for studying planetary orbit missions including mapping and flyby components. Sample data included for geosynchronous station drift cycle study. Venus radar mapping strategy, frozen orbit about Mars, and repeat ground trace orbit. Written in FORTRAN.

  17. A Matlab Program for Textural Classification Using Neural Networks

    NASA Astrophysics Data System (ADS)

    Leite, E. P.; de Souza, C.

    2008-12-01

    A new MATLAB code that provides tools to perform classification of textural images for applications in the Geosciences is presented. The program, here coined TEXTNN, comprises the computation of variogram maps in the frequency domain for specific lag distances in the neighborhood of a pixel. The result is then converted back to spatial domain, where directional or ominidirectional semivariograms are extracted. Feature vectors are built with textural information composed of the semivariance values at these lag distances and, moreover, with histogram measures of mean, standard deviation and weighted fill-ratio. This procedure is applied to a selected group of pixels or to all pixels in an image using a moving window. A feed- forward back-propagation Neural Network can then be designed and trained on feature vectors of predefined classes (training set). The training phase minimizes the mean-squared error on the training set. Additionally, at each iteration, the mean-squared error for every validation is assessed and a test set is evaluated. The program also calculates contingency matrices, global accuracy and kappa coefficient for the three data sets, allowing a quantitative appraisal of the predictive power of the Neural Network models. The interpreter is able to select the best model obtained from a k-fold cross-validation or to use a unique split-sample data set for classification of all pixels in a given textural image. The code is opened to the geoscientific community and is very flexible, allowing the experienced user to modify it as necessary. The performance of the algorithms and the end-user program were tested using synthetic images, orbital SAR (RADARSAT) imagery for oil seepage detection, and airborne, multi-polarimetric SAR imagery for geologic mapping. The overall results proved very promising.

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

    PubMed

    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. PMID:24644162

  19. Network TV Programming: Economics, Audiences, and the Ratings Game, 1971-1986.

    ERIC Educational Resources Information Center

    Atkin, David; Litman, Barry

    1986-01-01

    Presents a model to ascertain the "critical mass" in ratings points required to facilitate renewal of prime-time network programs aired between 1971 and 1985. Emphasizes a financial model incorporating revenue levels needed to offset program costs--advertising agency commissions, affiliate compensation, network overhead--and program production and…

  20. Gap analysis of the European Earth Observation Networks

    NASA Astrophysics Data System (ADS)

    Closa, Guillem; Serral, Ivette; Maso, Joan

    2016-04-01

    Earth Observations (EO) are fundamental to enhance the scientific understanding of the current status of the Earth. Nowadays, there are a lot of EO services that provide large volume of data, and the number of datasets available for different geosciences areas is increasing by the day. Despite this coverage, a glance of the European EO networks reveals that there are still some issues that are not being met; some gaps in specific themes or some thematic overlaps between different networks. This situation requires a clarification process of the actual status of the EO European networks in order to set priorities and propose future actions that will improve the European EO networks. The aim of this work is to detect the existing gaps and overlapping problems among the European EO networks. The analytical process has been done by studying the availability and the completeness of the Essential Variables (EV) data captured by the European EO networks. The concept of EVs considers that there are a number of parameters that are essential to characterize the state and trends of a system without losing significant information. This work generated a database of the existing gaps in the European EO network based on the initial GAIA-CLIM project data structure. For each theme the missing or incomplete data about each EV was indentified. Then, if incomplete, the gap was described by adding its type (geographical extent, vertical extent, temporal extent, spatial resolution, etc), the cost, the remedy, the feasibility, the impact and the priority, among others. Gaps in EO are identified following the ConnectinGEO methodology structured in 5 threads; identification of observation requirements, incorporation of international research programs material, consultation process within the current EO actors, GEOSS Discovery and Access Broker analysis, and industry-driven challenges implementation. Concretely, the presented work focuses on the second thread, which is based on

  1. Multistage neural network model for dynamic scene analysis

    SciTech Connect

    Ajjimarangsee, P.

    1989-01-01

    This research is concerned with dynamic scene analysis. The goal of scene analysis is to recognize objects and have a meaningful interpretation of the scene from which images are obtained. The task of the dynamic scene analysis process generally consists of region identification, motion analysis and object recognition. The objective of this research is to develop clustering algorithms using neural network approach and to investigate a multi-stage neural network model for region identification and motion analysis. The research is separated into three parts. First, a clustering algorithm using Kohonens' self-organizing feature map network is developed to be capable of generating continuous membership valued outputs. A newly developed version of the updating algorithm of the network is introduced to achieve a high degree of parallelism. A neural network model for the fuzzy c-means algorithm is proposed. In the second part, the parallel algorithms of a neural network model for clustering using the self-organizing feature maps approach and a neural network that models the fuzzy c-means algorithm are modified for implementation on a distributed memory parallel architecture. In the third part, supervised and unsupervised neural network models for motion analysis are investigated. For a supervised neural network, a three layer perceptron network is trained by a series of images to recognize the movement of the objects. For the unsupervised neural network, a self-organizing feature mapping network will learn to recognize the movement of the objects without an explicit training phase.

  2. A systems approach to the biology of mood disorders through network analysis of candidate genes.

    PubMed

    Detera-Wadleigh, S D; Akula, N

    2011-05-01

    Meta analysis of association data of mood disorders has shown evidence for the role of particular genes in genetic risk. Integration of association data from meta analysis with differential expression data in brains of mood disorder patients could heighten the level of support for specific genes. To identify molecular mechanisms that may be disrupted in disease, a systems approach that involves analysis of biological networks created by these selected genes was employed.Interaction networks of hierarchical groupings of selected genes were generated using the Michigan Molecular Interactions (MiMI) software. Large networks were deconvoluted into subclusters of core complexes by using a community clustering program, GLay. Network nodes were functionally annotated in DAVID Bioinformatics Resource to identify enriched pathways and functional clusters. MAPK and beta adrenergic receptor signaling pathways were significantly enriched in the ANK3 and CACNA1C network. The PBRM1 network bolstered the enrichment of chromatin remodeling and transcription regulation functional clusters. Lowering the stringency for inclusion of other genes in network seeds increased network complexity and expanded the recruitment of enriched pathways to include signaling by neurotransmitter and hormone receptors, neurotrophin, ErbB and the cell cycle. We present a strategy to interrogate mechanisms in the cellular system that might be perturbed in disease. Network analysis of meta analysis- generated candidate genes that exhibited differential expression in mood disorder brains identified signaling pathways and functional clusters that may be involved in genetic risk for mood disorders. PMID:21547870

  3. Using Social Network Analysis for Spam Detection

    NASA Astrophysics Data System (ADS)

    Debarr, Dave; Wechsler, Harry

    Content filtering is a popular approach to spam detection. It focuses on analysis of the message content to identify spam. In this paper, we evaluate the use of social network analysis measures to improve the performance of a content filtering model. By measuring the degree centrality of message transfer agents, we observed performance improvements for spam detection in repeated experiments; e.g. a 70% increase in the proportion of spam detected with a false positive rate of 0.1%. We were also able to use anomaly detection to identify mislabeled messages in a publicly available spam data set. Messages claiming unusually long paths between the sender's message transfer agent and the recipient's message transfer agent turned out to be spam.

  4. Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

    ERIC Educational Resources Information Center

    Grunspan, Daniel Z.; Wiggins, Benjamin L.; Goodreau, Steven M.

    2014-01-01

    Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA)…

  5. Static Analysis of C Programs

    NASA Technical Reports Server (NTRS)

    Venet, Arnaud; Brat, Guillaume

    2003-01-01

    Contents include the following: Motivation. Cost of losing missions. Introduction to Static Analysis:definition, defect classes, applicability issues, specialization, analysis of MPF. C Global Surveyor (CGS): fact sheet, CGS phases, example. Conclusions.

  6. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

    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

  7. Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research

    PubMed Central

    Wiggins, Benjamin L.; Goodreau, Steven M.

    2014-01-01

    Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. PMID:26086650

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Vehicle dynamic analysis using neuronal network algorithms

    NASA Astrophysics Data System (ADS)

    Oloeriu, Florin; Mocian, Oana

    2014-06-01

    Theoretical developments of certain engineering areas, the emergence of new investigation tools, which are better and more precise and their implementation on-board the everyday vehicles, all these represent main influence factors that impact the theoretical and experimental study of vehicle's dynamic behavior. Once the implementation of these new technologies onto the vehicle's construction had been achieved, it had led to more and more complex systems. Some of the most important, such as the electronic control of engine, transmission, suspension, steering, braking and traction had a positive impact onto the vehicle's dynamic behavior. The existence of CPU on-board vehicles allows data acquisition and storage and it leads to a more accurate and better experimental and theoretical study of vehicle dynamics. It uses the information offered directly by the already on-board built-in elements of electronic control systems. The technical literature that studies vehicle dynamics is entirely focused onto parametric analysis. This kind of approach adopts two simplifying assumptions. Functional parameters obey certain distribution laws, which are known in classical statistics theory. The second assumption states that the mathematical models are previously known and have coefficients that are not time-dependent. Both the mentioned assumptions are not confirmed in real situations: the functional parameters do not follow any known statistical repartition laws and the mathematical laws aren't previously known and contain families of parameters and are mostly time-dependent. The purpose of the paper is to present a more accurate analysis methodology that can be applied when studying vehicle's dynamic behavior. A method that provides the setting of non-parametrical mathematical models for vehicle's dynamic behavior is relying on neuronal networks. This method contains coefficients that are time-dependent. Neuronal networks are mostly used in various types' system controls, thus

  10. Analysis of quantum network coding for realistic repeater networks

    NASA Astrophysics Data System (ADS)

    Satoh, Takahiko; Ishizaki, Kaori; Nagayama, Shota; Van Meter, Rodney

    2016-03-01

    Quantum repeater networks have attracted attention for the implementation of long-distance and large-scale sharing of quantum states. Recently, researchers extended classical network coding, which is a technique for throughput enhancement, into quantum information. The utility of quantum network coding (QNC) has been shown under ideal conditions, but it has not been studied previously under conditions of noise and shortage of quantum resources. We analyzed QNC on a butterfly network, which can create end-to-end Bell pairs at twice the rate of the standard quantum network repeater approach. The joint fidelity of creating two Bell pairs has a small penalty for QNC relative to entanglement swapping. It will thus be useful when we care more about throughput than fidelity. We found that the output fidelity drops below 0.5 when the initial Bell pairs have fidelity F <0.90 , even with perfect local gates. Local gate errors have a larger impact on quantum network coding than on entanglement swapping.

  11. Weighted network analysis of earthquake seismic data

    NASA Astrophysics Data System (ADS)

    Chakraborty, Abhijit; Mukherjee, G.; Manna, S. S.

    2015-09-01

    Three different earthquake seismic data sets are used to construct the earthquake networks following the prescriptions of Abe and Suzuki (2004). It has been observed that different links of this network appear with highly different strengths. This prompted us to extend the study of earthquake networks by considering it as the weighted network. Different properties of such weighted network have been found to be quite different from those of their un-weighted counterparts.

  12. FLOWNET: A Computer Program for Calculating Secondary Flow Conditions in a Network of Turbomachinery

    NASA Technical Reports Server (NTRS)

    Rose, J. R.

    1978-01-01

    The program requires the network parameters, the flow component parameters, the reservoir conditions, and the gas properties as input. It will then calculate all unknown pressures and the mass flow rate in each flow component in the network. The program can treat networks containing up to fifty flow components and twenty-five unknown network pressures. The types of flow components that can be treated are face seals, narrow slots, and pipes. The program is written in both structured FORTRAN (SFTRAN) and FORTRAN 4. The program must be run in an interactive (conversational) mode.

  13. Traffic chaotic dynamics modeling and analysis of deterministic network

    NASA Astrophysics Data System (ADS)

    Wu, Weiqiang; Huang, Ning; Wu, Zhitao

    2016-07-01

    Network traffic is an important and direct acting factor of network reliability and performance. To understand the behaviors of network traffic, chaotic dynamics models were proposed and helped to analyze nondeterministic network a lot. The previous research thought that the chaotic dynamics behavior was caused by random factors, and the deterministic networks would not exhibit chaotic dynamics behavior because of lacking of random factors. In this paper, we first adopted chaos theory to analyze traffic data collected from a typical deterministic network testbed — avionics full duplex switched Ethernet (AFDX, a typical deterministic network) testbed, and found that the chaotic dynamics behavior also existed in deterministic network. Then in order to explore the chaos generating mechanism, we applied the mean field theory to construct the traffic dynamics equation (TDE) for deterministic network traffic modeling without any network random factors. Through studying the derived TDE, we proposed that chaotic dynamics was one of the nature properties of network traffic, and it also could be looked as the action effect of TDE control parameters. A network simulation was performed and the results verified that the network congestion resulted in the chaotic dynamics for a deterministic network, which was identical with expectation of TDE. Our research will be helpful to analyze the traffic complicated dynamics behavior for deterministic network and contribute to network reliability designing and analysis.

  14. Honeycomb: Visual Analysis of Large Scale Social Networks

    NASA Astrophysics Data System (ADS)

    van Ham, Frank; Schulz, Hans-Jörg; Dimicco, Joan M.

    The rise in the use of social network sites allows us to collect large amounts of user reported data on social structures and analysis of this data could provide useful insights for many of the social sciences. This analysis is typically the domain of Social Network Analysis, and visualization of these structures often proves invaluable in understanding them. However, currently available visual analysis tools are not very well suited to handle the massive scale of this network data, and often resolve to displaying small ego networks or heavily abstracted networks. In this paper, we present Honeycomb, a visualization tool that is able to deal with much larger scale data (with millions of connections), which we illustrate by using a large scale corporate social networking site as an example. Additionally, we introduce a new probability based network metric to guide users to potentially interesting or anomalous patterns and discuss lessons learned during design and implementation.

  15. A 'bioproduction breadboard': programming, assembling, and actuating cellular networks.

    PubMed

    Zargar, Amin; Payne, Gregory F; Bentley, William E

    2015-12-01

    With advances in synthetic biology and biofabrication, cellular networks can be functionalized and connected with unprecedented sophistication. We describe a platform for the creation of a 'bioproduction breadboard'. This would consist of physically isolated product-producing cell populations, product capture devices, and other unit operations that function as programmed in place, using unique, orthogonal inputs. For product synthesis, customized cell populations would be connected through standardized, generic inputs allowing 'plug and play' functionality and primary, user-mediated regulation. In addition, through autonomous pathway redirection and balancing, the cells themselves would provide secondary, self-directed regulation to optimize bioproduction. By leveraging specialization and division of labor, we envision diverse cell populations linked to create new pathway designs. PMID:26342587

  16. (abstract) Deep Space Network Radiometric Remote Sensing Program

    NASA Technical Reports Server (NTRS)

    Walter, Steven J.

    1994-01-01

    Planetary spacecraft are viewed through a troposphere that absorbs and delays radio signals propagating through it. Tropospheric water, in the form of vapor, cloud liquid,and precipitation , emits radio noise which limits satellite telemetry communication link performance. Even at X-band, rain storms have severely affected several satellite experiments including a planetary encounter. The problem will worsen with DSN implementation of Ka-band becausecommunication link budgets will be dominated by tropospheric conditions. Troposphere-induced propagation delays currently limit VLBI accuracy and are significant sources of error for Doppler tracking. Additionally, the success of radio science programs such as satellite gravity wave experiments and atmospheric occultation experiments depends on minimizing the effect of watervapor-induced prop agation delays. In order to overcome limitations imposed by the troposphere, the Deep Space Network has supported a program of radiometric remote sensing. Currently, water vapor radiometers (WVRs) and microwave temperature profilers (MTPs) support many aspects of the Deep Space Network operations and research and development programs. Their capability to sense atmospheric water, microwave sky brightness, and atmospheric temperature is critical to development of Ka-band telemetry systems, communication link models, VLBI, satellite gravity waveexperiments, and r adio science missions. During 1993, WVRs provided data for propagation mode development, supp orted planetary missions, and demonstrated advanced tracking capability. Collection of atmospheric statistics is necessary to model and predict performance of Ka-band telemetry links, antenna arrays, and radio science experiments. Since the spectrum of weather variations has power at very long time scales, atmospheric measurements have been requested for periods ranging from one year to a decade at each DSN site. The resulting database would provide reliable statistics on daily

  17. Analysis and implementation of optoelectronic network routers

    NASA Astrophysics Data System (ADS)

    Raksapatcharawong, Mongkol

    1999-11-01

    Network routers based on optoelectronic technology have the potential to solve the network bandwidth problem which is becoming more and more critical in multiprocessor systems. By combining high-bandwidth optoelectronic I/O technology and high-performance CMOS logic technology, optoelectronic network routers promise both sophisticated switching functions as well as ample bandwidth that scales well with the performance of current and next-generation processors. Performance analysis and implementation of optoelectronic routers or other optoelectronic chips with this level of complexity, however, have not been pursued to a great extent before. This dissertation uses analytical and semi-empirical models to quantify and estimate the performance of optoelectronic routers at the chip and system levels, and it studies the feasibility of implementing such routers using GaAs MESFET/LED/OPFET and CMOS/SEED integrated technologies. The results show that optoelectronic routers may not only be technologically viable but also can provide certain architectural advantages in multiprocessor systems. Nevertheless, as shown in this dissertation, three major requirements must be met to effectively utilize this new technology. First, small and robust packaging at the chip and system levels that ensure high-bandwidth operation at useful interconnection distances and topologies are needed. Second, optoelectronic compatible CAD tools that effectively integrate a large array of optoelectronic devices with complex circuitry while retaining the potential performance of optoelectronic chips are needed. Third, optoelectronic devices must have uniform characteristics and reliability. In addition, advanced architectural techniques that efficiently exploit high-bandwidth optical interconnects are also required.

  18. Analysis and monitoring design for networks

    SciTech Connect

    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. External quality-assurance results for the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2004

    USGS Publications Warehouse

    Wetherbee, Gregory A.; Latysh, Natalie E.; Greene, Shannon M.

    2006-01-01

    The U.S. Geological Survey (USGS) used five programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program/National Trends Network (NADP/NTN) and two programs to provide external quality-assurance monitoring for the NADP/Mercury Deposition Network (NADP/MDN) during 2004. An intersite-comparison program was used to estimate accuracy and precision of field-measured pH and specific-conductance. The variability and bias of NADP/NTN data attributed to field exposure, sample handling and shipping, and laboratory chemical analysis were estimated using the sample-handling evaluation (SHE), field-audit, and interlaboratory-comparison programs. Overall variability of NADP/NTN data was estimated using a collocated-sampler program. Variability and bias of NADP/MDN data attributed to field exposure, sample handling and shipping, and laboratory chemical analysis were estimated using a system-blank program and an interlaboratory-comparison program. In two intersite-comparison studies, approximately 89 percent of NADP/NTN site operators met the pH measurement accuracy goals, and 94.7 to 97.1 percent of NADP/NTN site operators met the accuracy goals for specific conductance. Field chemistry measurements were discontinued by NADP at the end of 2004. As a result, the USGS intersite-comparison program also was discontinued at the end of 2004. Variability and bias in NADP/NTN data due to sample handling and shipping were estimated from paired-sample concentration differences and specific conductance differences obtained for the SHE program. Median absolute errors (MAEs) equal to less than 3 percent were indicated for all measured analytes except potassium and hydrogen ion. Positive bias was indicated for most of the measured analytes except for calcium, hydrogen ion and specific conductance. Negative bias for hydrogen ion and specific conductance indicated loss of hydrogen ion and decreased specific conductance from contact of the sample with

  20. Dynamic Analysis of Integrated Signaling, Metabolic, and Regulatory Networks

    PubMed Central

    Eddy, James A.; Papin, Jason A.

    2008-01-01

    Extracellular cues affect signaling, metabolic, and regulatory processes to elicit cellular responses. Although intracellular signaling, metabolic, and regulatory networks are highly integrated, previous analyses have largely focused on independent processes (e.g., metabolism) without considering the interplay that exists among them. However, there is evidence that many diseases arise from multifunctional components with roles throughout signaling, metabolic, and regulatory networks. Therefore, in this study, we propose a flux balance analysis (FBA)–based strategy, referred to as integrated dynamic FBA (idFBA), that dynamically simulates cellular phenotypes arising from integrated networks. The idFBA framework requires an integrated stoichiometric reconstruction of signaling, metabolic, and regulatory processes. It assumes quasi-steady-state conditions for “fast” reactions and incorporates “slow” reactions into the stoichiometric formalism in a time-delayed manner. To assess the efficacy of idFBA, we developed a prototypic integrated system comprising signaling, metabolic, and regulatory processes with network features characteristic of actual systems and incorporating kinetic parameters based on typical time scales observed in literature. idFBA was applied to the prototypic system, which was evaluated for different environments and gene regulatory rules. In addition, we applied the idFBA framework in a similar manner to a representative module of the single-cell eukaryotic organism Saccharomyces cerevisiae. Ultimately, idFBA facilitated quantitative, dynamic analysis of systemic effects of extracellular cues on cellular phenotypes and generated comparable time-course predictions when contrasted with an equivalent kinetic model. Since idFBA solves a linear programming problem and does not require an exhaustive list of detailed kinetic parameters, it may be efficiently scaled to integrated intracellular systems that incorporate signaling, metabolic, and

  1. Interdependent Multi-Layer Networks: Modeling and Survivability Analysis with Applications to Space-Based Networks

    PubMed Central

    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

  2. NASA Multidisciplinary Design and Analysis Fellowship Program

    NASA Technical Reports Server (NTRS)

    Schrage, D. P.; Craig, J. I.; Mavris, D. N.; Hale, M. A.; DeLaurentis, D.

    1999-01-01

    This report summarizes the results of a multi-year training grant for the development and implementation of a Multidisciplinary Design and Analysis (MDA) Fellowship Program at Georgia Tech. The Program funded the creation of graduate MS and PhD degree programs in aerospace systems design, analysis and integration. It also provided prestigious Fellowships with associated Industry Internships for outstanding engineering students. The graduate program has become the foundation for a vigorous and productive research effort and has produced: 20 MS degrees, 7 Ph.D. degrees, and has contributed to 9 ongoing Ph.D. students. The results of the research are documented in 32 publications (23 of which are included on a companion CDROM) and 4 annual student design reports (included on a companion CDROM). The legacy of this critical funding is the Center for Aerospace Systems Analysis at Georgia Tech which is continuing the graduate program, the research, and the industry internships established by this grant.

  3. Quantitative methods for ecological network analysis.

    PubMed

    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. PMID:15556474

  4. Network-Based Visual Analysis of Tabular Data

    ERIC Educational Resources Information Center

    Liu, Zhicheng

    2012-01-01

    Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…

  5. Traffic Driven Analysis of Cellular and WiFi Networks

    ERIC Educational Resources Information Center

    Paul, Utpal Kumar

    2012-01-01

    Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…

  6. Network algorithms for information analysis using the Titan Toolkit.

    SciTech Connect

    McLendon, William Clarence, III; Baumes, Jeffrey; Wilson, Andrew T.; Wylie, Brian Neil; Shead, Timothy M.

    2010-07-01

    The analysis of networked activities is dramatically more challenging than many traditional kinds of analysis. A network is defined by a set of entities (people, organizations, banks, computers, etc.) linked by various types of relationships. These entities and relationships are often uninteresting alone, and only become significant in aggregate. The analysis and visualization of these networks is one of the driving factors behind the creation of the Titan Toolkit. Given the broad set of problem domains and the wide ranging databases in use by the information analysis community, the Titan Toolkit's flexible, component based pipeline provides an excellent platform for constructing specific combinations of network algorithms and visualizations.

  7. Radiological Safety Analysis Computer Program

    Energy Science and Technology Software Center (ESTSC)

    2001-08-28

    RSAC-6 is the latest version of the RSAC program. It calculates the consequences of a release of radionuclides to the atmosphere. Using a personal computer, a user can generate a fission product inventory; decay and in-grow the inventory during transport through processes, facilities, and the environment; model the downwind dispersion of the activity; and calculate doses to downwind individuals. Internal dose from the inhalation and ingestion pathways is calculated. External dose from ground surface andmore » plume gamma pathways is calculated. New and exciting updates to the program include the ability to evaluate a release to an enclosed room, resuspension of deposited activity and evaluation of a release up to 1 meter from the release point. Enhanced tools are included for dry deposition, building wake, occupancy factors, respirable fraction, AMAD adjustment, updated and enhanced radionuclide inventory and inclusion of the dose-conversion factors from FOR 11 and 12.« less

  8. MIRAP, microcomputer reliability analysis program

    SciTech Connect

    Jehee, J.N.T.

    1989-01-01

    A program for a microcomputer is outlined that can determine minimal cut sets from a specified fault tree logic. The speed and memory limitations of the microcomputers on which the program is implemented (Atari ST and IBM) are addressed by reducing the fault tree's size and by storing the cut set data on disk. Extensive well proven fault tree restructuring techniques, such as the identification of sibling events and of independent gate events, reduces the fault tree's size but does not alter its logic. New methods are used for the Boolean reduction of the fault tree logic. Special criteria for combining events in the 'AND' and 'OR' logic avoid the creation of many subsuming cut sets which all would cancel out due to existing cut sets. Figures and tables illustrates these methods. 4 refs., 5 tabs.

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

    PubMed Central

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

    2008-01-01

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

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

    PubMed

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

    2008-07-01

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

  11. Thermal boundaries analysis program document

    NASA Technical Reports Server (NTRS)

    Evans, M. E.

    1975-01-01

    The digital program TBAP has been developed to provide thermal boundaries in the DD/M-relative velocity (D-V), dynamic pressure-relative velocity (q-V), and altitude-relative velocity (h-V) planes. These thermal boundaries are used to design and/or analyze shuttle orbiter entry trajectories. The TBAP has been used extensively in supporting the Flight Performance Branch of NASA in evaluating candidate trajectories for the thermal protection system design trajectory.

  12. 34 CFR 477.1 - What is the State Program Analysis Assistance and Policy Studies Program?

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... ANALYSIS ASSISTANCE AND POLICY STUDIES PROGRAM General § 477.1 What is the State Program Analysis Assistance and Policy Studies Program? The State Program Analysis Assistance and Policy Studies Program... 34 Education 3 2010-07-01 2010-07-01 false What is the State Program Analysis Assistance...

  13. 34 CFR 477.1 - What is the State Program Analysis Assistance and Policy Studies Program?

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... ANALYSIS ASSISTANCE AND POLICY STUDIES PROGRAM General § 477.1 What is the State Program Analysis Assistance and Policy Studies Program? The State Program Analysis Assistance and Policy Studies Program... 34 Education 3 2011-07-01 2011-07-01 false What is the State Program Analysis Assistance...

  14. Co-occurrence network analysis of modern Chinese poems

    NASA Astrophysics Data System (ADS)

    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.

  15. Mask Analysis Program (MAP) reference manual

    NASA Technical Reports Server (NTRS)

    Mitchell, C. L.

    1976-01-01

    A document intended to serve as a User's Manual and a Programmer's Manual for the Mask Analysis Program is presented. The first portion of the document is devoted to the user. It contains all of the information required to execute MAP. The remainder of the document describes the details of MAP software logic. Although the information in this portion is not required to run the program, it is recommended that every user review it to gain an appreciation for the program functions.

  16. Social Network Analysis: A case study of the Islamist terrorist network

    SciTech Connect

    Medina, Richard M

    2012-01-01

    Social Network Analysis is a compilation of methods used to identify and analyze patterns in social network systems. This article serves as a primer on foundational social network concepts and analyses and builds a case study on the global Islamist terrorist network to illustrate the use and usefulness of these methods. The Islamist terrorist network is a system composed of multiple terrorist organizations that are socially connected and work toward the same goals. This research utilizes traditional social network, as well as small-world, and scale-free analyses to characterize this system on individual, network and systemic levels. Leaders in the network are identified based on their positions in the social network and the network structure is categorized. Finally, two vital nodes in the network are removed and this version of the network is compared with the previous version to make implications of strengths, weaknesses and vulnerabilities. The Islamist terrorist network structure is found to be a resilient and efficient structure, even with important social nodes removed. Implications for counterterrorism are given from the results of each analysis.

  17. Network and eigenvalue analysis of financial transaction networks

    NASA Astrophysics Data System (ADS)

    Kyriakopoulos, F.; Thurner, S.; Puhr, C.; Schmitz, S. W.

    2009-10-01

    We study a dataset containing all financial transactions between the accounts of practically all major financial players within Austria over one year. We empirically analyze transaction networks of money (in and out) flows and report the characteristic network parameters. We observe a significant dependence of network topology on the time scales of observation, and remarkably low correlation between node degrees and transaction volume. We further use transaction timeseries of the financial agents to compute covariance matrices and their eigenvalue spectra. Eigenvectors corresponding to eigenvalues deviating from the Marcenko-Pastur law are analyzed in detail. The potential for practical use as an automated detection mechanism for abnormal behavior of financial players is discussed. The opinion expressed in this paper is that of the authors and does not necessarily reflect the opinion of the OeNB or the ESCB. in here

  18. Visual analysis and exploration of complex corporate shareholder networks

    NASA Astrophysics Data System (ADS)

    Tekušová, Tatiana; Kohlhammer, Jörn

    2008-01-01

    The analysis of large corporate shareholder network structures is an important task in corporate governance, in financing, and in financial investment domains. In a modern economy, large structures of cross-corporation, cross-border shareholder relationships exist, forming complex networks. These networks are often difficult to analyze with traditional approaches. An efficient visualization of the networks helps to reveal the interdependent shareholding formations and the controlling patterns. In this paper, we propose an effective visualization tool that supports the financial analyst in understanding complex shareholding networks. We develop an interactive visual analysis system by combining state-of-the-art visualization technologies with economic analysis methods. Our system is capable to reveal patterns in large corporate shareholder networks, allows the visual identification of the ultimate shareholders, and supports the visual analysis of integrated cash flow and control rights. We apply our system on an extensive real-world database of shareholder relationships, showing its usefulness for effective visual analysis.

  19. Using Social Network Analysis to Evaluate Community Capacity Building of a Regional Community Cancer Network

    ERIC Educational Resources Information Center

    Luque, John; Tyson, Dinorah Martinez; Lee, Ji-Hyun; Gwede, Clement; Vadaparampil, Susan; Noel-Thomas, Shalewa; Meade, Cathy

    2010-01-01

    The Tampa Bay Community Cancer Network (TBCCN) is one of 25 Community Network Programs funded by the National Cancer Institute's (NCI's) Center to Reduce Cancer Health Disparities with the objectives to create a collaborative infrastructure of academic and community based organizations and to develop effective and sustainable interventions to…

  20. Associated neural network independent component analysis structure

    NASA Astrophysics Data System (ADS)

    Kim, Keehoon; Kostrzweski, Andrew

    2006-05-01

    Detection, classification, and localization of potential security breaches in extremely high-noise environments are important for perimeter protection and threat detection both for homeland security and for military force protection. Physical Optics Corporation has developed a threat detection system to separate acoustic signatures from unknown, mixed sources embedded in extremely high-noise environments where signal-to-noise ratios (SNRs) are very low. Associated neural network structures based on independent component analysis are designed to detect/separate new acoustic sources and to provide reliability information. The structures are tested through computer simulations for each critical component, including a spontaneous detection algorithm for potential threat detection without a predefined knowledge base, a fast target separation algorithm, and nonparametric methodology for quantified confidence measure. The results show that the method discussed can separate hidden acoustic sources of SNR in 5 dB noisy environments with an accuracy of 80%.

  1. Method and tool for network vulnerability analysis

    DOEpatents

    Swiler, Laura Painton; Phillips, Cynthia A.

    2006-03-14

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

  2. Event/Time/Availability/Reliability-Analysis Program

    NASA Technical Reports Server (NTRS)

    Viterna, L. A.; Hoffman, D. J.; Carr, Thomas

    1994-01-01

    ETARA is interactive, menu-driven program that performs simulations for analysis of reliability, availability, and maintainability. Written to evaluate performance of electrical power system of Space Station Freedom, but methodology and software applied to any system represented by block diagram. Program written in IBM APL.

  3. Comparing Package Programs for Factor Analysis

    ERIC Educational Resources Information Center

    Wimberley, Ronald C.

    1978-01-01

    Earlier comparisons of packaged programs for factor analysis are updated because of recent revision in some programs. The top status of SPSS is no longer so apparent as formerly. BMD and SAS now have expanded options. SAS has flexibility and convenience. (Author)

  4. Finite-Element Composite-Analysis Program

    NASA Technical Reports Server (NTRS)

    Bowles, David E.

    1990-01-01

    Finite Element Composite Analysis Program, FECAP, special-purpose finite-element program for analyzing behavior of composite material with microcomputer. Procedure leads to set of linear simultaneous equations relating unknown nodal displacement to applied loads. Written in HP BASIC 3.0.

  5. Nonorthogonal Analysis of Variance Programs: An Evaluation.

    ERIC Educational Resources Information Center

    Hosking, James D.; Hamer, Robert M.

    1979-01-01

    Six computer programs for four methods of nonorthogonal analysis of variance are compared for capabilities, accuracy, cost, transportability, quality of documentation, associated computational capabilities, and ease of use: OSIRIS; SAS; SPSS; MANOVA; BMDP2V; and MULTIVARIANCE. (CTM)

  6. Science Education Programs That Work. A Collection of Proven Exemplary Educational Programs and Practices in the National Diffusion Network.

    ERIC Educational Resources Information Center

    Sivertsen, Mary Lewis, Comp.

    These programs are available to school systems or other educational institutions for implementation in the classroom. Some programs may be able to offer consultant services and limited assistance with the training and materials associated with installing one of these programs in schools. Information about the National Diffusion Network (NDN) is…

  7. Science Education Programs That work. A Collection of Proven Exemplary Educational Programs and Practices in the National Diffusion Network.

    ERIC Educational Resources Information Center

    Lewis, Mary G., Comp.

    This catalog contains descriptions of the science education programs in the National Diffusion Network (NDN). These programs are available to school systems or other educational institutions for implementation in their classrooms. Some programs may be able to offer consultant services and limited assistance with the training and materials…

  8. Science Education Programs That Work. A Collection of Proven Exemplary Educational Programs and Practices in the National Diffusion Network.

    ERIC Educational Resources Information Center

    Lewis, Mary G., Comp.

    This catalog contains descriptions of the science education programs and materials in the National Diffusion Network (NDN). These programs and materials are available to school systems or other educational institutions for implementation in their classrooms. Some programs may be able to offer consultant services and limited assistance with the…

  9. Science Education Programs That Work. A Collection of Proven Exemplary Educational Programs and Practices in the National Diffusion Network.

    ERIC Educational Resources Information Center

    Office of Educational Research and Improvement (ED), Washington, DC. National Diffusion Network.

    The National Diffusion Network (NDN) is a federally funded system that makes exemplary educational programs available for use by schools, colleges, and other institutions. This publication contains information describing the science education programs currently in the NDN, along with procedural information on how to access these programs. The…

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

    NASA Astrophysics Data System (ADS)

    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.

  11. IMES-Ural: the system of the computer programs for operational analysis of power flow distribution using telemetric data

    SciTech Connect

    Bogdanov, V.A.; Bol'shchikov, A.A.; Zifferman, E.O.

    1981-02-01

    A system of computer programs was described which enabled the user to perform real-time calculation and analysis of the current flow in the 500 kV network of the Ural Regional Electric Power Plant for all possible variations of the network, based on teleinformation and correctable equivalent parameters of the 220 to 110 kV network.

  12. Analysis of epileptic seizures with complex network.

    PubMed

    Ni, Yan; Wang, Yinghua; Yu, Tao; Li, Xiaoli

    2014-01-01

    Epilepsy is a disease of abnormal neural activities involving large area of brain networks. Until now the nature of functional brain network associated with epilepsy is still unclear. Recent researches indicate that the small world or scale-free attributes and the occurrence of highly clustered connection patterns could represent a general organizational principle in the human brain functional network. In this paper, we seek to find whether the small world or scale-free property of brain network is correlated with epilepsy seizure formation. A mass neural model was adopted to generate multiple channel EEG recordings based on regular, small world, random, and scale-free network models. Whether the connection patterns of cortical networks are directly associated with the epileptic seizures was investigated. The results showed that small world and scale-free cortical networks are highly correlated with the occurrence of epileptic seizures. In particular, the property of small world network is more significant during the epileptic seizures. PMID:25147576

  13. GUI Type Fault Diagnostic Program for a Turboshaft Engine Using Fuzzy and Neural Networks

    NASA Astrophysics Data System (ADS)

    Kong, Changduk; Koo, Youngju

    2011-04-01

    The helicopter to be operated in a severe flight environmental condition must have a very reliable propulsion system. On-line condition monitoring and fault detection of the engine can promote reliability and availability of the helicopter propulsion system. A hybrid health monitoring program using Fuzzy Logic and Neural Network Algorithms can be proposed. In this hybrid method, the Fuzzy Logic identifies easily the faulted components from engine measuring parameter changes, and the Neural Networks can quantify accurately its identified faults. In order to use effectively the fault diagnostic system, a GUI (Graphical User Interface) type program is newly proposed. This program is composed of the real time monitoring part, the engine condition monitoring part and the fault diagnostic part. The real time monitoring part can display measuring parameters of the study turboshaft engine such as power turbine inlet temperature, exhaust gas temperature, fuel flow, torque and gas generator speed. The engine condition monitoring part can evaluate the engine condition through comparison between monitoring performance parameters the base performance parameters analyzed by the base performance analysis program using look-up tables. The fault diagnostic part can identify and quantify the single faults the multiple faults from the monitoring parameters using hybrid method.

  14. Strategic Planning of Recycling Drop-Off Stations and Collection Network by Multiobjective Programming.

    PubMed

    Chang; Wei

    1999-09-01

    / Effective planning of solid-waste recycling programs is a substantial challenge to the current solid-waste management systems in Taiwan. Due to the rapid depletion of landfill space and the continuing delay in construction programs of municipal incinerators, solid-waste management strategies have to be reorganized in light of the success of recycling, recovery, and reuse of secondary materials. One of these efforts is how to effectively allocate recycling drop-off stations of appropriate size and how to design efficient collection-vehicle routing and scheduling programs in the solid waste collection network. This management strategy is particularly important in the privatized system with recycling containers and material recovery facilities (MRFs) owned by one agency. This research seeks multiobjective evaluation of the trade-off between the number and size of drop-off stations, the population covered in the service network, the average walking distance to drop-off stations by the population, and the distance traveled by collection vehicles. It also illustrates the use of the multiobjective nonlinear mixed integer programming model to achieve such goals that are solved by the genetic algorithms (GA) in a geographical information system (GIS) platform. The case study shows the application potential of such a methodology in the city of Kaohsiung in Taiwan.KEY WORDS: Optimization analysis; Recycling; Solid waste managementhttp://link.springer-ny.com/link/service/journals/00267/bibs/24n2p247.html PMID:10384033

  15. Spreadsheet Analysis Of Queuing In A Computer Network

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1992-01-01

    Method of analyzing responses of computer network based on simple queuing-theory mathmatical models via spreadsheet program. Effects of variations in traffic, capacities of channels, and message protocols assessed.

  16. External quality-assurance project report for the National Atmospheric Deposition Program/National Trends Network and Mercury Deposition Network, 2009-2010

    USGS Publications Warehouse

    Wetherbee, Gregory A.; Martin, RoseAnn; Rhodes, Mark F.; Chesney, Tanya A.

    2014-01-01

    The U.S. Geological Survey operated six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program/National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2009–2010. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples; a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory (CAL) and Mercury (Hg) Analytical Laboratory (HAL). The blind-audit program was also implemented for the MDN to evaluate analytical bias in total Hg concentration data produced by the HAL. The co-located-sampler program was used to identify and quantify potential shifts in NADP data resulting from replacement of original network instrumentation with new electronic recording rain gages (E-gages) and precipitation collectors that use optical sensors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the United States. Results also suggest that retrofit of the NADP networks with the new precipitation collectors could cause –8 to +14 percent shifts in NADP annual precipitation-weighted mean concentrations and total deposition values for ammonium, nitrate, sulfate, and hydrogen ion, and larger shifts (+13 to +74 percent) for calcium, magnesium, sodium, potassium, and chloride. The prototype N-CON Systems bucket collector is more efficient in the catch of precipitation in winter than Aerochem Metrics Model 301 collector, especially for light snowfall.

  17. U.S. Geological Survey external quality-assurance project report to the National Atmospheric Deposition Program / National Trends Network and Mercury Deposition Network, 2007-08

    USGS Publications Warehouse

    Wetherbee, Gregory A.; Latysh, Natalie E.; Chesney, Tanya A.

    2010-01-01

    The U.S. Geological Survey (USGS) used six distinct programs to provide external quality-assurance monitoring for the National Atmospheric Deposition Program / National Trends Network (NTN) and Mercury Deposition Network (MDN) during 2007-08. The field-audit program assessed the effects of onsite exposure, sample handling, and shipping on the chemistry of NTN samples, and a system-blank program assessed the same effects for MDN. Two interlaboratory-comparison programs assessed the bias and variability of the chemical analysis data from the Central Analytical Laboratory (CAL), Mercury (Hg) Analytical Laboratory (HAL), and 12 other participating laboratories. A blind-audit program was also implemented for the MDN to evaluate analytical bias in HAL total Hg concentration data. A co-located-sampler program was used to identify and quantify potential shifts in NADP data resulting from replacement of original network instrumentation with new electronic recording rain gages (E-gages) and prototype precipitation collectors. The results indicate that NADP data continue to be of sufficient quality for the analysis of spatial distributions and time trends of chemical constituents in wet deposition across the U.S. NADP data-quality objectives continued to be achieved during 2007-08. Results also indicate that retrofit of the NADP networks with the new E-gages is not likely to create step-function type shifts in NADP precipitation-depth records, except for sites where annual precipitation depth is dominated by snow because the E-gages tend to catch more snow than the original NADP rain gages. Evaluation of prototype precipitation collectors revealed no difference in sample volumes and analyte concentrations between the original NADP collectors and modified, deep-bucket collectors, but the Yankee Environmental Systems, Inc. (YES) collector obtained samples of significantly higher volumes and analyte concentrations than the standard NADP collector.

  18. How To Design and Deliver an Effective Job Development and Placement Program. Neighborhood Networks.

    ERIC Educational Resources Information Center

    Department of Housing and Urban Development, Washington, DC. Office of Multifamily Housing.

    This second of four publications in the Neighborhood Networks Employment Series focuses on how Neighborhood Networks centers can deliver effective job development and placement programs for residents who are on public assistance, are unemployed, or are underemployed. This guide explains how Neighborhood Networks centers can develop relationships…

  19. Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice1[OPEN

    PubMed Central

    Obertello, Mariana; Shrivastava, Stuti; Katari, Manpreet S.; Coruzzi, Gloria M.

    2015-01-01

    In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis. PMID:26045464

  20. Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice.

    PubMed

    Obertello, Mariana; Shrivastava, Stuti; Katari, Manpreet S; Coruzzi, Gloria M

    2015-08-01

    In this study, we used a cross-species network approach to uncover nitrogen (N)-regulated network modules conserved across a model and a crop species. By translating gene network knowledge from the data-rich model Arabidopsis (Arabidopsis thaliana) to a crop, rice (Oryza sativa), we identified evolutionarily conserved N-regulatory modules as targets for translational studies to improve N use efficiency in transgenic plants. To uncover such conserved N-regulatory network modules, we first generated an N-regulatory network based solely on rice transcriptome and gene interaction data. Next, we enhanced the network knowledge in the rice N-regulatory network using transcriptome and gene interaction data from Arabidopsis and new data from Arabidopsis and rice plants exposed to the same N treatment conditions. This cross-species network analysis uncovered a set of N-regulated transcription factors (TFs) predicted to target the same genes and network modules in both species. Supernode analysis of the TFs and their targets in these conserved network modules uncovered genes directly related to N use (e.g. N assimilation) and to other shared biological processes indirectly related to N. This cross-species network approach was validated with members of two TF families in the supernode network, BASIC-LEUCINE ZIPPER TRANSCRIPTION FACTOR1-TGA and HYPERSENSITIVITY TO LOW PI-ELICITED PRIMARY ROOT SHORTENING1 (HRS1)/HRS1 Homolog family, which have recently been experimentally validated to mediate the N response in Arabidopsis. PMID:26045464

  1. Performance analysis of electronic code division multiple access based virtual private networks over passive optical networks

    NASA Astrophysics Data System (ADS)

    Nadarajah, Nishaanthan; Nirmalathas, Ampalavanapillai

    2008-03-01

    A solution for implementing multiple secure virtual private networks over a passive optical network using electronic code division multiple access is proposed and experimentally demonstrated. The multiple virtual private networking capability is experimentally demonstrated with 40 Mb/s data multiplexed with a 640 Mb/s electronic code that is unique to each of the virtual private networks in the passive optical network, and the transmission of the electronically coded data is carried out using Fabry-Perot laser diodes. A theoretical scalability analysis for electronic code division multiple access based virtual private networks over a passive optical network is also carried out to identify the performance limits of the scheme. Several sources of noise such as optical beat interference and multiple access interference that are present in the receiver are considered with different operating system parameters such as transmitted optical power, spectral width of the broadband optical source, and processing gain to study the scalability of the network.

  2. Dynamic network data envelopment analysis for university hospitals evaluation

    PubMed Central

    Lobo, Maria Stella de Castro; Rodrigues, Henrique de Castro; André, Edgard Caires Gazzola; de Azeredo, Jônatas Almeida; Lins, Marcos Pereira Estellita

    2016-01-01

    ABSTRACT OBJECTIVE To develop an assessment tool to evaluate the efficiency of federal university general hospitals. METHODS Data envelopment analysis, a linear programming technique, creates a best practice frontier by comparing observed production given the amount of resources used. The model is output-oriented and considers variable returns to scale. Network data envelopment analysis considers link variables belonging to more than one dimension (in the model, medical residents, adjusted admissions, and research projects). Dynamic network data envelopment analysis uses carry-over variables (in the model, financing budget) to analyze frontier shift in subsequent years. Data were gathered from the information system of the Brazilian Ministry of Education (MEC), 2010-2013. RESULTS The mean scores for health care, teaching and research over the period were 58.0%, 86.0%, and 61.0%, respectively. In 2012, the best performance year, for all units to reach the frontier it would be necessary to have a mean increase of 65.0% in outpatient visits; 34.0% in admissions; 12.0% in undergraduate students; 13.0% in multi-professional residents; 48.0% in graduate students; 7.0% in research projects; besides a decrease of 9.0% in medical residents. In the same year, an increase of 0.9% in financing budget would be necessary to improve the care output frontier. In the dynamic evaluation, there was progress in teaching efficiency, oscillation in medical care and no variation in research. CONCLUSIONS The proposed model generates public health planning and programming parameters by estimating efficiency scores and making projections to reach the best practice frontier. PMID:27191158

  3. SURE reliability analysis: Program and mathematics

    NASA Technical Reports Server (NTRS)

    Butler, Ricky W.; White, Allan L.

    1988-01-01

    The SURE program is a new reliability analysis tool for ultrareliable computer system architectures. The computational methods on which the program is based provide an efficient means for computing accurate upper and lower bounds for the death state probabilities of a large class of semi-Markov models. Once a semi-Markov model is described using a simple input language, the SURE program automatically computes the upper and lower bounds on the probability of system failure. A parameter of the model can be specified as a variable over a range of values directing the SURE program to perform a sensitivity analysis automatically. This feature, along with the speed of the program, makes it especially useful as a design tool.

  4. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

    The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, ``Energy Efficiency, Developing Countries, and Eastern Europe,`` part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program`s researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

  5. Network model and short circuit program for the Kennedy Space Center electric power distribution system

    NASA Technical Reports Server (NTRS)

    1976-01-01

    Assumptions made and techniques used in modeling the power network to the 480 volt level are discussed. Basic computational techniques used in the short circuit program are described along with a flow diagram of the program and operational procedures. Procedures for incorporating network changes are included in this user's manual.

  6. Center for development technology and program in technology and human affairs. [emphasizing technology-based networks

    NASA Technical Reports Server (NTRS)

    Wong, M. D.

    1974-01-01

    The role of technology in nontraditional higher education with particular emphasis on technology-based networks is analyzed nontraditional programs, institutions, and consortia are briefly reviewed. Nontraditional programs which utilize technology are studied. Technology-based networks are surveyed and analyzed with regard to kinds of students, learning locations, technology utilization, interinstitutional relationships, cost aspects, problems, and future outlook.

  7. Factors Impacting Adult Learner Achievement in a Technology Certificate Program on Computer Networks

    ERIC Educational Resources Information Center

    Delialioglu, Omer; Cakir, Hasan; Bichelmeyer, Barbara A.; Dennis, Alan R.; Duffy, Thomas M.

    2010-01-01

    This study investigates the factors impacting the achievement of adult learners in a technology certificate program on computer networks. We studied 2442 participants in 256 institutions. The participants were older than age 18 and were enrolled in the Cisco Certified Network Associate (CCNA) technology training program as "non-degree" or…

  8. Methodologies and techniques for analysis of network flow data

    SciTech Connect

    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.

  9. Fracture network evaluation program (FraNEP): A software for analyzing 2D fracture trace-line maps

    NASA Astrophysics Data System (ADS)

    Zeeb, Conny; Gomez-Rivas, Enrique; Bons, Paul D.; Virgo, Simon; Blum, Philipp

    2013-10-01

    Fractures, such as joints, faults and veins, strongly influence the transport of fluids through rocks by either enhancing or inhibiting flow. Techniques used for the automatic detection of lineaments from satellite images and aerial photographs, LIDAR technologies and borehole televiewers significantly enhanced data acquisition. The analysis of such data is often performed manually or with different analysis software. Here we present a novel program for the analysis of 2D fracture networks called FraNEP (Fracture Network Evaluation Program). The program was developed using Visual Basic for Applications in Microsoft Excel™ and combines features from different existing software and characterization techniques. The main novelty of FraNEP is the possibility to analyse trace-line maps of fracture networks applying the (1) scanline sampling, (2) window sampling or (3) circular scanline and window method, without the need of switching programs. Additionally, binning problems are avoided by using cumulative distributions, rather than probability density functions. FraNEP is a time-efficient tool for the characterisation of fracture network parameters, such as density, intensity and mean length. Furthermore, fracture strikes can be visualized using rose diagrams and a fitting routine evaluates the distribution of fracture lengths. As an example of its application, we use FraNEP to analyse a case study of lineament data from a satellite image of the Oman Mountains.

  10. Dynamic network analysis of protein interactions

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind; Deri, Joya

    2007-03-01

    Network approaches have recently become a popular tool to study complex systems such as cellular metabolism and protein interactions. A substantial number of analyses of the protein interaction network (PIN) of the yeast Saccharomyces cerevisiae have considered this network as a static entity, not taking the network's dynamic nature into account. Here, we examine the time-variation of gene regulation superimposed on the PIN by defining mRNA expression profiles throughout the cell cycle as node weights. To characterize these network dynamics, we have both developed a set of novel network measures as well as studied previously published measures for weighted networks. We expect that our approach will provide a deeper understanding of protein regulation during the cell cycle.

  11. Multilayer Kohonen network and its separability analysis

    NASA Astrophysics Data System (ADS)

    Liu, Chao-yuan; Li, Jie-Gu

    1995-04-01

    This paper presents a model of a multilayer Kohonen network. Because of obeying the winner- take-all learning rule and projecting high dimensional patterns into one or two dimensional space, the conventional Kohonen network has many limitations in its applications, such as pattern separability limitation and open ended limitation. Taking advantage of the innovation for learning method and its multilayer structure, the multilayer Kohonen network has the performance of nonlinear pattern partition. Owing to labeling pattern clusters with appropriate category names or numbers only, the network is an open ended system, so it is far more powerful than the conventional Kohonen network. The mechanism of the multilayer Kohonen network is explained in detail, and its nonlinear pattern separability is analyzed theoretically. As a result of an experiment made by two layer Kohonen network, a set of human head contour figures assigned into diverse by categories is shown.

  12. GNAP (Graphic Normative Analysis Program)

    USGS Publications Warehouse

    Bowen, Roger W.; Odell, John, North, L.D.

    1979-01-01

    A user-oriented command language is developed to provide direct control over the computation and output of the standard CIPW norm. A user-supplied input format for the oxide values may be given or a standard CIPW Rock Analysis format may be used. Once the oxide values have been read by the computer, these values may be manipulated by the user and the 'norm' recalculated on the basis of the manipulated or 'adjusted' values. Additional output capabilities include tabular listing of computed values, summary listings suitable for publication, x-y plots, and ternary diagrams. As many as 20 rock analysis cards may be processed as a group. Any number of such groups may be processed in any one computer run.

  13. 76 FR 11310 - Alternatives Analysis Program Discretionary Funding Allocations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-01

    ... Federal Transit Administration Alternatives Analysis Program Discretionary Funding Allocations AGENCY: Federal Transit Administration (FTA), DOT. ACTION: Alternatives Analysis Program Announcement of Project...) announces the selection of projects funded with unallocated Section 5339 Alternatives Analysis Program...

  14. Smart-Grid Backbone Network Real-Time Delay Reduction via Integer Programming.

    PubMed

    Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

    2016-08-01

    This research investigates an optimal delay-based virtual topology design using integer linear programming (ILP), which is applied to the current backbone networks such as smart-grid real-time communication systems. A network traffic matrix is applied and the corresponding virtual topology problem is solved using the ILP formulations that include a network delay-dependent objective function and lightpath routing, wavelength assignment, wavelength continuity, flow routing, and traffic loss constraints. The proposed optimization approach provides an efficient deterministic integration of intelligent sensing and decision making, and network learning features for superior smart grid operations by adaptively responding the time-varying network traffic data as well as operational constraints to maintain optimal virtual topologies. A representative optical backbone network has been utilized to demonstrate the proposed optimization framework whose simulation results indicate that superior smart-grid network performance can be achieved using commercial networks and integer programming. PMID:25935050

  15. On Kirchhoff's equations and variational approaches to electrical network analysis

    NASA Astrophysics Data System (ADS)

    Ercan, Alper

    2016-03-01

    Analysis of electrical networks using variational techniques, while repeatedly mentioned in the literature, is not widely known or utilized. In this short communication, we emphasize the connection between Kirchhoff's network equations, energy conservation, and variational analysis techniques using a brief example.

  16. Experimental analysis of large belief networks for medical diagnosis.

    PubMed

    Pradhan, M; Provan, G; Henrion, M

    1994-01-01

    We present an experimental analysis of two parameters that are important in knowledge engineering for large belief networks. We conducted the experiments on a network derived from the Internist-1 medical knowledge base. In this network, a generalization of the noisy-OR gate is used to model causal independence for the multivalued variables, and leak probabilities are used to represent the nonspecified causes of intermediate states and findings. We study two network parameters, (1) the parameter governing the assignment of probability values to the network, and (2) the parameter denoting whether the network nodes represent variables with two or more than two values. The experimental results demonstrate that the binary simplification computes diagnoses with similar accuracy to the full multivalued network. We discuss the implications of these parameters, as well other network parameters, for knowledge engineering for medical applications. PMID:7950030

  17. Network congestion analysis of gravity generated models

    NASA Astrophysics Data System (ADS)

    Maniadakis, Dimitris; Varoutas, Dimitris

    2014-07-01

    The network topology has lately proved to be critical to the appearance of traffic congestion, with scale-free networks being the less affected at high volumes of traffic. Here, the congestion dynamics are investigated for a class of networks that has experienced a resurgence of interest, the networks based on the gravity model. In addition, supplementary to the standard paradigm of uniform traffic volumes between randomly interacting node pairs, more realistic gravity traffic patterns are used to simulate the flows in the network. Results indicate that depending on the traffic pattern, the networks have different tolerance to congestion. Experiment simulation shows that the topologies created on the basis of the gravity model suffer less from congestion than the random, the scale-free or the Jackson-Rogers ones under both random and gravity traffic patterns. The congestion level is found to be approximately correlated with the network clustering coefficient in the case of random traffic, whereas in the case of gravity traffic such a correlation is not a trivial one. Other basic network properties such as the average shortest path and the diameter are seen to correlate fairly well with the congestion level. Further investigation on the adjustment of the gravity model parameters indicates particular sensitivity to network congestion. This work may have practical implications for designing traffic networks with both reasonable budget and good performance.

  18. Building a Virtual Network in a Community Health Research Training Program

    PubMed Central

    Lau, Francis; Hayward, Robert

    2000-01-01

    Objective: To describe the experiences, lessons, and implications of building a virtual network as part of a two-year community health research training program in a Canadian province. Design: An action research field study in which 25 health professionals from 17 health regions participated in a seven-week training course on health policy, management, economics, research methods, data analysis, and computer technology. The participants then returned to their regions to apply the knowledge in different community health research projects. Ongoing faculty consultations and support were provided as needed. Each participant was given a notebook computer with the necessary software, Internet access, and technical support for two years, to access information resources, engage in group problem solving, share ideas and knowledge, and collaborate on projects. Measurements: Data collected over two years consisted of program documents, records of interviews with participants and staff, meeting notes, computer usage statistics, automated online surveys, computer conference postings, program Web site, and course feedback. The analysis consisted of detailed review and comparison of the data from different sources. NUD*IST was then used to validate earlier study findings. Results: The ten key lessons are that role clarity, technology vision, implementation staging, protected time, just-in-time training, ongoing facilitation, work integration, participatory design, relationship building, and the demonstration of results are essential ingredients for building a successful network. Conclusion: This study provides a descriptive model of the processes involved in developing, in the community health setting, virtual networks that can be used as the basis for future research and as a practical guide for managers. PMID:10887165

  19. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

    The Energy Analysis Program has played an active role in the analysis and discussion of energy and environmental issues at several levels. (1) at the international level, with programs as developing scenarios for long-term energy demand in developing countries and organizing leading an analytic effort, Energy Efficiency, Developing Countries, and Eastern Europe,'' part of a major effort to increase support for energy efficiency programs worldwide; (2) at national level, the Program has been responsible for assessing energy forecasts and policies affecting energy use (e.g., appliance standards, National Energy Strategy scenarios); and (3) at the state and utility levels, the Program has been a leader in promoting integrated resource utility planning; the collaborative process has led to agreement on a new generation of utility demand-site programs in California, providing an opportunity to use knowledge and analytic techniques of the Program's researchers. We continue to place highest on analyzing energy efficiency, with particular attention given to energy use in buildings. The Program continues its active analysis of international energy issues in Asia (including China), the Soviet Union, South America, and Western Europe. Analyzing the costs and benefits of different levels of standards for residential appliances continues to be the largest single area of research within the Program. The group has developed and applied techniques for forecasting energy demand (or constructing scenarios) for the United States. We have built a new model of industrial energy demand, are in the process of making major changes in our tools for forecasting residential energy demand, have built an extensive and documented energy conservation supply curve of residential energy use, and are beginning an analysis of energy-demand forecasting for commercial buildings.

  20. Applying temporal network analysis to the venture capital market

    NASA Astrophysics Data System (ADS)

    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.

  1. Public transport networks: empirical analysis and modeling

    NASA Astrophysics Data System (ADS)

    von Ferber, C.; Holovatch, T.; Holovatch, Yu.; Palchykov, V.

    2009-03-01

    Public transport networks of fourteen cities of so far unexplored network size are analyzed in standardized graph representations: the simple graph of the network map, the bipartite graph of routes and stations, and both one mode projections of the latter. Special attention is paid to the inter-relations and spatial embedding of transport routes. This systematic approach reveals rich behavior beyond that of the ubiquitous scale-free complex network. We find strong evidence for structures in PTNs that are counter-intuitive and need to be explained, among these a pronounced diversity in the expression of typical network characteristics within the present sample of cities, a surprising geometrical behavior with respect to the two-dimensional geographical embedding and an unexpected attraction between transport routes. A simple model based on these observations reproduces many of the identified PTN properties by growing networks of attractive self-avoiding walks.

  2. Network analysis of human heartbeat dynamics

    NASA Astrophysics Data System (ADS)

    Shao, Zhi-Gang

    2010-02-01

    We construct the complex networks of human heartbeat dynamics and investigate their statistical properties, using the visibility algorithm proposed by Lacasa and co-workers [Proc. Natl. Acad. Sci. U.S.A. 105, 4972 (2008)]. Our results show that the associated networks for the time series of heartbeat interval are always scale-free, high clustering, hierarchy, and assortative mixing. In particular, the assortative coefficient of associated networks could distinguish between healthy subjects and patients with congestive heart failure.

  3. Analysis of IMS spectra using neural networks

    SciTech Connect

    Bell, S.E.

    1992-09-01

    Ion mobility spectrometry (IMS) has been used for over 20 years, and IMS coupled to gas chromatography (GC/IMS) has been used for over 10 years. There still is no systematic approach to IMS spectral interpretation such as exists for mass spectrometry and infrared spectrometry. Neural networks, a form of adaptive pattern recognition, were examined as a method of data reduction for IMS and GC/IMS. A wide variety of volatile organics were analyzed using IMS and GC/IMS and submitted to different networks for identification. Several different networks and data preprocessing algorithms were studied. A network was linked to a simple rule-based expert system and analyzed. The expert system was used to filter out false positive identifications made by the network using retention indices. The various network configurations were compared to other pattern recognition techniques, including human experts. The network performance was comparable to human experts, but responded much faster. Preliminary comparison of the network to other pattern recognition showed comparable performance. Linkage of the network output to the rule-based retention index system yielded the best performance.

  4. Analysis of IMS spectra using neural networks

    SciTech Connect

    Bell, S.E.

    1992-01-01

    Ion mobility spectrometry (IMS) has been used for over 20 years, and IMS coupled to gas chromatography (GC/IMS) has been used for over 10 years. There still is no systematic approach to IMS spectral interpretation such as exists for mass spectrometry and infrared spectrometry. Neural networks, a form of adaptive pattern recognition, were examined as a method of data reduction for IMS and GC/IMS. A wide variety of volatile organics were analyzed using IMS and GC/IMS and submitted to different networks for identification. Several different networks and data preprocessing algorithms were studied. A network was linked to a simple rule-based expert system and analyzed. The expert system was used to filter out false positive identifications made by the network using retention indices. The various network configurations were compared to other pattern recognition techniques, including human experts. The network performance was comparable to human experts, but responded much faster. Preliminary comparison of the network to other pattern recognition showed comparable performance. Linkage of the network output to the rule-based retention index system yielded the best performance.

  5. Ad Hoc Networks: Headline 2000 Communications Analysis

    NASA Astrophysics Data System (ADS)

    Blair, W. D.; Reynolds, A. B.

    2002-06-01

    This report examines unit location data and terrain from Headline 2000 to investigate communications networks within the maneuver units. Within the Enhanced Combat Force timeframe, such units would be supported by a Tactical Data Distribution Sub-system (TDDS). This is envisaged as an ad hoc network changing its topology as units maneuver across the battlespace. The report describes approaches that can be applied to Headline 2000 and other data to characterize the nature of the network topology, both statically and as it changes over time, in order to explore the impact on the TDDS network capacity and hence to hence to assist in elucidating consequent requirements of a candidate TDDS.

  6. Linking Transnational Logics: A Feminist Rhetorical Analysis of Public Policy Networks

    ERIC Educational Resources Information Center

    Dingo, Rebecca

    2008-01-01

    In this article, the author investigates the circulation and appropriation of representations of women in public policy. The author effectively mobilizes the metaphor of the network to examine the discursive intersections and transnational links between U.S. welfare programs and the World Bank gender mainstreaming policies. Her analysis reveals…

  7. Investigating the Potential of Using Social Network Analysis in Educational Evaluation

    ERIC Educational Resources Information Center

    Penuel, William R.; Sussex, Willow; Korbak, Christine; Hoadley, Christopher

    2006-01-01

    This article describes results of a study investigating the potential of using social network analysis to evaluate programs that aim at improving schools by fostering greater collaboration between teachers. The goal of this method is to use data about teacher collaboration within schools to map the distribution of expertise and resources needed to…

  8. Why social network analysis is important to Air Force applications

    NASA Astrophysics Data System (ADS)

    Havig, Paul R.; McIntire, John P.; Geiselman, Eric; Mohd-Zaid, Fairul

    2012-06-01

    Social network analysis is a powerful tool used to help analysts discover relationships amongst groups of people as well as individuals. It is the mathematics behind such social networks as Facebook and MySpace. These networks alone cause a huge amount of data to be generated and the issue is only compounded once one adds in other electronic media such as e-mails and twitter. In this paper we outline the basics of social network analysis and how it may be used in current and future Air Force applications.

  9. Protein identification by spectral networks analysis.

    PubMed

    Bandeira, Nuno; Tsur, Dekel; Frank, Ari; Pevzner, Pavel A

    2007-04-10

    Advances in tandem mass spectrometry (MS/MS) steadily increase the rate of generation of MS/MS spectra. As a result, the existing approaches that compare spectra against databases are already facing a bottleneck, particularly when interpreting spectra of modified peptides. Here we explore a concept that allows one to perform an MS/MS database search without ever comparing a spectrum against a database. We propose to take advantage of spectral pairs, which are pairs of spectra obtained from overlapping (often nontryptic) peptides or from unmodified and modified versions of the same peptide. Having a spectrum of a modified peptide paired with a spectrum of an unmodified peptide allows one to separate the prefix and suffix ladders, to greatly reduce the number of noise peaks, and to generate a small number of peptide reconstructions that are likely to contain the correct one. The MS/MS database search is thus reduced to extremely fast pattern-matching (rather than time-consuming matching of spectra against databases). In addition to speed, our approach provides a unique paradigm for identifying posttranslational modifications by means of spectral networks analysis. PMID:17404225

  10. Topology design and performance analysis of an integrated communication network

    NASA Technical Reports Server (NTRS)

    Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.

    1985-01-01

    A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.

  11. Graph theoretical analysis of complex networks in the brain

    PubMed Central

    Stam, Cornelis J; Reijneveld, Jaap C

    2007-01-01

    Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336

  12. egoSlider: Visual Analysis of Egocentric Network Evolution.

    PubMed

    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. PMID:26529706

  13. From sensor networks to connected analysis tools

    NASA Astrophysics Data System (ADS)

    Dawes, N.; Bavay, M.; Egger, T.; Sarni, S.; Salehi, A.; Davison, A.; Jeung, H.; Aberer, K.; Lehning, M.

    2012-04-01

    Multi-disciplinary data systems provide excellent tools for locating data, but most eventually provide a series of local files for further processing, providing marginal advantages for the regular user. The Swiss Experiment Platform (SwissEx) was built with the primary goal of enabling high density measurements, integrating them with lower density existing measurements and encouraging cross/inter-disciplinary collaborations. Nearing the end of the project, we have exceeded these goals, also providing connected tools for direct data access from analysis applications. SwissEx (www.swiss-experiment.ch) provides self-organising networks for rapid deployment and integrates these data with existing measurements from across environmental research. The data are categorised and documented according to their originating experiments and fieldsites as well as being searchable globally. Data from SwissEx are available for download, but we also provide tools to directly access data from within common scientific applications (Matlab, LabView, R) and numerical models such as Alpine3D (using a data acquisition plugin and preprocessing library, MeteoIO). The continuation project (the Swiss Environmental Data and Knowledge Platform) will aim to continue the ideas developed within SwissEx and (alongside cloud enablement and standardisation) work on the development of these tools for application specific tasks. We will work alongside several projects from a wide range of disciplines to help them to develop tools which either require real-time data, or large data samples. As well as developing domain specific tools, we will also be working on tools for the utilisation of the latest knowledge in data control, trend analysis, spatio-temporal statistics and downscaling (developed within the CCES Extremes project), which will be a particularly interesting application when combined with the large range of measurements already held in the system. This presentation will look at the

  14. The Lockheed Martin Network: An Intranet Analysis.

    ERIC Educational Resources Information Center

    Okey, Robert M.

    Lockheed Martin Corporation, which is comprised of approximately 72 operating units (some 200,000 employees) worldwide, has set up an intranet called the Lockheed Martin Network. On the network, the corporation released a set of corporate policies via web pages which must be implemented by each of its companies. Because each company varied on what…

  15. Longitudinal Network Analysis Using Multidimensional Scaling.

    ERIC Educational Resources Information Center

    Barnett, George A.; Palmer, Mark T.

    The Galileo System, a variant of metric multidimensional scaling, is used in this paper to analyze over-time changes in social networks. The paper first discusses the theoretical necessity for the use of this procedure and the methodological problems associated with its use. It then examines the air traffic network among 31 major cities in the…

  16. Comparative network analysis via differential graphlet communities

    PubMed Central

    Wong, Serene W H; Cercone, Nick; Jurisica, Igor

    2015-01-01

    While current protein interaction data provides a rich resource for molecular biology, it mostly lacks condition-specific details. Abundance of mRNA data for most diseases provides potential to model condition-specific transcriptional changes. Transcriptional data enables modeling disease mechanisms, and in turn provide potential treatments. While approaches to compare networks constructed from healthy and disease samples have been developed, they do not provide the complete comparison, evaluations are performed on very small networks, or no systematic network analyses are performed on differential network structures. We propose a novel method for efficiently exploiting network structure information in the comparison between any graphs, and validate results in non-small cell lung cancer. We introduce the notion of differential graphlet community to detect deregulated subgraphs between any graphs such that the network structure information is exploited. The differential graphlet community approach systematically captures network structure differences between any graphs. Instead of using connectivity of each protein or each edge, we used shortest path distributions on differential graphlet communities in order to exploit network structure information on identified deregulated subgraphs. We validated the method by analyzing three non-small cell lung cancer datasets and validated results on four independent datasets. We observed that the shortest path lengths are significantly longer for normal graphs than for tumor graphs between genes that are in differential graphlet communities, suggesting that tumor cells create "shortcuts" between biological processes that may not be present in normal conditions. PMID:25283527

  17. Design and analysis of the satellite laser communications network

    NASA Astrophysics Data System (ADS)

    Ren, Pei-an; Qian, Fengchen; Liu, Qiang; Jin, Linlin

    2015-02-01

    A satellite laser communications network structure with two layers and multiple domains has been proposed, which performance has been simulated by OPENT. To simulation, we design several OPNET models of the network's components based on a satellite constellation with two layers and multiple domains, as network model, node model, MAC layer protocol and optical antenna model. The network model consists of core layer and access layer. The core network consists of four geostationary orbit (GEO) satellites which are uniformly distributed in the geostationary orbit. The access network consists of 6 low Earth orbit (LEO) satellites which is the walker delta (walk-δ) constellation with three orbit planes. In access layer, each plane has two satellites, and the constellation is stably. The satellite constellation presented for space laser network can meet the demand of coverage in the middle and low latitude by a few satellites. Also several terminal device models such as the space laser transmitter, receiver, protocol layer module and optical antenna have been designed according to the inter-satellite links in different orbits t from GEO to LEO or GEO to ground. The influence to network of different transmitting throughput, receiving throughput, network protocol and average time delay are simulated. Simulation results of network coverage, connectivity and traffic load performance in different scenes show that the satellite laser network presented by the paper can be fit for high-speed satellite communications. Such analysis can provide effective reference for the research of satellite laser networking and communication protocol.

  18. Criteria for Evaluating Alternative Network and Link Layer Protocols for the NASA Constellation Program Communication Architecture

    NASA Technical Reports Server (NTRS)

    Benbenek, Daniel; Soloff, Jason; Lieb, Erica

    2010-01-01

    Selecting a communications and network architecture for future manned space flight requires an evaluation of the varying goals and objectives of the program, development of communications and network architecture evaluation criteria, and assessment of critical architecture trades. This paper uses Cx Program proposed exploration activities as a guideline; lunar sortie, outpost, Mars, and flexible path options are described. A set of proposed communications network architecture criteria are proposed and described. They include: interoperability, security, reliability, and ease of automating topology changes. Finally a key set of architecture options are traded including (1) multiplexing data at a common network layer vs. at the data link layer, (2) implementing multiple network layers vs. a single network layer, and (3) the use of a particular network layer protocol, primarily IPv6 vs. Delay Tolerant Networking (DTN). In summary, the protocol options are evaluated against the proposed exploration activities and their relative performance with respect to the criteria are assessed. An architectural approach which includes (a) the capability of multiplexing at both the network layer and the data link layer and (b) a single network layer for operations at each program phase, as these solutions are best suited to respond to the widest array of program needs and meet each of the evaluation criteria.

  19. Space station interior noise analysis program

    NASA Technical Reports Server (NTRS)

    Stusnick, E.; Burn, M.

    1987-01-01

    Documentation is provided for a microcomputer program which was developed to evaluate the effect of the vibroacoustic environment on speech communication inside a space station. The program, entitled Space Station Interior Noise Analysis Program (SSINAP), combines a Statistical Energy Analysis (SEA) prediction of sound and vibration levels within the space station with a speech intelligibility model based on the Modulation Transfer Function and the Speech Transmission Index (MTF/STI). The SEA model provides an effective analysis tool for predicting the acoustic environment based on proposed space station design. The MTF/STI model provides a method for evaluating speech communication in the relatively reverberant and potentially noisy environments that are likely to occur in space stations. The combinations of these two models provides a powerful analysis tool for optimizing the acoustic design of space stations from the point of view of speech communications. The mathematical algorithms used in SSINAP are presented to implement the SEA and MTF/STI models. An appendix provides an explanation of the operation of the program along with details of the program structure and code.

  20. Space station interior noise analysis program

    NASA Astrophysics Data System (ADS)

    Stusnick, E.; Burn, M.

    1987-02-01

    Documentation is provided for a microcomputer program which was developed to evaluate the effect of the vibroacoustic environment on speech communication inside a space station. The program, entitled Space Station Interior Noise Analysis Program (SSINAP), combines a Statistical Energy Analysis (SEA) prediction of sound and vibration levels within the space station with a speech intelligibility model based on the Modulation Transfer Function and the Speech Transmission Index (MTF/STI). The SEA model provides an effective analysis tool for predicting the acoustic environment based on proposed space station design. The MTF/STI model provides a method for evaluating speech communication in the relatively reverberant and potentially noisy environments that are likely to occur in space stations. The combinations of these two models provides a powerful analysis tool for optimizing the acoustic design of space stations from the point of view of speech communications. The mathematical algorithms used in SSINAP are presented to implement the SEA and MTF/STI models. An appendix provides an explanation of the operation of the program along with details of the program structure and code.

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

    SciTech Connect

    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. Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

    DOE Data Explorer

    Maddalena, Damian; Hoffman, Forrest; Kumar, Jitendra; Hargrove, William

    2014-08-01

    Sampling networks rarely conform to spatial and temporal ideals, often comprised of network sampling points which are unevenly distributed and located in less than ideal locations due to access constraints, budget limitations, or political conflict. Quantifying the global, regional, and temporal representativeness of these networks by quantifying the coverage of network infrastructure highlights the capabilities and limitations of the data collected, facilitates upscaling and downscaling for modeling purposes, and improves the planning efforts for future infrastructure investment under current conditions and future modeled scenarios. The work presented here utilizes multivariate spatiotemporal clustering analysis and representativeness analysis for quantitative landscape characterization and assessment of the Fluxnet, RAINFOR, and ForestGEO networks. Results include ecoregions that highlight patterns of bioclimatic, topographic, and edaphic variables and quantitative representativeness maps of individual and combined networks.

  3. System analysis of power transients in advanced WDM networks

    NASA Astrophysics Data System (ADS)

    Gorinevsky, Dimitry; Farber, Gennady

    2002-06-01

    This paper considers dynamical transient effects in the physical layer of an optical circuit-switched WDM network. These transients of the average transmission power have millisecond time scales. Instead of studying detailed nonlinear dynamics of the network elements, such as optical line amplifiers, a linearized model of the dynamics around a given steady state is considered. System-level analysis in this paper uses modern control theory methods and handles nonlinearity as uncertainty. The analysis translates requirements on the network performance into the requirements to the network elements. These requirements involve a few gross measures of performance for network elements and do not depend on the circuit switching state. One such performance measure is the worst amplification gain for all harmonic disturbances of the average transmission power. Another, is cross coupling of the wavelength channel power variations. The derived requirements guarantee system-level performance for all network configurations and can be used for specifying optical components and subsystems.

  4. Network Analysis Guided Synthesis of Weisaconitine D and Liljestrandinine

    PubMed Central

    Marth, C. J.; Gallego, G. M.; Lee, J. C.; Lebold, T. P.; Kulyk, S.; Kou, K. G. M.; Qin, J.; Lilien, R.; Sarpong, R.

    2015-01-01

    General strategies for the chemical synthesis of organic compounds, especially of architecturally complex natural products, are not easily identified. Here, we present a method to establish a strategy for such syntheses, which begins with a process termed ‘network analysis’. This exercise, along with other considerations, has been used to identify a versatile synthetic intermediate that facilitated syntheses of the diterpenoid alkaloids weisaconitine D and liljestrandinine, as well as the core of gomandonine. The diterpenoid alkaloids comprise some of the most architecturally complex and functional group dense secondary metabolites ever isolated. For these reasons, they present a significant challenge for chemical synthesis. The synthesis approach described herein is a notable departure from other strategies adopted for the syntheses of related structures and affords not only the targeted natural products, but also intermediates and derivatives in the three subfamilies of diterpenoid alkaloids (i.e., C-18, C-19, and C-20), providing the first unified synthetic strategy to these natural products. This work validates the utility of network analysis as a starting point for identifying strategies for the syntheses of architecturally complex secondary metabolites. An easily accessible web-based graphing program has been developed for this purpose. PMID:26675722

  5. Mapping Extension's Networks: Using Social Network Analysis to Explore Extension's Outreach

    ERIC Educational Resources Information Center

    Bartholomay, Tom; Chazdon, Scott; Marczak, Mary S.; Walker, Kathrin C.

    2011-01-01

    The University of Minnesota Extension conducted a social network analysis (SNA) to examine its outreach to organizations external to the University of Minnesota. The study found that its outreach network was both broad in its reach and strong in its connections. The study found that SNA offers a unique method for describing and measuring Extension…

  6. The Applicability of Social Network Analysis to the Study of Networked Learning

    ERIC Educational Resources Information Center

    Toikkanen, Tarmo; Lipponen, Lasse

    2011-01-01

    Studying networked learning (NL) by applying social network analysis (SNA) has gained popularity in recent years. However, it appears that in the context of NL the choice of SNA indices is very often dictated by using easily achievable SNA tools. Most studies in this field only involve a single group of students and utilise simple indices, such as…

  7. Natural Time Analysis and Complex Networks

    NASA Astrophysics Data System (ADS)

    Sarlis, Nicholas; Skordas, Efthimios; Lazaridou, Mary; Varotsos, Panayiotis

    2013-04-01

    Here, we review the analysis of complex time series in a new time domain, termed natural time, introduced by our group [1,2]. This analysis conforms to the desire to reduce uncertainty and extract signal information as much as possible [3]. It enables [4] the distinction between the two origins of self-similarity when analyzing data from complex systems, i.e., whether self-similarity solely results from long-range temporal correlations (the process's memory only) or solely from the process's increments infinite variance (heavy tails in their distribution). Natural time analysis captures the dynamical evolution of a complex system and identifies [5] when the system enters a critical stage. Hence, this analysis plays a key role in predicting forthcoming catastrophic events in general. Relevant examples, compiled in a recent monograph [6], have been presented in diverse fields, including Solid State Physics [7], Statistical Physics (for example systems exhibiting self-organized criticality [8]), Cardiology [9,10], Earth Sciences [11] (Geophysics, Seismology), Environmental Sciences (e.g. see Ref. [12]), etc. Other groups have proposed and developed a network approach to earthquake events with encouraging results. A recent study [13] reveals that this approach is strengthened if we combine it with natural time analysis. In particular, we find [13,14] that the study of the spatial distribution of the variability [15] of the order parameter fluctuations, defined in natural time, provides important information on the dynamical evolution of the system. 1. P. Varotsos, N. Sarlis, and E. Skordas, Practica of Athens Academy, 76, 294-321, 2001. 2. P.A. Varotsos, N.V. Sarlis, and E.S. Skordas, Phys. Rev. E, 66, 011902 , 2002. 3. S. Abe, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and P.A. Varotsos, Phys. Rev. Lett. 94, 170601, 2005. 4. P.A. Varotsos, N.V. Sarlis, E.S. Skordas, H.K. Tanaka and M.S. Lazaridou, Phys. Rev. E, 74, 021123, 2006. 5. P.Varotsos, N. V. Sarlis, E. S. Skordas

  8. Classroom Community at a Distance: A Comparative Analysis of Two ALN-Based University Programs.

    ERIC Educational Resources Information Center

    Rovai, Alfred P.

    2001-01-01

    Describes a study that examined sense of community in two graduate distance education programs that differed only in the amount of face-to-face contact. Discusses results of multivariate analysis of variance and post hoc discriminant analysis and includes implications for asynchronous learning networks (ALNs) in higher education, especially the…

  9. The cryogenics analysis program for Apollo mission planning and analysis

    NASA Technical Reports Server (NTRS)

    Scott, W.; Williams, J.

    1971-01-01

    The cryogenics analysis program was developed as a simplified tool for use in premission planning operations for the Apollo command service module. Through a dynamic development effort, the program has been extended to include real time and postflight analysis capabilities with nominal and contingency planning features. The technical aspects of the program and a comparison of ground test and mission data with data generated by using the cryogenics analysis program are presented. The results of the program capability to predict flight requirements also are presented. Comparisons of data from the program with data from flight results, from a tank qualifications program, and from various system anomalies that have been encountered are discussed. Future plans and additional considerations for the program also are included. Among these plans are a three tank management scheme for hydrogen, venting profile generation for Skylab, and a capability for handling two gas atmospheres. The plan for two gas atmospheres will involve the addition of the capability to handle nitrogen as well as oxygen and hydrogen.

  10. Protein Co-Expression Network Analysis (ProCoNA)

    SciTech Connect

    Gibbs, David L.; Baratt, Arie; Baric, Ralph; Kawaoka, Yoshihiro; Smith, Richard D.; Orwoll, Eric S.; Katze, Michael G.; Mcweeney, Shannon K.

    2013-06-01

    Biological networks are important for elucidating disease etiology due to their ability to model complex high dimensional data and biological systems. Proteomics provides a critical data source for such models, but currently lacks robust de novo methods for network construction, which could bring important insights in systems biology. We have evaluated the construction of network models using methods derived from weighted gene co-expression network analysis (WGCNA). We show that approximately scale-free peptide networks, composed of statistically significant modules, are feasible and biologically meaningful using two mouse lung experiments and one human plasma experiment. Within each network, peptides derived from the same protein are shown to have a statistically higher topological overlap and concordance in abundance, which is potentially important for inferring protein abundance. The module representatives, called eigenpeptides, correlate significantly with biological phenotypes. Furthermore, within modules, we find significant enrichment for biological function and known interactions (gene ontology and protein-protein interactions). Biological networks are important tools in the analysis of complex systems. In this paper we evaluate the application of weighted co-expression network analysis to quantitative proteomics data. Protein co-expression networks allow novel approaches for biological interpretation, quality control, inference of protein abundance, a framework for potentially resolving degenerate peptide-protein mappings, and a biomarker signature discovery.

  11. Assessing Group Interaction with Social Language Network Analysis

    NASA Astrophysics Data System (ADS)

    Scholand, Andrew J.; Tausczik, Yla R.; Pennebaker, James W.

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  12. Assessing group interaction with social language network analysis.

    SciTech Connect

    Pennebaker, James; Scholand, Andrew Joseph; Tausczik, Yla R.

    2010-04-01

    In this paper we discuss a new methodology, social language network analysis (SLNA), that combines tools from social language processing and network analysis to assess socially situated working relationships within a group. Specifically, SLNA aims to identify and characterize the nature of working relationships by processing artifacts generated with computer-mediated communication systems, such as instant message texts or emails. Because social language processing is able to identify psychological, social, and emotional processes that individuals are not able to fully mask, social language network analysis can clarify and highlight complex interdependencies between group members, even when these relationships are latent or unrecognized.

  13. Languages across Borders: Social Network Development in an Adolescent Two-Way Dual-Language Program

    ERIC Educational Resources Information Center

    Kibler, Amanda K.; Atteberry, Allison; Hardigree, Christine N.; Salerno, April S.

    2015-01-01

    Background/Context: Two-way dual-language programs have become an increasingly popular educational model in the United States for language minority and majority speakers, with a small but growing number of programs at the high school level. Little is known, however, about how adolescents' social networks develop in the contexts of these programs.…

  14. Globalizing Social Justice Education: The Case of The Global Solidarity Network Study e-Broad Program

    ERIC Educational Resources Information Center

    Harrison, Yvonne D.; Kostic, Kevin; Toton, Suzanne C.; Zurek, Jerome

    2010-01-01

    This paper documents the development, implementation, and evaluation of "The Global Solidarity Network Study e-Broad Program (GSNSeBP)", an online social justice educational program that is blended into an onsite academic course. This global electronic program, which was developed through a partnership between Catholic Relief Services (CRS) and…

  15. Hierarchical neural networks for autonomous data analysis and decision making

    NASA Technical Reports Server (NTRS)

    Eberlein, Susan; Yates, Gigi

    1988-01-01

    A neural network based data analysis and decision making system to increase the autonomy of a planetary rover or similar exploratory vehicle is presented. A hierarchical series of neural networks for real time analysis of scientific images is used. The system under development emphasizes analysis of multispectral images by classifier and feature detector neural networks, to provide information on the mineral composition of a scene. A hierarchy of alternating analysis and decision making networks is being developed to allow increasingly fine scale analysis in regions of the image that are potentially important. It is noted that this system will facilitate both the selection of high priorty scientific information for transmission to earth, and the autonomous collection of rocks and soil for sample return.

  16. Integrated Structural Analysis and Test Program

    NASA Technical Reports Server (NTRS)

    Kaufman, Daniel

    2005-01-01

    An integrated structural-analysis and structure-testing computer program is being developed in order to: Automate repetitive processes in testing and analysis; Accelerate pre-test analysis; Accelerate reporting of tests; Facilitate planning of tests; Improve execution of tests; Create a vibration, acoustics, and shock test database; and Integrate analysis and test data. The software package includes modules pertaining to sinusoidal and random vibration, shock and time replication, acoustics, base-driven modal survey, and mass properties and static/dynamic balance. The program is commanded by use of ActiveX controls. There is minimal need to generate command lines. Analysis or test files are selected by opening a Windows Explorer display. After selecting the desired input file, the program goes to a so-called analysis data process or test data process, depending on the type of input data. The status of the process is given by a Windows status bar, and when processing is complete, the data are reported in graphical, tubular, and matrix form.

  17. QUALITY ASSURANCE PROGRAM FOR WET DEPOSITION SAMPLING AND CHEMICAL ANALYSES FOR THE NATIONAL TRENDS NETWORK.

    USGS Publications Warehouse

    Schroder, LeRoy J.; Malo, Bernard A.

    1985-01-01

    The purpose of the National Trends Network is to delineate the major inorganic constituents in the wet deposition in the United States. The approach chosen to monitor the Nation's wet deposition is to install approximately 150 automatic sampling devices with at least one collector in each state. Samples are collected at one week intervals, removed from collectors, and transported to an analytical laboratory for chemical analysis. The quality assurance program has divided wet deposition monitoring into 5 parts: (1) Sampling site selection, (2) sampling device, (3) sample container, (4) sample handling, and (5) laboratory analysis. Each of these five components is being examined using existing designs or new designs. Each existing or proposed sampling site is visited and a criteria audit is performed.

  18. Dynamic Network-Based Epistasis Analysis: Boolean Examples

    PubMed Central

    Azpeitia, Eugenio; Benítez, Mariana; Padilla-Longoria, Pablo; Espinosa-Soto, Carlos; Alvarez-Buylla, Elena R.

    2011-01-01

    In this article we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the inference of gene regulatory networks. 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, epistasis is defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus (herein, classical epistasis). 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 inference of gene interaction topologies is 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 article complements previous accounts, not only by focusing on the implications of the hierarchical and

  19. Multiobjective blockmodeling for social network analysis.

    PubMed

    Brusco, Michael; Doreian, Patrick; Steinley, Douglas; Satornino, Cinthia B

    2013-07-01

    To date, most methods for direct blockmodeling of social network data have focused on the optimization of a single objective function. However, there are a variety of social network applications where it is advantageous to consider two or more objectives simultaneously. These applications can broadly be placed into two categories: (1) simultaneous optimization of multiple criteria for fitting a blockmodel based on a single network matrix and (2) simultaneous optimization of multiple criteria for fitting a blockmodel based on two or more network matrices, where the matrices being fit can take the form of multiple indicators for an underlying relationship, or multiple matrices for a set of objects measured at two or more different points in time. A multiobjective tabu search procedure is proposed for estimating the set of Pareto efficient blockmodels. This procedure is used in three examples that demonstrate possible applications of the multiobjective blockmodeling paradigm. PMID:25106397

  20. BASIC Programming In Water And Wastewater Analysis

    NASA Technical Reports Server (NTRS)

    Dreschel, Thomas

    1988-01-01

    Collection of computer programs assembled for use in water-analysis laboratories. First program calculates quality-control parameters used in routine water analysis. Second calculates line of best fit for standard concentrations and absorbances entered. Third calculates specific conductance from conductivity measurement and temperature at which measurement taken. Fourth calculates any one of four types of residue measured in water. Fifth, sixth, and seventh calculate results of titrations commonly performed on water samples. Eighth converts measurements, to actual dissolved-oxygen concentration using oxygen-saturation values for fresh and salt water. Ninth and tenth perform calculations of two other common titrimetric analyses. Eleventh calculates oil and grease residue from water sample. Last two use spectro-photometric measurements of absorbance at different wavelengths and residue measurements. Programs included in collection written for Hewlett-Packard 2647F in H-P BASIC.

  1. Ball bearing heat analysis program (BABHAP)

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The Ball Bearing Heat Analysis Program (BABHAP) is an attempt to assemble a series of equations, some of which are non-linear algebraic systems, in a logical order, which when solved, provide a complex analysis of load distribution among the balls, ball velocities, heat generation resulting from friction, applied load, and ball spinning, minimum lubricant film thickness, and many additional characteristics of ball bearing systems. Although initial design requirements for BABHAP were dictated by the core limitations of the PDP 11/45 computer, (approximately 8K of real words with limited number of instructions) the program dimensions can easily be expanded for large core computers such as the UNIVAC 1108. The PDP version of BABHAP is also operational on the UNIVAC system with the exception that the PDP uses 029 punch and the UNIVAC uses 026. A conversion program was written to allow transfer between machines.

  2. NASA Multidisciplinary Design and Analysis Fellowship Program

    NASA Technical Reports Server (NTRS)

    1995-01-01

    This report is a Year 1 interim report of the progress on the NASA multidisciplinary Design and Analysis Fellowship Program covering the period, January 1, 1995 through September 30, 1995. It summarizes progress in establishing the MDA Fellowship Program at Georgia Tech during the initial year. Progress in the advertisement of the program, recruiting results for the 1995-96 academic year, placement of the Fellows in industry during Summer 1995, program development at the M.S. and Ph.D. levels, and collaboration and dissemination of results are summarized in this report. Further details of the first year's progress will be included in the report from the Year 1 Workshop to be held at NASA Langley on December 7-8, 1995.

  3. Timeline analysis program (TLA-1), appendices

    NASA Technical Reports Server (NTRS)

    Miller, K. H.

    1976-01-01

    Appendices for the Timeline Analysis Program (TLA-1) were given. The appendices contain the Atlanta terminal area scenarios, the task catalog and the control and display configurations for the forward and aft flight decks of the NASA 515 aircraft, and the event/procedure, phase, mission, and subsystem catalogs.

  4. NASA program decisions using reliability analysis.

    NASA Technical Reports Server (NTRS)

    Steinberg, A.

    1972-01-01

    NASA made use of the analytical outputs of reliability people to make management decisions on the Apollo program. Such decisions affected the amount of the incentive fees, how much acceptance testing was necessary, how to optimize development testing, whether to approve engineering changes, and certification of flight readiness. Examples of such analysis are discussed and related to programmatic decisions.-

  5. The Boston Rehabilitation Program, An Independent Analysis.

    ERIC Educational Resources Information Center

    Keyes, Langley C., Jr.

    BURP, The Boston Rehabilitation Program, is described and analyzed in this monograph published by the Joint Center for Urban Studies. Its purpose is to provide an independent analysis of BURP as a political, economic, and social event. Examination is given to the nation's first effort to carry out large-scale residential rehabilitation in blighted…

  6. Subsatellite Orbital Analysis Program (SOAP) user's guide

    NASA Technical Reports Server (NTRS)

    Castle, K. G.; Voss, J. M.; Gibson, J. S.

    1981-01-01

    The features and use of the subsatellite operational analysis are examined. The model simulates several Earth-orbiting vehicles, their pilots, control systems, and interaction with the environment. The use of the program, input and output capabilities, executive structures, and properties of the vehicles and environmental effects which it models are described.

  7. SYNOPTIC RAINFALL DATA ANALYSIS PROGRAM (SYNOP)

    EPA Science Inventory

    An integral part of the assessment of storm loads on water quality is the statistical evaluation of rainfall records. Hourly rainfall records of many years duration are cumbersome and difficult to analyze. The purpose of this rainfall data analysis program is to provide the user ...

  8. Network traffic analysis using dispersion patterns

    Energy Science and Technology Software Center (ESTSC)

    2010-03-15

    The Verilog code us used to map a measurement solution on FPGA to analyze network traffic. It realizes a set of Bloom filters and counters, besides associated control logic that can quickly measure statistics like InDegree, OutDegree, Depth, in the context of Traffic Dispersion Graphs. Such patterns are helpful in classification of network activity, like Peer to Peer and Port-Scanning, in the traffic.

  9. An Analysis of the Structure and Evolution of Networks

    ERIC Educational Resources Information Center

    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…

  10. Social Network Analysis to Evaluate an Interdisciplinary Research Center

    ERIC Educational Resources Information Center

    Aboelela, Sally W.; Merrill, Jacqueline A.; Carley, Kathleen M.; Larson, Elaine

    2007-01-01

    We sought to examine the growth of an interdisciplinary center using social network analysis techniques. Specific aims were to examine the patterns of growth and interdisciplinary connectedness of the Center and to identify the social network characteristics of its productive members. The setting for this study was The Center for Interdisciplinary…

  11. A Graph Oriented Approach for Network Forensic Analysis

    ERIC Educational Resources Information Center

    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…

  12. A Semantic Network Analysis of the International Communication Association.

    ERIC Educational Resources Information Center

    Doerfel, Marya L.; Barnett, George A.

    1999-01-01

    Finds that a semantic network analysis of the International Communication Association (ICA) based on paper titles presented at its 1991 conference had a high degree of correspondence with the affiliation structure. Suggests validity of the procedures employed for determining semantic networks. Interprets results in regard to this journal's…

  13. Evaluating network models: A likelihood analysis

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Many models are put forward to mimic the evolution of real networked systems. A well-accepted way to judge the validity is to compare the modeling results with real networks subject to several structural features. Even for a specific real network, we cannot fairly evaluate the goodness of different models since there are too many structural features while there is no criterion to select and assign weights on them. Motivated by the studies on link prediction algorithms, we propose a unified method to evaluate the network models via the comparison of the likelihoods of the currently observed network driven by different models, with an assumption that the higher the likelihood is, the more accurate the model is. We test our method on the real Internet at the Autonomous System (AS) level, and the results suggest that the Generalized Linear Preferential (GLP) model outperforms the Tel Aviv Network Generator (Tang), while both two models are better than the Barabási-Albert (BA) and Erdös-Rényi (ER) models. Our method can be further applied in determining the optimal values of parameters that correspond to the maximal likelihood. The experiment indicates that the parameters obtained by our method can better capture the characters of newly added nodes and links in the AS-level Internet than the original methods in the literature.

  14. Managing Programs for Adults Learning English. CAELA Network Brief

    ERIC Educational Resources Information Center

    Rodriguez, Amber Gallup; Burt, Miriam; Peyton, Joy Kreeft; Ueland, Michelle

    2009-01-01

    Programs for adults learning English vary widely in size and scope. Some are large, multilevel programs, such as the Arlington Education and Employment Program (REEP) in Virginia, which has more than 45 staff members, over 100 volunteers, and an array of student services for the 7,500 learners served annually at the program's 7 locations. Others…

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

    PubMed Central

    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.1 PMID:26175682

  16. Higher-order aggregate networks in the analysis of temporal networks: path structures and centralities

    NASA Astrophysics Data System (ADS)

    Scholtes, Ingo; Wider, Nicolas; Garas, Antonios

    2016-03-01

    Despite recent advances in the study of temporal networks, the analysis of time-stamped network data is still a fundamental challenge. In particular, recent studies have shown that correlations in the ordering of links crucially alter causal topologies of temporal networks, thus invalidating analyses based on static, time-aggregated representations of time-stamped data. These findings not only highlight an important dimension of complexity in temporal networks, but also call for new network-analytic methods suitable to analyze complex systems with time-varying topologies. Addressing this open challenge, here we introduce a novel framework for the study of path-based centralities in temporal networks. Studying betweenness, closeness and reach centrality, we first show than an application of these measures to time-aggregated, static representations of temporal networks yields misleading results about the actual importance of nodes. To overcome this problem, we define path-based centralities in higher-order aggregate networks, a recently proposed generalization of the commonly used static representation of time-stamped data. Using data on six empirical temporal networks, we show that the resulting higher-order measures better capture the true, temporal centralities of nodes. Our results demonstrate that higher-order aggregate networks constitute a powerful abstraction, with broad perspectives for the design of new, computationally efficient data mining techniques for time-stamped relational data.

  17. Mobilizing homeless youth for HIV prevention: a social network analysis of the acceptability of a face-to-face and online social networking intervention

    PubMed Central

    Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Barman Adhikari, Anamika; Milburn, Norweeta G.

    2012-01-01

    The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth.Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F recruited online youth (OY) to participate in MySpace and Facebook communities where digital media was disseminated and discussed. The resulting social networks were assessed with respect to size, growth, density, relative centrality of positions and homophily of ties. Seven PL, 53 F2F and 103 OY created two large networks. After the first 50 F2F youth participated, online networks entered a rapid growth phase. OY were among the most central youth in these networks. Younger aged persons and females were disproportionately connected to like youth. The program appears highly acceptable to homeless youth. Social network analysis revealed which PL were the most critical to the program and which types of participants (younger youth and females) may require additional outreach efforts in the future. PMID:22247453

  18. Mobilizing Homeless Youth for HIV Prevention: A Social Network Analysis of the Acceptability of a Face-to-Face and Online Social Networking Intervention

    ERIC Educational Resources Information Center

    Rice, Eric; Tulbert, Eve; Cederbaum, Julie; Adhikari, Anamika Barman; Milburn, Norweeta G.

    2012-01-01

    The objective of the study is to use social network analysis to examine the acceptability of a youth-led, hybrid face-to-face and online social networking HIV prevention program for homeless youth. Seven peer leaders (PLs) engaged face-to-face homeless youth (F2F) in the creation of digital media projects (e.g. You Tube videos). PL and F2F…

  19. Technology Network Ties: Network Services and Technology Programs for New York State's Educational System.

    ERIC Educational Resources Information Center

    New York State Education Dept., Albany. Office of Elementary and Secondary Education Planning, Testing, and Technological Services.

    The New York State Technology Network Ties (TNT) systems is a statewide telecommunications network which consists of computers, telephone lines, and telecommunications hardware and software. This network links school districts, Boards of Cooperative Educational Services (BOCES), libraries, other educational institutions, and the State Education…

  20. Application of artificial neural networks in nonlinear analysis of trusses

    NASA Technical Reports Server (NTRS)

    Alam, J.; Berke, L.

    1991-01-01

    A method is developed to incorporate neural network model based upon the Backpropagation algorithm for material response into nonlinear elastic truss analysis using the initial stiffness method. Different network configurations are developed to assess the accuracy of neural network modeling of nonlinear material response. In addition to this, a scheme based upon linear interpolation for material data, is also implemented for comparison purposes. It is found that neural network approach can yield very accurate results if used with care. For the type of problems under consideration, it offers a viable alternative to other material modeling methods.

  1. Analysis of community structure in networks of correlated data

    SciTech Connect

    Gomez, S.; Jensen, P.; Arenas, A.

    2008-12-25

    We present a reformulation of modularity that allows the analysis of the community structure in networks of correlated data. The new modularity preserves the probabilistic semantics of the original definition even when the network is directed, weighted, signed, and has self-loops. This is the most general condition one can find in the study of any network, in particular those defined from correlated data. We apply our results to a real network of correlated data between stores in the city of Lyon (France).

  2. Economic analysis of life cycle costing irrigation pipe network design

    SciTech Connect

    Bliesner, R.D.; Keller, J.; Watters, G.Z.; Cone, B.W.

    1981-01-01

    Three irrigation systems (solid set sprinkle, trickle and center pivot) were designed using a computerized life cycle costing irrigation pipe network design program for economic life cycles of 5, 10, 15, 20, 30 and 40 years with irrigation demand, interest plus profit, initial energy cost and energy inflation held constant. A comparative economic analysis was made of the designs to determine the impact of economic life cycle on energy usage, capital cost, total annual cost over the system life and annual cost over loan period for the three system types. Since farmers can rarely borrow money for the full economic life of the system, the annual cost over the loan term of a more expensive, energy efficient system may not be affordable. A procedure for examining the extra cash flow required and energy saved by designing for the full economic life as opposed to designing for the shorter loan term is presented as well as one possible method of determining a tax incentive program to encourage the design of more energy efficient systems. For the economic parameters used, a relatively small tax incentive produces a significant energy savings. However, different values for the economic parameters could significantly change the results.

  3. Multifractal analysis of weighted networks by a modified sandbox algorithm

    NASA Astrophysics Data System (ADS)

    Song, Yu-Qin; Liu, Jin-Long; Yu, Zu-Guo; Li, Bao-Gen

    2015-12-01

    Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): “Sierpinski” WFNs and “Cantor dust” WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks — collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights.

  4. Multifractal analysis of weighted networks by a modified sandbox algorithm.

    PubMed

    Song, Yu-Qin; Liu, Jin-Long; Yu, Zu-Guo; Li, Bao-Gen

    2015-01-01

    Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor dust" WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks - collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights. PMID:26634304

  5. Multifractal analysis of weighted networks by a modified sandbox algorithm

    PubMed Central

    Song, Yu-Qin; Liu, Jin-Long; Yu, Zu-Guo; Li, Bao-Gen

    2015-01-01

    Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): “Sierpinski” WFNs and “Cantor dust” WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks — collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights. PMID:26634304

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

    PubMed

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

    2015-01-01

    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. PMID:26634293

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

    PubMed Central

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

    2015-01-01

    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. PMID:26634293

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

    NASA Astrophysics Data System (ADS)

    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.

  9. Structural analysis of metabolic networks based on flux centrality.

    PubMed

    Koschützki, Dirk; Junker, Björn H; Schwender, Jörg; Schreiber, Falk

    2010-08-01

    Metabolic reactions are fundamental to living organisms, and a large number of reactions simultaneously occur at a given time in living cells transforming diverse metabolites into each other. There has been an ongoing debate on how to classify metabolites with respect to their importance for metabolic performance, usually based on the analysis of topological properties of genome scale metabolic networks. However, none of these studies have accounted quantitatively for flux in metabolic networks, thus lacking an important component of a cell's biochemistry. We therefore analyzed a genome scale metabolic network of Escherichia coli by comparing growth under 19 different growth conditions, using flux balance analysis and weighted network centrality investigation. With this novel concept of flux centrality we generated metabolite rankings for each particular growth condition. In contrast to the results of conventional analysis of genome scale metabolic networks, different metabolites were top-ranking dependent on the growth condition. At the same time, several metabolites were consistently among the high ranking ones. Those are associated with pathways that have been described by biochemists as the most central part of metabolism, such as glycolysis, tricarboxylic acid cycle and pentose phosphate pathway. The values for the average path length of the analyzed metabolite networks were between 10.5 and 12.6, supporting recent findings that the metabolic network of E. coli is not a small-world network. PMID:20471988

  10. Cognitive Networking With Regards to NASA's Space Communication and Navigation Program

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Paulsen, Phillip E.; Vaden, Karl R.; Ponchak, Denise S.

    2013-01-01

    This report describes cognitive networking (CN) and its application to NASA's Space Communication and Networking (SCaN) Program. This report clarifies the terminology and framework of CN and provides some examples of cognitive systems. It then provides a methodology for developing and deploying CN techniques and technologies. Finally, the report attempts to answer specific questions regarding how CN could benefit SCaN. It also describes SCaN's current and target networks and proposes places where cognition could be deployed.

  11. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

    Hardin, D. M.; Hawkins, L.; He, M.; Ebersole, S.

    2010-12-01

    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 SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. 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 Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  12. Social Networks Analysis and Participation in Learning Environments to Digital Inclusion Based on Large-Scale Distance Education

    ERIC Educational Resources Information Center

    da Silva, Aleksandra do Socorro; de Brito, Silvana Rossy; Martins, Dalton Lopes; Vijaykumar, Nandamudi Lankalapalli; da Rocha, Cláudio Alex Jorge; Costa, João Crisóstomo Weyl Albuquerque; Francês, Carlos Renato Lisboa

    2014-01-01

    Evaluating and monitoring large-scale distance learning programs require different techniques, systems, and analysis methods. This work presents challenges in evaluating and monitoring digital inclusion training programs, considering the aspects inherent in large-scale distance training, and reports an approach based on network and distance…

  13. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics.

    PubMed

    Prescott, Aaron M; McCollough, Forest W; Eldreth, Bryan L; Binder, Brad M; Abel, Steven M

    2016-01-01

    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. 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 underlying ethylene

  14. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    PubMed Central

    Prescott, Aaron M.; McCollough, Forest W.; Eldreth, Bryan L.; Binder, Brad M.; Abel, Steven M.

    2016-01-01

    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. 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 underlying ethylene

  15. Artificial neural networks for small dataset analysis.

    PubMed

    Pasini, Antonello

    2015-05-01

    Artificial neural networks (ANNs) are usually considered as tools which can help to analyze cause-effect relationships in complex systems within a big-data framework. On the other hand, health sciences undergo complexity more than any other scientific discipline, and in this field large datasets are seldom available. In this situation, I show how a particular neural network tool, which is able to handle small datasets of experimental or observational data, can help in identifying the main causal factors leading to changes in some variable which summarizes the behaviour of a complex system, for instance the onset of a disease. A detailed description of the neural network tool is given and its application to a specific case study is shown. Recommendations for a correct use of this tool are also supplied. PMID:26101654

  16. Multilayer Network Analysis of Nuclear Reactions.

    PubMed

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, (4)He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  17. Multilayer Network Analysis of Nuclear Reactions

    PubMed Central

    Zhu, Liang; Ma, Yu-Gang; Chen, Qu; Han, Ding-Ding

    2016-01-01

    The nuclear reaction network is usually studied via precise calculation of differential equation sets, and much research interest has been focused on the characteristics of nuclides, such as half-life and size limit. In this paper, however, we adopt the methods from both multilayer and reaction networks, and obtain a distinctive view by mapping all the nuclear reactions in JINA REACLIB database into a directed network with 4 layers: neutron, proton, 4He and the remainder. The layer names correspond to reaction types decided by the currency particles consumed. This combined approach reveals that, in the remainder layer, the β-stability has high correlation with node degree difference and overlapping coefficient. Moreover, when reaction rates are considered as node strength, we find that, at lower temperatures, nuclide half-life scales reciprocally with its out-strength. The connection between physical properties and topological characteristics may help to explore the boundary of the nuclide chart. PMID:27558995

  18. Artificial neural networks for small dataset analysis

    PubMed Central

    2015-01-01

    Artificial neural networks (ANNs) are usually considered as tools which can help to analyze cause-effect relationships in complex systems within a big-data framework. On the other hand, health sciences undergo complexity more than any other scientific discipline, and in this field large datasets are seldom available. In this situation, I show how a particular neural network tool, which is able to handle small datasets of experimental or observational data, can help in identifying the main causal factors leading to changes in some variable which summarizes the behaviour of a complex system, for instance the onset of a disease. A detailed description of the neural network tool is given and its application to a specific case study is shown. Recommendations for a correct use of this tool are also supplied. PMID:26101654

  19. Analysis of remote synchronization in complex networks

    NASA Astrophysics Data System (ADS)

    Gambuzza, Lucia Valentina; Cardillo, Alessio; Fiasconaro, Alessandro; Fortuna, Luigi; Gómez-Gardeñes, Jesus; Frasca, Mattia

    2013-12-01

    A novel regime of synchronization, called remote synchronization, where the peripheral nodes form a phase synchronized cluster not including the hub, was recently observed in star motifs [Bergner et al., Phys. Rev. E 85, 026208 (2012)]. We show the existence of a more general dynamical state of remote synchronization in arbitrary networks of coupled oscillators. This state is characterized by the synchronization of pairs of nodes that are not directly connected via a physical link or any sequence of synchronized nodes. This phenomenon is almost negligible in networks of phase oscillators as its underlying mechanism is the modulation of the amplitude of those intermediary nodes between the remotely synchronized units. Our findings thus show the ubiquity and robustness of these states and bridge the gap from their recent observation in simple toy graphs to complex networks.

  20. Performance Analysis of IIUM Wireless Campus Network

    NASA Astrophysics Data System (ADS)

    Abd Latif, Suhaimi; Masud, Mosharrof H.; Anwar, Farhat

    2013-12-01

    International Islamic University Malaysia (IIUM) is one of the leading universities in the world in terms of quality of education that has been achieved due to providing numerous facilities including wireless services to every enrolled student. The quality of this wireless service is controlled and monitored by Information Technology Division (ITD), an ISO standardized organization under the university. This paper aims to investigate the constraints of wireless campus network of IIUM. It evaluates the performance of the IIUM wireless campus network in terms of delay, throughput and jitter. QualNet 5.2 simulator tool has employed to measure these performances of IIUM wireless campus network. The observation from the simulation result could be one of the influencing factors in improving wireless services for ITD and further improvement.

  1. 77 FR 65581 - Verizon Business Networks Services, Inc., Senior Analyst, Service Program Delivery (SA-SPD...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-29

    ... Employment and Training Administration Verizon Business Networks Services, Inc., Senior Analyst, Service Program Delivery (SA-SPD), Including Workers Whose Wages Were Paid Under MCI Communication Services, Inc..., 2012, applicable to workers and former workers of Verizon Business Network Services, Inc.,...

  2. The Structure and Quality of Social Network Support among Mental Health Consumers of Clubhouse Programs

    ERIC Educational Resources Information Center

    Pernice-Duca, Francesca M.

    2008-01-01

    This study explored the structure and quality of social network support among a group of adult consumers of community-based mental health programs known as "clubhouses". The structure and quality of social network support was also examined by diagnosis, specifically between consumers living with and without schizophrenia. The study involved a…

  3. Navigating Social Networking and Social Media in School Psychology: Ethical and Professional Considerations in Training Programs

    ERIC Educational Resources Information Center

    Pham, Andy V.

    2014-01-01

    Social networking and social media have undoubtedly proliferated within the past decade, allowing widespread communication and dissemination of user-generated content and information. Some psychology graduate programs, including school psychology, have started to embrace social networking and media for instructional and training purposes; however,…

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

    NASA Astrophysics Data System (ADS)

    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

  5. Real-time physiological monitoring with distributed networks of sensors and object-oriented programming techniques

    NASA Astrophysics Data System (ADS)

    Wiesmann, William P.; Pranger, L. Alex; Bogucki, Mary S.

    1998-05-01

    Remote monitoring of physiologic data from individual high- risk workers distributed over time and space is a considerable challenge. This is often due to an inadequate capability to accurately integrate large amounts of data into usable information in real time. In this report, we have used the vertical and horizontal organization of the 'fireground' as a framework to design a distributed network of sensors. In this system, sensor output is linked through a hierarchical object oriented programing process to accurately interpret physiological data, incorporate these data into a synchronous model and relay processed data, trends and predictions to members of the fire incident command structure. There are several unique aspects to this approach. The first includes a process to account for variability in vital parameter values for each individual's normal physiologic response by including an adaptive network in each data process. This information is used by the model in an iterative process to baseline a 'normal' physiologic response to a given stress for each individual and to detect deviations that indicate dysfunction or a significant insult. The second unique capability of the system orders the information for each user including the subject, local company officers, medical personnel and the incident commanders. Information can be retrieved and used for training exercises and after action analysis. Finally this system can easily be adapted to existing communication and processing links along with incorporating the best parts of current models through the use of object oriented programming techniques. These modern software techniques are well suited to handling multiple data processes independently over time in a distributed network.

  6. Energy Analysis Program, 1993 annual report

    SciTech Connect

    Not Available

    1994-06-01

    With the new federal Administration in place, we have observed increasing attention in the areas of research and analysis that have been central to our interests. Energy efficiency is once again a very high priority in the national agenda. This increased emphasis on energy efficiency was already apparent prior to the national elections in the contents of the National Energy Policy Act (EPACT), passed by Congress in 1992. The Climate Change Action Plan, released by the White House in October 1993, strengthens the federal government`s leadership role in the design and implementation of energy-efficiency programs. Budget submissions show energy efficiency and renewable energy programs among the relatively small number of discretionary programs at the federal level that are expected to receive large percentage increases.

  7. DOE-2 Building Energy Analysis Program

    SciTech Connect

    Curtis, R.B.; Birdsall, B.; Buhl, W.F.; Erdem, E.; Eto, J.; Hirsch, J.J.; Olson, K.H.; Winkelmann, F.C.

    1984-04-01

    The DOE-2 Building Energy Analysis Program was designed to allow engineers and architects to perform design studies of whole-building energy use under actual weather conditions. Its development was guided by several objectives: (1) that the description of the building entered by the user be readily understood by non-computer scientists, (2) that, when available, the calculations be based upon well established algorithms, (3) that it permit the simulation of commonly available heating, ventilating, and air-conditioning (HVAC) equipment, (4) that the computer costs of the program be minimal, and (5) that the predicted energy use of a building be acceptably close to measured values. These objectives have been met. An overview of the program upon completion of the DOE-2.1C edition is given.

  8. A recurrent neural network with exponential convergence for solving convex quadratic program and related linear piecewise equations.

    PubMed

    Xia, Youshen; Feng, Gang; Wang, Jun

    2004-09-01

    This paper presents a recurrent neural network for solving strict convex quadratic programming problems and related linear piecewise equations. Compared with the existing neural networks for quadratic program, the proposed neural network has a one-layer structure with a low model complexity. Moreover, the proposed neural network is shown to have a finite-time convergence and exponential convergence. Illustrative examples further show the good performance of the proposed neural network in real-time applications. PMID:15312842

  9. Network Analysis with the Enron Email Corpus

    ERIC Educational Resources Information Center

    Hardin, J. S.; Sarkis, G.; URC, P. .

    2015-01-01

    We use the Enron email corpus to study relationships in a network by applying six different measures of centrality. Our results came out of an in-semester undergraduate research seminar. The Enron corpus is well suited to statistical analyses at all levels of undergraduate education. Through this article's focus on centrality, students can explore…

  10. Tractable Analysis for Large Social Networks

    ERIC Educational Resources Information Center

    Zhang, Bin

    2012-01-01

    Social scientists usually are more interested in consumers' dichotomous choice, such as purchase a product or not, adopt a technology or not, etc. However, up to date, there is nearly no model can help us solve the problem of multi-network effects comparison with a dichotomous dependent variable. Furthermore, the study of multi-network…

  11. Using Citation Network Analysis in Educational Technology

    ERIC Educational Resources Information Center

    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…

  12. Maize metabolic network construction and transcriptome analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A framework for understanding the synthesis and catalysis of metabolites and other biochemicals by proteins is crucial for unraveling the physiology of cells. To create such a framework for Zea mays ssp. mays (maize), we developed MaizeCyc a metabolic network of enzyme catalysts, proteins, carbohydr...

  13. Sea water level forecasting using genetic programming and comparing the performance with Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Ali Ghorbani, Mohammad; Khatibi, Rahman; Aytek, Ali; Makarynskyy, Oleg; Shiri, Jalal

    2010-05-01

    Water level forecasting at various time intervals using records of past time series is of importance in water resources engineering and management. In the last 20 years, emerging approaches over the conventional harmonic analysis techniques are based on using Genetic Programming (GP) and Artificial Neural Networks (ANNs). In the present study, the GP is used to forecast sea level variations, three time steps ahead, for a set of time intervals comprising 12 h, 24 h, 5 day and 10 day time intervals using observed sea levels. The measurements from a single tide gauge at Hillarys Boat Harbor, Western Australia, were used to train and validate the employed GP for the period from December 1991 to December 2002. Statistical parameters, namely, the root mean square error, correlation coefficient and scatter index, are used to measure their performances. These were compared with a corresponding set of published results using an Artificial Neural Network model. The results show that both these artificial intelligence methodologies perform satisfactorily and may be considered as alternatives to the harmonic analysis.

  14. Genomic analysis of regulatory network dynamics reveals large topological changes

    NASA Astrophysics Data System (ADS)

    Luscombe, Nicholas M.; Madan Babu, M.; Yu, Haiyuan; Snyder, Michael; Teichmann, Sarah A.; Gerstein, Mark

    2004-09-01

    Network analysis has been applied widely, providing a unifying language to describe disparate systems ranging from social interactions to power grids. It has recently been used in molecular biology, but so far the resulting networks have only been analysed statically. Here we present the dynamics of a biological network on a genomic scale, by integrating transcriptional regulatory information and gene-expression data for multiple conditions in Saccharomyces cerevisiae. We develop an approach for the statistical analysis of network dynamics, called SANDY, combining well-known global topological measures, local motifs and newly derived statistics. We uncover large changes in underlying network architecture that are unexpected given current viewpoints and random simulations. In response to diverse stimuli, transcription factors alter their interactions to varying degrees, thereby rewiring the network. A few transcription factors serve as permanent hubs, but most act transiently only during certain conditions. By studying sub-network structures, we show that environmental responses facilitate fast signal propagation (for example, with short regulatory cascades), whereas the cell cycle and sporulation direct temporal progression through multiple stages (for example, with highly inter-connected transcription factors). Indeed, to drive the latter processes forward, phase-specific transcription factors inter-regulate serially, and ubiquitously active transcription factors layer above them in a two-tiered hierarchy. We anticipate that many of the concepts presented here-particularly the large-scale topological changes and hub transience-will apply to other biological networks, including complex sub-systems in higher eukaryotes.

  15. Efficient network meta-analysis: a confidence distribution approach*

    PubMed Central

    Yang, Guang; Liu, Dungang; Liu, Regina Y.; Xie, Minge; Hoaglin, David C.

    2014-01-01

    Summary Network meta-analysis synthesizes several studies of multiple treatment comparisons to simultaneously provide inference for all treatments in the network. It can often strengthen inference on pairwise comparisons by borrowing evidence from other comparisons in the network. Current network meta-analysis approaches are derived from either conventional pairwise meta-analysis or hierarchical Bayesian methods. This paper introduces a new approach for network meta-analysis by combining confidence distributions (CDs). Instead of combining point estimators from individual studies in the conventional approach, the new approach combines CDs which contain richer information than point estimators and thus achieves greater efficiency in its inference. The proposed CD approach can e ciently integrate all studies in the network and provide inference for all treatments even when individual studies contain only comparisons of subsets of the treatments. Through numerical studies with real and simulated data sets, the proposed approach is shown to outperform or at least equal the traditional pairwise meta-analysis and a commonly used Bayesian hierarchical model. Although the Bayesian approach may yield comparable results with a suitably chosen prior, it is highly sensitive to the choice of priors (especially the prior of the between-trial covariance structure), which is often subjective. The CD approach is a general frequentist approach and is prior-free. Moreover, it can always provide a proper inference for all the treatment effects regardless of the between-trial covariance structure. PMID:25067933

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

    NASA Astrophysics Data System (ADS)

    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.

  17. Sensitivity to Excluding Treatments in Network Meta-analysis.

    PubMed

    Lin, Lifeng; Chu, Haitao; Hodges, James S

    2016-07-01

    Network meta-analysis of randomized controlled trials is increasingly used to combine both direct evidence comparing treatments within trials and indirect evidence comparing treatments across different trials. When the outcome is binary, the commonly used contrast-based network meta-analysis methods focus on relative treatment effects such as odds ratios comparing two treatments. As shown in a recent report, when using contrast-based network meta-analysis, the impact of excluding a treatment in the network can be substantial, suggesting a methodological limitation. In addition, relative treatment effects are sometimes not sufficient for patients to make decisions. For example, it can be challenging for patients to trade off efficacy and safety for two drugs if they only know the relative effects, not the absolute effects. A recently proposed arm-based network meta-analysis, based on a missing-data framework, provides an alternative approach. It focuses on estimating population-averaged treatment-specific absolute effects. This article examines the influence of treatment exclusion empirically using 14 published network meta-analyses, for both arm- and contrast-based approaches. The difference between these two approaches is substantial, and it is almost entirely due to single-arm trials. When a treatment is removed from a contrast-based network meta-analysis, it is necessary to exclude other treatments in two-arm studies that investigated the excluded treatment; such exclusions are not necessary in arm-based network meta-analysis, leading to substantial gain in performance. PMID:27007642

  18. Analysis and logical modeling of biological signaling transduction networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  19. Major component analysis of dynamic networks of physiologic organ interactions

    NASA Astrophysics Data System (ADS)

    Liu, Kang K. L.; Bartsch, Ronny P.; Ma, Qianli D. Y.; Ivanov, Plamen Ch

    2015-09-01

    The human organism is a complex network of interconnected organ systems, where the behavior of one system affects the dynamics of other systems. Identifying and quantifying dynamical networks of diverse physiologic systems under varied conditions is a challenge due to the complexity in the output dynamics of the individual systems and the transient and nonlinear characteristics of their coupling. We introduce a novel computational method based on the concept of time delay stability and major component analysis to investigate how organ systems interact as a network to coordinate their functions. We analyze a large database of continuously recorded multi-channel physiologic signals from healthy young subjects during night-time sleep. We identify a network of dynamic interactions between key physiologic systems in the human organism. Further, we find that each physiologic state is characterized by a distinct network structure with different relative contribution from individual organ systems to the global network dynamics. Specifically, we observe a gradual decrease in the strength of coupling of heart and respiration to the rest of the network with transition from wake to deep sleep, and in contrast, an increased relative contribution to network dynamics from chin and leg muscle tone and eye movement, demonstrating a robust association between network topology and physiologic function.

  20. Monolithic ceramic analysis using the SCARE program

    NASA Technical Reports Server (NTRS)

    Manderscheid, Jane M.

    1988-01-01

    The Structural Ceramics Analysis and Reliability Evaluation (SCARE) computer program calculates the fast fracture reliability of monolithic ceramic components. The code is a post-processor to the MSC/NASTRAN general purpose finite element program. The SCARE program automatically accepts the MSC/NASTRAN output necessary to compute reliability. This includes element stresses, temperatures, volumes, and areas. The SCARE program computes two-parameter Weibull strength distributions from input fracture data for both volume and surface flaws. The distributions can then be used to calculate the reliability of geometrically complex components subjected to multiaxial stress states. Several fracture criteria and flaw types are available for selection by the user, including out-of-plane crack extension theories. The theoretical basis for the reliability calculations was proposed by Batdorf. These models combine linear elastic fracture mechanics (LEFM) with Weibull statistics to provide a mechanistic failure criterion. Other fracture theories included in SCARE are the normal stress averaging technique and the principle of independent action. The objective of this presentation is to summarize these theories, including their limitations and advantages, and to provide a general description of the SCARE program, along with example problems.

  1. Analysis of data from ISO CORRAG program

    SciTech Connect

    Dean, S.W.; Reiser, D.B.

    1998-12-31

    An analysis of the flat panel corrosion rates from the one-year exposures in the ISO CORRAG program has been carried out to determine the extent of correlation between the four metals used in this study. The corrosion rates all showed highly significant correlations when compared on a logarithmic basis. This conversion was necessary to eliminate bias from the correlation of standard deviation with average values. Residual analysis showed that times of wetness accelerated steel, zinc, and copper corrosion more than aluminum. Sulfur dioxide accelerated zinc more than copper, and chloride accelerated steel more than zinc and aluminum, and copper more than aluminum.

  2. Computing single step operators of logic programming in radial basis function neural networks

    NASA Astrophysics Data System (ADS)

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-07-01

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  3. Computing single step operators of logic programming in radial basis function neural networks

    SciTech Connect

    Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

    2014-07-10

    Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

  4. Vulnerability analysis for complex networks using aggressive abstraction.

    SciTech Connect

    Colbaugh, Richard; Glass, Kristin L.

    2010-06-01

    Large, complex networks are ubiquitous in nature and society, and there is great interest in developing rigorous, scalable methods for identifying and characterizing their vulnerabilities. This paper presents an approach for analyzing the dynamics of complex networks in which the network of interest is first abstracted to a much simpler, but mathematically equivalent, representation, the required analysis is performed on 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 vulnerability-preserving, finite state abstractions, and develop efficient algorithms for computing these abstractions. We then propose a vulnerability analysis methodology which combines these finite state abstractions with formal analytics from theoretical computer science to yield a comprehensive vulnerability analysis process for networks of realworld scale and complexity. The potential of the proposed approach is illustrated with a case study involving a realistic electric power grid model and also with brief discussions of biological and social network examples.

  5. Comparative analysis of differential network modularity in tissue specific normal and cancer protein interaction networks

    PubMed Central

    2013-01-01

    Background Large scale understanding of complex and dynamic alterations in cellular and subcellular levels during cancer in contrast to normal condition has facilitated the emergence of sophisticated systemic approaches like network biology in recent times. As most biological networks show modular properties, the analysis of differential modularity between normal and cancer protein interaction networks can be a good way to understand cancer more significantly. Two aspects of biological network modularity e.g. detection of molecular complexes (potential modules or clusters) and identification of crucial nodes forming the overlapping modules have been considered in this regard. Methods In the current study, the computational analysis of previously published protein interaction networks (PINs) has been conducted to identify the molecular complexes and crucial nodes of the networks. Protein molecules involved in ten major cancer signal transduction pathways were used to construct the networks based on expression data of five tissues e.g. bone, breast, colon, kidney and liver in both normal and cancer conditions. MCODE (molecular complex detection) and ModuLand methods have been used to identify the molecular complexes and crucial nodes of the networks respectively. Results In case of all tissues, cancer PINs show higher level of clustering (formation of molecular complexes) than the normal ones. In contrast, lower level modular overlapping is found in cancer PINs than the normal ones. Thus a proposition can be made regarding the formation of some giant nodes in the cancer networks with very high degree and resulting in reduced overlapping among the network modules though the predicted molecular complex numbers are higher in cancer conditions. Conclusion The study predicts some major molecular complexes that might act as the important regulators in cancer progression. The crucial nodes identified in this study can be potential drug targets to combat cancer. PMID

  6. Cardiac phase: Amplitude analysis using macro programming

    SciTech Connect

    Logan, K.W.; Hickey, K.A.

    1981-11-01

    The analysis of EKG gated radionuclide cardiac imaging data with Fourier amplitude and phase images is becoming a valuable clinical technique, demonstrating location, size, and severity of regional ventricular abnormalities. Not all commercially available nuclear medicine computer systems offer software for phase and amplitude analysis; however, many systems do have the capability of linear image arithmetic using simple macro commands which can easily be sequenced into stored macro-strings or programs. Using simple but accurate series approximations for the Fourier operations, macro programs have been written for a Digital Equipment Corporation Gamma-11 system to obtain phase and amplitude images from routine gated cardiac studies. In addition, dynamic cine-mode presentation of the onset of mechanical systole is generated from the phase data, using only a second set of macro programs. This approach is easily adapted to different data acquisition protocols, and can be used on any system with macro commands for image arithmetic. Key words: Fourier analysis, cardiac cycle, gated blood pool imaging, amplitude image, phase image

  7. Network portal: a database for storage, analysis and visualization of biological networks

    PubMed Central

    Turkarslan, Serdar; Wurtmann, Elisabeth J.; Wu, Wei-Ju; Jiang, Ning; Bare, J. Christopher; Foley, Karen; Reiss, David J.; Novichkov, Pavel; Baliga, Nitin S.

    2014-01-01

    The ease of generating high-throughput data has enabled investigations into organismal complexity at the systems level through the inference of networks of interactions among the various cellular components (genes, RNAs, proteins and metabolites). The wider scientific community, however, currently has limited access to tools for network inference, visualization and analysis because these tasks often require advanced computational knowledge and expensive computing resources. We have designed the network portal (http://networks.systemsbiology.net) to serve as a modular database for the integration of user uploaded and public data, with inference algorithms and tools for the storage, visualization and analysis of biological networks. The portal is fully integrated into the Gaggle framework to seamlessly exchange data with desktop and web applications and to allow the user to create, save and modify workspaces, and it includes social networking capabilities for collaborative projects. While the current release of the database contains networks for 13 prokaryotic organisms from diverse phylogenetic clades (4678 co-regulated gene modules, 3466 regulators and 9291 cis-regulatory motifs), it will be rapidly populated with prokaryotic and eukaryotic organisms as relevant data become available in public repositories and through user input. The modular architecture, simple data formats and open API support community development of the portal. PMID:24271392

  8. Network Configuration Analysis for Formation Flying Satellites

    NASA Technical Reports Server (NTRS)

    Knoblock, Eric J.; Wallett, Thomas M.; Konangi, Vijay K.; Bhasin, Kul B.

    2001-01-01

    The performance of two networks to support autonomous multi-spacecraft formation flying systems is presented. Both systems are comprised of a ten-satellite formation, with one of the satellites designated as the central or 'mother ship.' All data is routed through the mother ship to the terrestrial network. The first system uses a TCP/EP over ATM protocol architecture within the formation, and the second system uses the IEEE 802.11 protocol architecture within the formation. The simulations consist of file transfers using either the File Transfer Protocol (FTP) or the Simple Automatic File Exchange (SAFE) Protocol. The results compare the IP queuing delay, IP queue size and IP processing delay at the mother ship as well as end-to-end delay for both systems. In all cases, using IEEE 802.11 within the formation yields less delay. Also, the throughput exhibited by SAFE is better than FTP.

  9. Neurocontroller analysis via evolutionary network minimization.

    PubMed

    Ganon, Zohar; Keinan, Alon; Ruppin, Eytan

    2006-01-01

    This study presents a new evolutionary network minimization (ENM) algorithm. Neurocontroller minimization is beneficial for finding small parsimonious networks that permit a better understanding of their workings. The ENM algorithm is specifically geared to an evolutionary agents setup, as it does not require any explicit supervised training error, and is very easily incorporated in current evolutionary algorithms. ENM is based on a standard genetic algorithm with an additional step during reproduction in which synaptic connections are irreversibly eliminated. It receives as input a successfully evolved neurocontroller and aims to output a pruned neurocontroller, while maintaining the original fitness level. The small neurocontrollers produced by ENM provide upper bounds on the neurocontroller size needed to perform a given task successfully, and can provide for more effcient hardware implementations. PMID:16859448

  10. Complex networks analysis of obstructive nephropathy data

    NASA Astrophysics Data System (ADS)

    Zanin, M.; Boccaletti, S.

    2011-09-01

    Congenital obstructive nephropathy (ON) is one of the most frequent and complex diseases affecting children, characterized by an abnormal flux of the urine, due to a partial or complete obstruction of the urinary tract; as a consequence, urine may accumulate in the kidney and disturb the normal operation of the organ. Despite important advances, pathological mechanisms are not yet fully understood. In this contribution, the topology of complex networks, based on vectors of features of control and ON subjects, is related with the severity of the pathology. Nodes in these networks represent genetic and metabolic profiles, while connections between them indicate an abnormal relation between their expressions. Resulting topologies allow discriminating ON subjects and detecting which genetic or metabolic elements are responsible for the malfunction.

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

    PubMed Central

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

    2016-01-01

    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. PMID:27548197

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

    PubMed

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

    2016-01-01

    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. PMID:27548197

  13. Statistical Models and Methods for Network Meta-Analysis.

    PubMed

    Madden, L V; Piepho, H-P; Paul, P A

    2016-08-01

    Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS. PMID:27111798

  14. Qualitative Analysis of Commercial Social Network Profiles

    NASA Astrophysics Data System (ADS)

    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.

  15. 7 CFR 1700.32 - Program Accounting and Regulatory Analysis.

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 7 Agriculture 11 2010-01-01 2010-01-01 false Program Accounting and Regulatory Analysis. 1700.32... Accounting and Regulatory Analysis. RUS, through Program Accounting and Regulatory Analysis, monitors and... Assistant Administrator, Program Accounting and Regulatory Analysis, directs and coordinates...

  16. Analysis of opinion spreading in homogeneous networks with signed relationships

    NASA Astrophysics Data System (ADS)

    Fan, Pengyi; Wang, Hui; Li, Pei; Li, Wei; Jiang, Zhihong

    2012-08-01

    Recently, significant attention has been devoted to opinion dynamics in social networks, in which all the relationships between individuals are assumed as positive ones (i.e. friend, altruism or trust). However, many realistic social networks include negative relationships (i.e. enemy or distrust) as well as positive ones. In order to find the dynamical behavior of opinion spreading in signed networks, we propose a model taking into account the impacts of positive and negative relationships. Based on this model, we analyze the dynamical process and provide a detailed mathematical analysis for identifying the threshold of opinion spreading in homogeneous networks with signed relationships. By performing numerical simulations for the threshold in three different signed networks, we find that the theoretical and numerical results are in good agreement, confirming the correctness of our exact solution.

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

    NASA Astrophysics Data System (ADS)

    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.

  18. Random matrix analysis of localization properties of gene coexpression network

    NASA Astrophysics Data System (ADS)

    Jalan, Sarika; Solymosi, Norbert; Vattay, Gábor; Li, Baowen

    2010-04-01

    We analyze gene coexpression network under the random matrix theory framework. The nearest-neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral rigidity test follows random matrix prediction for a certain range and deviates afterwards. Eigenvector analysis of the network using inverse participation ratio suggests that the statistics of bulk of the eigenvalues of network is consistent with those of the real symmetric random matrix, whereas few eigenvalues are localized. Based on these IPR calculations, we can divide eigenvalues in three sets: (a) The nondegenerate part that follows RMT. (b) The nondegenerate part, at both ends and at intermediate eigenvalues, which deviates from RMT and expected to contain information about important nodes in the network. (c) The degenerate part with zero eigenvalue, which fluctuates around RMT-predicted value. We identify nodes corresponding to the dominant modes of the corresponding eigenvectors and analyze their structural properties.

  19. Radionuclide migration analysis using a discrete fracture network model

    SciTech Connect

    Ijiri, Y.; Sawada, A.; Webb, E.K.; Watari, S.; Hatanaka, K.; Uchida, M.; Ishiguro, K.; Umeki, H.; Dershowitz, W.S.

    1999-07-01

    This paper describes an approach for assessing the geosphere performance of nuclear waste disposal in fractured rock. In this approach, a three-dimensional heterogeneous channel-network model is constructed using a stochastic discrete fracture network (DFN) code. Radionuclide migration in the channel-network model is solved using the Laplace transform Galerkin finite element method, taking into account advection-dispersion in a fracture network, matrix diffusion, sorption in the rock matrix as well as radioactive chain decay. Preliminary radionuclide migration analysis was performed for fifty realizations of a synthetic block-scale DFN model. The total radionuclide release from all packages in the repository was estimated from the statistics of the results of fifty realizations under the hypothesis of ergodicity. The interpretation of the result of the three-dimensional network model by a combination of simpler one-dimensional parallel plate models is also discussed.

  20. A systematic review protocol: social network analysis of tobacco use

    PubMed Central

    2014-01-01

    Background Tobacco use is the single most preventable cause of death in the world. Evidence indicates that behaviours such as tobacco use can influence social networks, and that social network structures can influence behaviours. Social network analysis provides a set of analytic tools to undertake methodical analysis of social networks. We will undertake a systematic review to provide a comprehensive synthesis of the literature regarding social network analysis and tobacco use. The review will answer the following research questions: among participants who use tobacco, does social network structure/position influence tobacco use? Does tobacco use influence peer selection? Does peer selection influence tobacco use? Methods We will follow the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines and search the following databases for relevant articles: CINAHL (Cumulative Index to Nursing and Allied Health Literature); Informit Health Collection; PsycINFO; PubMed/MEDLINE; Scopus/Embase; Web of Science; and the Wiley Online Library. Keywords include tobacco; smoking; smokeless; cigarettes; cigar and ‘social network’ and reference lists of included articles will be hand searched. Studies will be included that provide descriptions of social network analysis of tobacco use. Qualitative, quantitative and mixed method data that meets the inclusion criteria for the review, including methodological rigour, credibility and quality standards, will be synthesized using narrative synthesis. Results will be presented using outcome statistics that address each of the research questions. Discussion This systematic review will provide a timely evidence base on the role of social network analysis of tobacco use, forming a basis for future research, policy and practice in this area. This systematic review will synthesise the evidence, supporting the hypothesis that social network structures can influence tobacco use. This will also include exploring

  1. Analysis of torsional oscillations using an artificial neural network

    SciTech Connect

    Hsu, Y.Y.; Jeng, L,H. )

    1992-12-01

    In this paper, a novel approach using an artificial neural network (ANN) is proposed for the analysis of torsional oscillations in a power system. In the developed artificial neural network, those system variables such as generator loadings and capacitor compensation ratio which have major impacts on the damping characteristics of torsional oscillatio modes are employed as the inputs. The outputs of the neural net provide the desired eigenvalues for torsional modes. Once the connection weights of the neural network have been learned using a set of training data derived off-line, the neural network can be applied to torsional analysis in real-time situations. To demonstrate the effectiveness of the proposed neural net, torsional analysis is performed on the IEEE First Benchmark Model. It is concluded from the test results that accurate assessment of the torsional mode eigenvalues can be achieved by the neural network in a very efficient manner. Thereofore, the proposed neural network approach can serve as a valuable tool to system operators in conducting SSR analysis in operational planning.

  2. Protein structural information derived from NMR chemical shift with the neural network program TALOS-N.

    PubMed

    Shen, Yang; Bax, Ad

    2015-01-01

    Chemical shifts are obtained at the first stage of any protein structural study by NMR spectroscopy. Chemical shifts are known to be impacted by a wide range of structural factors, and the artificial neural network based TALOS-N program has been trained to extract backbone and side-chain torsion angles from (1)H, (15)N, and (13)C shifts. The program is quite robust and typically yields backbone torsion angles for more than 90 % of the residues and side-chain χ 1 rotamer information for about half of these, in addition to reliably predicting secondary structure. The use of TALOS-N is illustrated for the protein DinI, and torsion angles obtained by TALOS-N analysis from the measured chemical shifts of its backbone and (13)C(β) nuclei are compared to those seen in a prior, experimentally determined structure. The program is also particularly useful for generating torsion angle restraints, which then can be used during standard NMR protein structure calculations. PMID:25502373

  3. Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis.

    PubMed

    Zhang, Ruibin; Jiang, Guihua; Tian, Junzhang; Qiu, Yingwei; Wen, Xue; Zalesky, Andrew; Li, Meng; Ma, Xiaofen; Wang, Junjing; Li, Shumei; Wang, Tianyue; Li, Changhong; Huang, Ruiwang

    2016-05-01

    Neuroimaging studies suggested that drug addiction is linked to abnormal brain functional connectivity. However, little is known about the alteration of brain white matter (WM) connectivity in addictive drug users and nearly no study has been performed to examine the alterations of brain WM connectivity in heroin-dependent individuals (HDIs). Diffusion tensor imaging (DTI) offers a comprehensive technique to map the whole brain WM connectivity in vivo. In this study, we acquired DTI datasets from 20 HDIs and 18 healthy controls and constructed their brain WM structural networks using a deterministic fibre tracking approach. Using graph theoretical analysis, we explored the global and nodal topological parameters of brain network for both groups and adopted a network-based statistic (NBS) approach to assess between-group differences in inter-regional WM connections. Statistical analysis indicated the global efficiency and network strength were significantly increased, but the characteristic path length was significantly decreased in the HDIs compared with the controls. We also found that in the HDIs, the nodal efficiency was significantly increased in the left prefrontal cortex, bilateral orbital frontal cortices and left anterior cingulate gyrus. Moreover, the NBS analysis revealed that in the HDIs, the significant increased connections were located in the paralimbic, orbitofrontal, prefrontal and temporal regions. Our results may reflect the disruption of whole brain WM structural networks in the HDIs. Our findings suggest that mapping brain WM structural network may be helpful for better understanding the neuromechanism of heroin addiction. PMID:25740690

  4. Program Excellence Network of the Academy of Human Resource Development: Its Purpose and Activities

    ERIC Educational Resources Information Center

    Ruona, Wendy E. A.

    2009-01-01

    This article features the Program Excellence Network (PEN) of the Academy of Human Resource Development (AHRD) which was established in September 2006 in response to a proposal brought forward by the author. The mission of PEN is to strengthen HRD academic programs and promote excellence in teaching HRD. PEN provides a forum for its members to…

  5. Commercial Network Television: Strategies for Programming and the Content of Prime Time TV, 1976-1979.

    ERIC Educational Resources Information Center

    Austin, Bruce A.

    The 1976-79 schedules of the three major television networks were analyzed to determine what strategies were used to organize prime time schedules and what types of programs appeared during prime time viewing periods. Five essential programing strategies were identified: fraction of selection (cost versus reward), lowest common denominator (wide…

  6. Administrative and Organizational Variables Affecting the Development of a Teacher-To-Teacher Network Program.

    ERIC Educational Resources Information Center

    Dempsey, Ellen

    This paper examines the strategies involved in planning, organizing, developing, administering, evaluating, and providing materials for replication for a teacher-to-teacher network program. The data for this paper was collected as part of IMPACT II, a program designed to identify, support, document, and disseminate successful classroom-based…

  7. Adult Education. Proven Exemplary Educational Programs and Practices: A Collection from the National Diffusion Network (NDN).

    ERIC Educational Resources Information Center

    Michigan State Board of Education, Lansing.

    This booklet provides descriptions of 16 adult education programs that have been validated as successful by the Joint Dissemination Review Panel (JDRP), U.S. Department of Education and that are being promoted by the National Diffusion Network (NDN). Although the programs were developed by individual school districts in response to local needs,…

  8. LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

    SciTech Connect

    Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.; Akyol, Bora A.; Oehmen, Christopher S.

    2013-09-28

    Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the data in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.

  9. Programming Molecular Association and Viscoelastic Behavior in Protein Networks.

    PubMed

    Dooling, Lawrence J; Buck, Maren E; Zhang, Wen-Bin; Tirrell, David A

    2016-06-01

    A set of recombinant artificial proteins that can be cross-linked, by either covalent bonds or association of helical domains or both, is described. The designed proteins can be used to construct molecular networks in which the mechanism of crosslinking determines the time-dependent responses to mechanical deformation. PMID:27061171

  10. The Problem of Thresholding in Small-World Network Analysis

    PubMed Central

    Langer, Nicolas; Pedroni, Andreas; Jäncke, Lutz

    2013-01-01

    Graph theory deterministically models networks as sets of vertices, which are linked by connections. Such mathematical representation of networks, called graphs are increasingly used in neuroscience to model functional brain networks. It was shown that many forms of structural and functional brain networks have small-world characteristics, thus, constitute networks of dense local and highly effective distal information processing. Motivated by a previous small-world connectivity analysis of resting EEG-data we explored implications of a commonly used analysis approach. This common course of analysis is to compare small-world characteristics between two groups using classical inferential statistics. This however, becomes problematic when using measures of inter-subject correlations, as it is the case in commonly used brain imaging methods such as structural and diffusion tensor imaging with the exception of fibre tracking. Since for each voxel, or region there is only one data point, a measure of connectivity can only be computed for a group. To empirically determine an adequate small-world network threshold and to generate the necessary distribution of measures for classical inferential statistics, samples are generated by thresholding the networks on the group level over a range of thresholds. We believe that there are mainly two problems with this approach. First, the number of thresholded networks is arbitrary. Second, the obtained thresholded networks are not independent samples. Both issues become problematic when using commonly applied parametric statistical tests. Here, we demonstrate potential consequences of the number of thresholds and non-independency of samples in two examples (using artificial data and EEG data). Consequently alternative approaches are presented, which overcome these methodological issues. PMID:23301043

  11. Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

    Energy Science and Technology Software Center (ESTSC)

    2012-05-31

    The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

  12. Google matrix analysis of C.elegans neural network

    NASA Astrophysics Data System (ADS)

    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.

  13. The Edinburgh human metabolic network reconstruction and its functional analysis

    PubMed Central

    Ma, Hongwu; Sorokin, Anatoly; Mazein, Alexander; Selkov, Alex; Selkov, Evgeni; Demin, Oleg; Goryanin, Igor

    2007-01-01

    A better understanding of human metabolism and its relationship with diseases is an important task in human systems biology studies. In this paper, we present a high-quality human metabolic network manually reconstructed by integrating genome annotation information from different databases and metabolic reaction information from literature. The network contains nearly 3000 metabolic reactions, which were reorganized into about 70 human-specific metabolic pathways according to their functional relationships. By analysis of the functional connectivity of the metabolites in the network, the bow-tie structure, which was found previously by structure analysis, is reconfirmed. Furthermore, the distribution of the disease related genes in the network suggests that the IN (substrates) subset of the bow-tie structure has more flexibility than other parts. PMID:17882155

  14. Topology analysis of social networks extracted from literature.

    PubMed

    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. PMID:26039072

  15. LANL material control indicator analysis program

    SciTech Connect

    Roybal, G. S.

    2001-01-01

    The possibility of SNM diversion/theft is a major concern to organizations charged with control of Special Nuclear Material (SNM). Several methods have been put in place to deter and or detect losses of SNM. These include inventory, material control physical barriers and the use of material control indicators (MCI). This paper will discuss the multi-tier LANL review mechanism for detecting and isolating missing SNM by the use of Material Control Indicators. Los Alamos MCI include daily analysis and review of item adjustments, weekly review of item adjustments, monthly analysis and review of inventory differences by Process Status and by Material Balance Areas, and quarterly analysis and review of Propagation of Variance. This paper, by providing an introduction to a site-specific application of MCI's, assists safeguards professionals in understanding the importance of an MCI Program in detecting accumulation for subsequent diversion/theft of special nuclear material.

  16. Graph spectral analysis of protein interaction network evolution.

    PubMed

    Thorne, Thomas; Stumpf, Michael P H

    2012-10-01

    We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a bayesian approach and perform posterior density estimation using an approximate bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more naturally than previously used summary statistics such as the degree distribution. Furthermore, we include the effects of sampling into the analysis, to properly correct for the incompleteness of existing datasets, and have analysed the performance of our method under various degrees of sampling. We consider a number of models focusing not only on the biologically relevant class of duplication models, but also including models of scale-free network growth that have previously been claimed to describe such data. We find a preference for a duplication-divergence with linear preferential attachment model in the majority of the interaction datasets considered. We also illustrate how our method can be used to perform multi-model inference of network parameters to estimate properties of the full network from sampled data. PMID:22552917

  17. Energy Analysis Program. 1992 Annual report

    SciTech Connect

    Not Available

    1993-06-01

    The Program became deeply involved in establishing 4 Washington, D.C., project office diving the last few months of fiscal year 1942. This project office, which reports to the Energy & Environment Division, will receive the majority of its support from the Energy Analysis Program. We anticipate having two staff scientists and support personnel in offices within a few blocks of DOE. Our expectation is that this office will carry out a series of projects that are better managed closer to DOE. We also anticipate that our representation in Washington will improve and we hope to expand the Program, its activities, and impact, in police-relevant analyses. In spite of the growth that we have achieved, the Program continues to emphasize (1) energy efficiency of buildings, (2) appliance energy efficiency standards, (3) energy demand forecasting, (4) utility policy studies, especially integrated resource planning issues, and (5) international energy studies, with considerate emphasis on developing countries and economies in transition. These continuing interests are reflected in the articles that appear in this report.

  18. Nonequilibrium, Drift-Flux Code System for Two-Phase Flow Network Analysis

    Energy Science and Technology Software Center (ESTSC)

    2000-08-01

    Version: 00 SOLA-LOOP is designed for the solution of transient two-phase flow in networks composed of one-dimensional components. The fluid dynamics is described by a nonequilibrium, drift-flux formulation of the fluid conservation laws. Although developed for nuclear reactor safety analysis, SOLA-LOOP may be used as the basis for other types of special-purpose network codes. The program can accommodate almost any set of constitutive relations, property tables, or other special features required for different applications.

  19. Network generation and analysis of complex biomass conversion systems

    SciTech Connect

    Rangarajan, S.; Kaminski, T.; Van Wyk, E.; Bhan, A.; Daoutidis, P.

    2011-01-01

    A modular computational tool for automated generation and rule-based post-processing of reaction systems in biomass conversion is presented. Cheminformatics and graph theory algorithms are used to generate chemical transformations pertaining to heterogeneous and homogeneous chemistries in the automated rule-based network generator. A domain-specific language provides a user-friendly English-like chemistry specification interface to the network generator. A rule-based pathway analysis module enables the user to extract and query pathways from the reaction network. A demonstration of the features of this tool is presented using Fructose to 5-Hydroxymethylfurfural as a case study.

  20. Network analysis of EtOH-related candidate genes.

    PubMed

    Guo, An-Yuan; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

    2010-05-01

    Recently, we collected many large-scale datasets for alcohol dependence and EtOH response in five organisms and deposited them in our EtOH-related gene resource database (ERGR, http://bioinfo.mc.vanderbilt.edu/ERGR/). Based on multidimensional evidence among these datasets, we prioritized 57 EtOH-related candidate genes. To explore their biological roles, and the molecular mechanisms of EtOH response and alcohol dependence, we examined the features of these genes by the Gene Ontology (GO) term-enrichment test and network/pathway analysis. Our analysis revealed that these candidate genes were highly enriched in alcohol dependence/alcoholism and highly expressed in brain or liver tissues. All the significantly enriched GO terms were related to neurotransmitter systems or EtOH metabolic processes. Using the Ingenuity Pathway Analysis system, we found that these genes were involved in networks of neurological disease, cardiovascular disease, inflammatory response, and small molecular metabolism. Many key genes in signaling pathways were in the central position of these networks. Furthermore, our protein-protein interaction (PPI) network analysis suggested some novel candidate genes which also had evidence in the ERGR database. This study demonstrated that our candidate gene selection is effective and our network/pathway analysis is useful for uncovering the molecular mechanisms of EtOH response and alcohol dependence. This approach can be applied to study the features of candidate genes of other complex traits/phenotypes. PMID:20491071