Science.gov

Sample records for network analysis program

  1. 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

  2. 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

  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. 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.

  3. 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.

  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. 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.

  11. 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.

  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. 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

  2. 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.

  3. 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)

  4. 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.

  5. 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.

  6. 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...

  7. 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...

  8. 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.

  9. 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.

  10. 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.

  11. 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

  12. 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.

  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 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

  20. 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

  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. 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

  6. 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

  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. 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.

  11. 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

  12. 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.

  13. 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…

  14. 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.

  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. 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.

  19. 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

  20. 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 (...

  1. 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.

  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. 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.

  4. 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…

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. 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.

  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. 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…

  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. 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.

  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. 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

  4. 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.

  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. 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.

  7. 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.

  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. 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.

  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. 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.

  1. 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'.

  2. 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

  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 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

  5. 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

  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. 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

  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. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  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. 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

  16. 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…

  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. 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…

  19. 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

  20. 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

  1. 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.

  2. 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.

  3. 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

  4. 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

  5. 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

  6. 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).

  7. 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.

  8. 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

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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)

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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…

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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…

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  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. 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

  15. 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...

  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. 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

  19. 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

  20. 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.

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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

  6. 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…

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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

  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. 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  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. 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.

  2. 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.

  3. 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.

  4. 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)

  5. 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.

  6. 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…

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. 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).

  12. 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

  13. 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...

  14. 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...

  15. 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...

  16. 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.

  17. 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).

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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

  3. 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

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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

  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. 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.