Science.gov

Sample records for network analysis program

  1. Social Network Analysis for Program Implementation

    PubMed Central

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

    2015-01-01

    This paper introduces the use of social network analysis theory and tools for implementation research. The social network perspective is useful for understanding, monitoring, influencing, or evaluating the implementation process when programs, policies, practices, or principles are designed and scaled up or adapted to different settings. We briefly describe common barriers to implementation success and relate them to the social networks of implementation stakeholders. We introduce a few simple measures commonly used in social network analysis and discuss how these measures can be used in program implementation. Using the four stage model of program implementation (exploration, adoption, implementation, and sustainment) proposed by Aarons and colleagues [1] and our experience in developing multi-sector partnerships involving community leaders, organizations, practitioners, and researchers, we show how network measures can be used at each stage to monitor, intervene, and improve the implementation process. Examples are provided to illustrate these concepts. We conclude with expected benefits and challenges associated with this approach. PMID:26110842

  2. Network Analysis of a Demonstration Program for the Developmentally Disabled

    ERIC Educational Resources Information Center

    Fredericks, Kimberly A.

    2005-01-01

    This chapter presents the findings from a network analysis of a demonstration program for the developmentally disabled to show the application of graphical network analysis in program evaluation. The developmentally disabled demonstration (DDD) program was a five-year pilot project to provide person-centered service environments to people with …

  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 the Farabi Exchange Program: Student Mobility

    ERIC Educational Resources Information Center

    Ugurlu, Zeynep

    2016-01-01

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

  5. 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.

  6. 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.…

  7. 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…

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Using Organizational Network Analysis to Plan Cancer Screening Programs for Vulnerable Populations

    PubMed Central

    Carothers, Bobbi J.; Lofters, Aisha K.

    2014-01-01

    Objectives. We examined relationships among organizations in a cancer screening network to inform the development of interventions to improve cancer screening for South Asians living in the Peel region of Ontario. Methods. From April to July 2012, we surveyed decision-makers, program managers, and program staff in 22 organizations in the South Asian cancer screening network in the Peel region. We used a network analytic approach to evaluate density (range = 0%–100%, number of ties among organizations in the network expressed as a percentage of all possible ties), centralization (range = 0–1, the extent of variability in centrality), and node characteristics for the communication, collaboration, and referral networks. Results. Density was similar across communication (15%), collaboration (17%), and referral (19%) networks. Centralization was greater in the collaboration network (0.30) than the communication network (0.24), and degree centralization was greater in the inbound (0.42) than the outbound (0.37) referral network. Diverse organizations were central to the networks. Conclusions. Certain organizations were unexpectedly important to the South Asian cancer screening network. Program planning was informed by identifying opportunities to strengthen linkages between key organizations and to leverage existing ties. PMID:24328613

  13. Weaving the Native Web: Using Social Network Analysis to Demonstrate the Value of a Minority Career Development Program

    PubMed Central

    Buchwald, Dedra; Dick, Rhonda Wiegman

    2011-01-01

    Purpose American Indian and Alaska Native scientists are consistently among the most underrepresented minority groups in health research. The authors used social network analysis (SNA) to evaluate the Native Investigator Development Program (NIDP), a career development program for junior Native researchers established as a collaboration between the University of Washington and the University of Colorado Denver. Method The study focused on 29 trainees and mentors who participated in the NIDP. Data were collected on manuscripts and grant proposals produced by participants from 1998 to 2007. Information on authorship of manuscripts and collaborations on grant applications was used to conduct social network analyses with 3 measures of centrality and 1 measure of network reach. Both visual and quantitative analyses were performed. Results Participants in the NIDP collaborated on 106 manuscripts and 83 grant applications. Although 3 highly connected individuals, with critical and central roles in the program, accounted for much of the richness of the network, both current core faculty and “graduates” of the program were heavily involved in collaborations on manuscripts and grants. Conclusions This study’s innovative application of SNA demonstrates that collaborative relationships can be an important outcome of career development programs for minority investigators, and that an analysis of these relationships can provide a more complete assessment of the value of such programs. PMID:21512364

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

    PubMed

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

    2007-01-05

    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 (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 performed

  15. [Networks, disease management programs, GP coordinator: analysis of recent ambulatory reforms in Germany].

    PubMed

    Giovanella, Ligia

    2011-01-01

    Strengthening the role of the general practitioner in the conduction and coordination of specialized, inpatient and social care to ensure the continuity is a trend observed in recent health reforms in European countries. In Germany, from the second half of the 1990s, driven by economic pressures, a specific legislation and initiatives of the providers themselves have developed new organizational structures and care models for the purpose of the integration of the health care system and the coordination of health care in the form of: physicians networks, practitioner coordinator model, diseases management programs and integrated care. From a literature review, document analysis, visits to services and interviews with key informants, this paper analyzes the dynamics of these organizational changes in the German outpatient sector. The mechanisms of integration and coordination proposed are examined, and the potential impacts on the efficiency and quality of new organizational arrangements are discussed. Also it is analyzed the reasons and interests involved that point out the obstacles to the implementation. It was observed the process of an incremental reform with a tendency of diversification of the healthcare panorama in Germany with the presence of integrated models of care and strengthening the role of general practitioners in the coordination of patient care.

  16. 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…

  17. 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

    2011-10-09

    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.

  18. 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.

  19. 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.

  20. 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.

  1. Communications network analysis tool

    NASA Astrophysics Data System (ADS)

    Phillips, Wayne; Dunn, Gary

    1989-11-01

    The Communications Network Analysis Tool (CNAT) is a set of computer programs that aids in the performance evaluation of a communication system in a real-world scenario. Communication network protocols can be modeled and battle group connectivity can be analyzed in the presence of jamming and the benefit of relay platforms can be studied. The Joint Tactical Information Distribution System (JTIDS) Communication system architecture is currently being modeled; however, the computer software is modular enough to allow substitution of a new code representative of prospective communication protocols.

  2. Automatic Microwave Network Analysis.

    DTIC Science & Technology

    A program and procedure are developed for the automatic measurement of microwave networks using a Hewlett-Packard network analyzer and programmable calculator . The program and procedure are used in the measurement of a simple microwave two port network. These measurements are evaluated by comparing with measurements on the same network using other techniques. The programs...in the programmable calculator are listed in Appendix 1. The step by step procedure used is listed in Appendix 2. (Author)

  3. Programming neural networks

    SciTech Connect

    Anderson, J.A.; Markman, A.B.; Viscuso, S.R.; Wisniewski, E.J.

    1988-09-01

    Neural networks ''compute'' though not in the way that traditional computers do. One must accept their weaknesses to use their strengths. The authors present several applications of a particular non-linear network (the BSB model) to illustrate some of the peculiarities inherent in this architecture.

  4. Analysis of Simple Neural Networks

    DTIC Science & Technology

    1988-12-20

    ANALYSIS OF SThlPLE NEURAL NETWORKS Chedsada Chinrungrueng Master’s Report Under the Supervision of Prof. Carlo H. Sequin Department of... Neural Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT...and guidJ.nce. I have learned a great deal from his teaching, knowledge, and criti- cism. 1. MOTIVATION ANALYSIS OF SIMPLE NEURAL NETWORKS Chedsada

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

    PubMed

    Hindhede, Anette Lykke; Aagaard-Hansen, Jens

    2017-03-01

    This article provides an example of the application of social network analysis method to assess community participation thereby strengthening planning and implementation of health promotion programming. Community health promotion often takes the form of services that reach out to or are located within communities. The concept of community reflects the idea that people's behavior and well-being are influenced by interaction with others, and here, health promotion requires participation and local leadership to facilitate transmission and uptake of interventions for the overall community to achieve social change. However, considerable uncertainty exists over exact levels of participation in these interventions. The article draws on a mixed methods research within a community development project in a vulnerable neighborhood of a town in Denmark. It presents a detailed analysis of the way in which social network analysis can be used as a tool to display participation and nonparticipation in community development and health promotion activities, to help identify capacities and assets, mobilize resources, and finally to evaluate the achievements. The article concludes that identification of interpersonal ties among people who know one another well as well as more tenuous relationships in networks can be used by community development workers to foster greater cohesion and cooperation within an area.

  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. Probabilistic Analysis of Neural Networks

    DTIC Science & Technology

    1990-11-26

    provide an understanding of the basic mechanisms of learning and recognition in neural networks . The main areas of progress were analysis of neural ... networks models, study of network connectivity, and investigation of computer network theory.

  12. 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

  13. Compressive Network Analysis.

    PubMed

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

    2014-11-01

    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.

  14. 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

  15. Neural-Network Object-Recognition Program

    NASA Technical Reports Server (NTRS)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  16. 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.

  17. Integrative Gene Regulatory Network Analysis Reveals Light-Induced Regional Gene Expression Phase Shift Programs in the Mouse Suprachiasmatic Nucleus

    PubMed Central

    Zhu, Haisun; Vadigepalli, Rajanikanth; Rafferty, Rachel; Gonye, Gregory E.; Weaver, David R.; Schwaber, James S.

    2012-01-01

    We use the multigenic pattern of gene expression across suprachiasmatic nuclei (SCN) regions and time to understand the dynamics within the SCN in response to a circadian phase-resetting light pulse. Global gene expression studies of the SCN indicate that circadian functions like phase resetting are complex multigenic processes. While the molecular dynamics of phase resetting are not well understood, it is clear they involve a “functional gene expression program”, e.g., the coordinated behavior of functionally related genes in space and time. In the present study we selected a set of 89 of these functionally related genes in order to further understand this multigenic program. By use of high-throughput qPCR we studied 52 small samples taken by anatomically precise laser capture from within the core and shell SCN regions, and taken at time points with and without phase resetting light exposure. The results show striking regional differences in light response to be present in the mouse SCN. By using network-based analyses, we are able to establish a highly specific multigenic correlation between genes expressed in response to light at night and genes normally activated during the day. The light pulse triggers a complex and highly coordinated network of gene regulation. The largest differences marking neuroanatomical location are in transmitter receptors, and the largest time-dependent differences occur in clock-related genes. Nighttime phase resetting appears to recruit transcriptional regulatory processes normally active in the day. This program, or mechanism, causes the pattern of core region gene expression to transiently shift to become more like that of the shell region. PMID:22662235

  18. 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…

  19. A linear circuit analysis program with stiff systems capability

    NASA Technical Reports Server (NTRS)

    Cook, C. H.; Bavuso, S. J.

    1973-01-01

    Several existing network analysis programs have been modified and combined to employ a variable topological approach to circuit translation. Efficient numerical integration techniques are used for transient analysis.

  20. A neural network for bounded linear programming

    SciTech Connect

    Culioli, J.C.; Protopopescu, V.; Britton, C.; Ericson, N. )

    1989-01-01

    The purpose of this paper is to describe a neural network implementation of an algorithm recently designed at ORNL to solve the Transportation and the Assignment Problems, and, more generally, any explicitly bounded linear program. 9 refs.

  1. 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.

  2. Nonlinear programming with feedforward neural networks.

    SciTech Connect

    Reifman, J.

    1999-06-02

    We provide a practical and effective method for solving constrained optimization problems by successively training a multilayer feedforward neural network in a coupled neural-network/objective-function representation. Nonlinear programming problems are easily mapped into this representation which has a simpler and more transparent method of solution than optimization performed with Hopfield-like networks and poses very mild requirements on the functions appearing in the problem. Simulation results are illustrated and compared with an off-the-shelf optimization tool.

  3. Programming of inhomogeneous resonant guided wave networks.

    PubMed

    Feigenbaum, Eyal; Burgos, Stanley P; Atwater, Harry A

    2010-12-06

    Photonic functions are programmed by designing the interference of local waves in inhomogeneous resonant guided wave networks composed of power-splitting elements arranged at the nodes of a nonuniform waveguide network. Using a compact, yet comprehensive, scattering matrix representation of the network, the desired photonic function is designed by fitting structural parameters according to an optimization procedure. This design scheme is demonstrated for plasmonic dichroic and trichroic routers in the infrared frequency range.

  4. Control of tree water networks: A geometric programming approach

    NASA Astrophysics Data System (ADS)

    Sela Perelman, L.; Amin, S.

    2015-10-01

    This paper presents a modeling and operation approach for tree water supply systems. The network control problem is approximated as a geometric programming (GP) problem. The original nonlinear nonconvex network control problem is transformed into a convex optimization problem. The optimization model can be efficiently solved to optimality using state-of-the-art solvers. Two control schemes are presented: (1) operation of network actuators (pumps and valves) and (2) controlled demand shedding allocation between network consumers with limited resources. The dual of the network control problem is formulated and is used to perform sensitivity analysis with respect to hydraulic constraints. The approach is demonstrated on a small branched-topology network and later extended to a medium-size irrigation network. The results demonstrate an intrinsic trade-off between energy costs and demand shedding policy, providing an efficient decision support tool for active management of water systems.

  5. 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.

  6. Neural network for solving convex quadratic bilevel programming problems.

    PubMed

    He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie

    2014-03-01

    In this paper, using the idea of successive approximation, we propose a neural network to solve convex quadratic bilevel programming problems (CQBPPs), which is modeled by a nonautonomous differential inclusion. Different from the existing neural network for CQBPP, the model has the least number of state variables and simple structure. Based on the theory of nonsmooth analysis, differential inclusions and Lyapunov-like method, the limit equilibrium points sequence of the proposed neural networks can approximately converge to an optimal solution of CQBPP under certain conditions. Finally, simulation results on two numerical examples and the portfolio selection problem show the effectiveness and performance of the proposed neural network.

  7. The Analysis of Social Networks.

    PubMed

    O'Malley, A James; Marsden, Peter V

    2008-12-01

    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.

  8. 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.

  9. Comparative analysis of collaboration networks

    NASA Astrophysics Data System (ADS)

    Progulova, Tatiana; Gadjiev, Bahruz

    2011-03-01

    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.

  10. Biodiesel Emissions Analysis Program

    EPA Pesticide Factsheets

    Using existing data, the EPA's biodiesel emissions analysis program sought to quantify the air pollution emission effects of biodiesel for diesel engines that have not been specifically modified to operate on biodiesel.

  11. 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.

  12. 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.

  13. 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

  14. The Integrated Oncology Program of the Italian Ministry of Health. Analytical and clinical validation of new biomarkers for early diagnosis: network, resources, methodology, quality control, and data analysis.

    PubMed

    Paradiso, Angelo; Mangia, Anita; Orlando, Claudio; Verderio, Paolo; Belfiglio, Maurizio; Marchetti, Antonio; Bertario, Lucio; Chiappetta, Gennaro; Gion, Massimo; Tonini, Gian Paolo; Podo, Franca; Vocaturo, Amina; Silvestrini, Rosella; Romani, Massimo; Belloni, Elena; Cavallo, Delia; Ulivi, Paola; Tommasi, Stefania; Steffan, Agostino; Russo, Antonio; Alessio, Massimo; Calistri, Daniele; Zancan, Matelda; Parrela, Paola; Broggini, Massimo; Giuseppe, Antonio; Buttitta, Fiamma; Finocchiaro, Gaetano; Mazzocco, Katia; Veronesi, Giulia; Landuzzi, Lorena; Benevolo, Maria; Mariani, Luciano; De Marco, Federico; Venuti, Aldo; Giannelli, Gianluigi; Quaranta, Michele; Trojano, Vito

    2009-01-01

    In 2007, an Italian cancer research group proposed a specific concerted action aimed at the "analytical and clinica validation of new biomarkers for early diagnosis: Network, resources, methodology, quality control, and data analysis." The proposal united 37 national operative units involved in different biomarker studies and it created a strong coordinative body with the necessary expertise in methodologies, statistical analysis, quality control, and biological resources to perform ad hoc validation studies for new biomarkers of early cancer diagnosis. The action, financed by the Italian Ministry of Health within the Integrated Oncology Program (PIO) coordinated by NCI-Istituto Tumori Bari, started in 2007 and activated 7 projects, each of which focused on disease-specific biomarker studies. Overall, the 37 participating units proposed studies on 50 biomarkers, including analytical and clinical validation procedures. Clusters of units were specifically involved in research of early-detection biomarkers for cancers of the lung, digestive tract, prostate/bladder, and nervous system, as well as female cancers. Furthermore, a cluster involved in biomarkers for bioimaging and infection-related cancers was created. The first investigators' meeting, "Analytical and clinical validation of new biomarkers for early diagnosis," was held on 9 September 2008 in Bari. During this meeting, methodological aspects, scientific programs and preliminary results were presented and discussed.

  15. 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)].

  16. 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…

  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. Family English Literacy Network Program. Curriculum Guide.

    ERIC Educational Resources Information Center

    Florida International Univ., Miami. Coll. of Education.

    This curriculum guide, developed for the Family English Literacy Network Program, contains a competency-based lesson plans for four levels of instruction. The competencies in the curriculum represent the objectives of each lesson. The charts that are provided are arranged by broad category, lesson plan number, and sub-topic. The curriculum also…

  19. Transcriptional Network Analysis in Muscle Reveals AP-1 as a Partner of PGC-1α in the Regulation of the Hypoxic Gene Program

    PubMed Central

    Baresic, Mario; Salatino, Silvia; Kupr, Barbara

    2014-01-01

    Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α. PMID:24912679

  20. Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program.

    PubMed

    Baresic, Mario; Salatino, Silvia; Kupr, Barbara; van Nimwegen, Erik; Handschin, Christoph

    2014-08-01

    Skeletal muscle tissue shows an extraordinary cellular plasticity, but the underlying molecular mechanisms are still poorly understood. Here, we use a combination of experimental and computational approaches to unravel the complex transcriptional network of muscle cell plasticity centered on the peroxisome proliferator-activated receptor γ coactivator 1α (PGC-1α), a regulatory nexus in endurance training adaptation. By integrating data on genome-wide binding of PGC-1α and gene expression upon PGC-1α overexpression with comprehensive computational prediction of transcription factor binding sites (TFBSs), we uncover a hitherto-underestimated number of transcription factor partners involved in mediating PGC-1α action. In particular, principal component analysis of TFBSs at PGC-1α binding regions predicts that, besides the well-known role of the estrogen-related receptor α (ERRα), the activator protein 1 complex (AP-1) plays a major role in regulating the PGC-1α-controlled gene program of the hypoxia response. Our findings thus reveal the complex transcriptional network of muscle cell plasticity controlled by PGC-1α.

  1. 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

  2. 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.

  3. Network Analysis with Stochastic Grammars

    DTIC Science & Technology

    2015-09-17

    forensics analysis of computer network traffic. SCFG is leveraged to provide context to the low-level data collected as evidence and to build behavior ...grammars was developed to compare behavior patterns represented as grammars. Finally, the SCFG capabilities were demonstrated in performing association...Comparison. After determining suitability for computer network traffic analysis, this research examines representing profiles as behavioral patterns and

  4. Defense Switched Network Technology and Experiments Program.

    DTIC Science & Technology

    2014-09-26

    amenable to sufficiently complete and detailed definition to be incor- porated in a computer system . Promising areas include diagnosis of system faults ...Technology and Experiments Program. The areas of work reported are: (1) development and evaluation of routing and system control techniques for...3) development and test of data communication techniques using DoD-standard data protocols in an integrated voice/data network, and (4) EISN system

  5. 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.

  6. Introduction to Social Network Analysis

    NASA Astrophysics Data System (ADS)

    Zaphiris, Panayiotis; Ang, Chee Siang

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

  7. Probabilistic Structural Analysis Program

    NASA Technical Reports Server (NTRS)

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

    2010-01-01

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

  8. 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.

  9. Chemical exchange program analysis.

    SciTech Connect

    Waffelaert, Pascale

    2007-09-01

    As part of its EMS, Sandia performs an annual environmental aspects/impacts analysis. The purpose of this analysis is to identify the environmental aspects associated with Sandia's activities, products, and services and the potential environmental impacts associated with those aspects. Division and environmental programs established objectives and targets based on the environmental aspects associated with their operations. In 2007 the most significant aspect identified was Hazardous Materials (Use and Storage). The objective for Hazardous Materials (Use and Storage) was to improve chemical handling, storage, and on-site movement of hazardous materials. One of the targets supporting this objective was to develop an effective chemical exchange program, making a business case for it in FY07, and fully implementing a comprehensive chemical exchange program in FY08. A Chemical Exchange Program (CEP) team was formed to implement this target. The team consists of representatives from the Chemical Information System (CIS), Pollution Prevention (P2), the HWMF, Procurement and the Environmental Management System (EMS). The CEP Team performed benchmarking and conducted a life-cycle analysis of the current management of chemicals at SNL/NM and compared it to Chemical Exchange alternatives. Those alternatives are as follows: (1) Revive the 'Virtual' Chemical Exchange Program; (2) Re-implement a 'Physical' Chemical Exchange Program using a Chemical Information System; and (3) Transition to a Chemical Management Services System. The analysis and benchmarking study shows that the present management of chemicals at SNL/NM is significantly disjointed and a life-cycle or 'Cradle-to-Grave' approach to chemical management is needed. This approach must consider the purchasing and maintenance costs as well as the cost of ultimate disposal of the chemicals and materials. A chemical exchange is needed as a mechanism to re-apply chemicals on site. This will not only reduce the quantity of

  10. 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... of vehicle registration and driver's licenses, or tax and fee collections. (b) (c) Program...

  11. 40 CFR 51.353 - Network type and program evaluation.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 40 Protection of Environment 2 2012-07-01 2012-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized... of vehicle registration and driver's licenses, or tax and fee collections. (b) (c) Program...

  12. 40 CFR 51.353 - Network type and program evaluation.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 40 Protection of Environment 2 2013-07-01 2013-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized... of vehicle registration and driver's licenses, or tax and fee collections. (b) (c) Program...

  13. 40 CFR 51.353 - Network type and program evaluation.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 40 Protection of Environment 2 2014-07-01 2014-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized... of vehicle registration and driver's licenses, or tax and fee collections. (b) (c) Program...

  14. 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... of vehicle registration and driver's licenses, or tax and fee collections. (b) (c) Program...

  15. 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.

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

    DTIC Science & Technology

    2015-12-01

    use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations and selectively target key elements...data to improve SC. 14. SUBJECT TERMS social network analysis, dark networks, light networks, dim networks, security cooperation, Southeast Asia...task may already exist. Recently, the use of social network analysis (SNA) has allowed the military to map dark networks of terrorist organizations

  17. 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.

  18. Neural network models for Linear Programming

    SciTech Connect

    Culioli, J.C.; Protopopescu, V.; Britton, C.; Ericson, N. )

    1989-01-01

    The purpose of this paper is to present a neural network that solves the general Linear Programming (LP) problem. In the first part, we recall Hopfield and Tank's circuit for LP and show that although it converges to stable states, it does not, in general, yield admissible solutions. This is due to the penalization treatment of the constraints. In the second part, we propose an approach based on Lagragrange multipliers that converges to primal and dual admissible solutions. We also show that the duality gap (measuring the optimality) can be rendered, in principle, as small as needed. 11 refs.

  19. Genetic Network Programming with Reconstructed Individuals

    NASA Astrophysics Data System (ADS)

    Ye, Fengming; Mabu, Shingo; Wang, Lutao; Eto, Shinji; Hirasawa, Kotaro

    A lot of research on evolutionary computation has been done and some significant classical methods such as Genetic Algorithm (GA), Genetic Programming (GP), Evolutionary Programming (EP), and Evolution Strategies (ES) have been studied. Recently, a new approach named Genetic Network Programming (GNP) has been proposed. GNP can evolve itself and find the optimal solution. It is based on the idea of Genetic Algorithm and uses the data structure of directed graphs. Many papers have demonstrated that GNP can deal with complex problems in the dynamic environments very efficiently and effectively. As a result, recently, GNP is getting more and more attentions and is used in many different areas such as data mining, extracting trading rules of stock markets, elevator supervised control systems, etc., and GNP has obtained some outstanding results. Focusing on the GNP's distinguished expression ability of the graph structure, this paper proposes a method named Genetic Network Programming with Reconstructed Individuals (GNP-RI). The aim of GNP-RI is to balance the exploitation and exploration of GNP, that is, to strengthen the exploitation ability by using the exploited information extensively during the evolution process of GNP and finally obtain better performances than that of GNP. In the proposed method, the worse individuals are reconstructed and enhanced by the elite information before undergoing genetic operations (mutation and crossover). The enhancement of worse individuals mimics the maturing phenomenon in nature, where bad individuals can become smarter after receiving a good education. In this paper, GNP-RI is applied to the tile-world problem which is an excellent bench mark for evaluating the proposed architecture. The performance of GNP-RI is compared with that of the conventional GNP. The simulation results show some advantages of GNP-RI demonstrating its superiority over the conventional GNPs.

  20. 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.

  1. Neural Networks, Reliability and Data Analysis

    DTIC Science & Technology

    1993-01-01

    Neural network technology has been surveyed with the intent of determining the feasibility and impact neural networks may have in the area of...automated reliability tools. Data analysis capabilities of neural networks appear to be very applicable to reliability science due to similar mathematical...tendencies in data.... Neural networks , Reliability, Data analysis, Automated reliability tools, Automated intelligent information processing, Statistical neural network.

  2. Linear programming for learning in neural networks

    NASA Astrophysics Data System (ADS)

    Raghavan, Raghu

    1991-08-01

    The authors have previously proposed a network of probabilistic cellular automata (PCAs) as part of an image recognition system designed to integrate model-based and data-driven approaches in a connectionist framework. The PCA arises from some natural requirements on the system which include incorporation of prior knowledge such as in inference rules, locality of inferences, and full parallelism. This network has been applied to recognize objects in both synthetic and in real data. This approach achieves recognition through the short-, rather than the long-time behavior of the dynamics of the PCA. In this paper, some methods are developed for learning the connection strengths by solving linear inequalities: the figures of merit are tendencies or directions of movement of the dynamical system. These 'dynamical' figures of merit result in inequality constraints on the connection strengths which are solved by linear (LP) or quadratic programs (QP). An algorithm is described for processing a large number of samples to determine weights for the PCA. The work may be regarded as either pointing out another application for constrained optimization, or as pointing out the need to extend the perceptron and similar methods for learning. The extension is needed because the neural network operates on a different principle from that for which the perceptron method was devised.

  3. Modular analysis of biological networks.

    PubMed

    Kaltenbach, Hans-Michael; Stelling, Jörg

    2012-01-01

    The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.

  4. 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.

  5. Antenna analysis using neural networks

    NASA Technical Reports Server (NTRS)

    Smith, William T.

    1992-01-01

    Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern

  6. 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.…

  7. 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

  8. Network Interventions on Physical Activity in an Afterschool Program: An Agent-Based Social Network Study

    PubMed Central

    Zhang, Jun; Shoham, David A.; Tesdahl, Eric

    2015-01-01

    Objectives. We studied simulated interventions that leveraged social networks to increase physical activity in children. Methods. We studied a real-world social network of 81 children (average age = 7.96 years) who lived in low socioeconomic status neighborhoods, and attended public schools and 1 of 2 structured afterschool programs. The sample was ethnically diverse, and 44% were overweight or obese. We used social network analysis and agent-based modeling simulations to test whether implementing a network intervention would increase children’s physical activity. We tested 3 intervention strategies. Results. The intervention that targeted opinion leaders was effective in increasing the average level of physical activity across the entire network. However, the intervention that targeted the most sedentary children was the best at increasing their physical activity levels. Conclusions. Which network intervention to implement depends on whether the goal is to shift the entire distribution of physical activity or to influence those most adversely affected by low physical activity. Agent-based modeling could be an important complement to traditional project planning tools, analogous to sample size and power analyses, to help researchers design more effective interventions for increasing children’s physical activity. PMID:25689202

  9. 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

  10. 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.

  11. 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…

  12. A recurrent neural network for solving bilevel linear programming problem.

    PubMed

    He, Xing; Li, Chuandong; Huang, Tingwen; Li, Chaojie; Huang, Junjian

    2014-04-01

    In this brief, based on the method of penalty functions, a recurrent neural network (NN) modeled by means of a differential inclusion is proposed for solving the bilevel linear programming problem (BLPP). Compared with the existing NNs for BLPP, the model has the least number of state variables and simple structure. Using nonsmooth analysis, the theory of differential inclusions, and Lyapunov-like method, the equilibrium point sequence of the proposed NNs can approximately converge to an optimal solution of BLPP under certain conditions. Finally, the numerical simulations of a supply chain distribution model have shown excellent performance of the proposed recurrent NNs.

  13. Solving quadratic programming problems by delayed projection neural network.

    PubMed

    Yang, Yongqing; Cao, Jinde

    2006-11-01

    In this letter, the delayed projection neural network for solving convex quadratic programming problems is proposed. The neural network is proved to be globally exponentially stable and can converge to an optimal solution of the optimization problem. Three examples show the effectiveness of the proposed network.

  14. 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.

  15. 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…

  16. 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…

  17. 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.

  18. 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…

  19. 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.

  20. 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.

  1. Liquid Effluents Program mission analysis

    SciTech Connect

    Lowe, S.S.

    1994-09-27

    Systems engineering is being used to identify work to cleanup the Hanford Site. The systems engineering process transforms an identified mission need into a set of performance parameters and a preferred system configuration. Mission analysis is the first step in the process. Mission analysis supports early decision-making by clearly defining the program objectives, and evaluating the feasibility and risks associated with achieving those objectives. The results of the mission analysis provide a consistent basis for subsequent systems engineering work. A mission analysis was performed earlier for the overall Hanford Site. This work was continued by a ``capstone`` team which developed a top-level functional analysis. Continuing in a top-down manner, systems engineering is now being applied at the program and project levels. A mission analysis was conducted for the Liquid Effluents Program. The results are described herein. This report identifies the initial conditions and acceptable final conditions, defines the programmatic and physical interfaces and sources of constraints, estimates the resources to carry out the mission, and establishes measures of success. The mission analysis reflects current program planning for the Liquid Effluents Program as described in Liquid Effluents FY 1995 Multi-Year Program Plan.

  2. Spherical-Bearing Analysis Program

    NASA Technical Reports Server (NTRS)

    Kleckner, R. J.

    1984-01-01

    Computer program SPHERBEAN, developed to predict thermomechanical performance characteristics of double-row spherical roller bearings over wide range of operating conditions. Analysis allows six degrees of freedom for each roller and three for each half of an optionally split cage. Program capabilities provide sufficient generality to allow detailed simulation of both high-speed and conventional bearing operation.

  3. Web Page Design and Network Analysis.

    ERIC Educational Resources Information Center

    Wan, Hakman A.; Chung, Chi-wai

    1998-01-01

    Examines problems in Web-site design from the perspective of network analysis. In view of the similarity between the hypertext structure of Web pages and a generic network, network analysis presents concepts and theories that provide insight for Web-site design. Describes the problem of home-page location and control of number of Web pages and…

  4. Modelling gene and protein regulatory networks with answer set programming.

    PubMed

    Fayruzov, Timur; Janssen, Jeroen; Vermeir, Dirk; Cornelis, Chris; De Cock, Martine

    2011-01-01

    Recently, many approaches to model regulatory networks have been proposed in the systems biology domain. However, the task is far from being solved. In this paper, we propose an Answer Set Programming (ASP)-based approach to model interaction networks. We build a general ASP framework that describes the network semantics and allows modelling specific networks with little effort. ASP provides a rich and flexible toolbox that allows expanding the framework with desired features. In this paper, we tune our framework to mimic Boolean network behaviour and apply it to model the Budding Yeast and Fission Yeast cell cycle networks. The obtained steady states of these networks correspond to those of the Boolean networks.

  5. Program Analysis in Arts Education

    ERIC Educational Resources Information Center

    Dobbs, Stephen Mark

    1972-01-01

    Major drawback of traditional evaluation is its emphasis on outcome" or terminal performance; what is needed are more process-oriented methods of assessment. Author describes Program Analysis" as a possible model. (Author/MB)

  6. 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

  7. A novel neural network for nonlinear convex programming.

    PubMed

    Gao, Xing-Bao

    2004-05-01

    In this paper, we present a neural network for solving the nonlinear convex programming problem in real time by means of the projection method. The main idea is to convert the convex programming problem into a variational inequality problem. Then a dynamical system and a convex energy function are constructed for resulting variational inequality problem. It is shown that the proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem. Compared with the existing neural networks for solving the nonlinear convex programming problem, the proposed neural network has no Lipschitz condition, no adjustable parameter, and its structure is simple. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.

  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. 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.

  10. Functional Module Analysis for Gene Coexpression Networks with Network Integration

    PubMed Central

    Zhang, Shuqin; Zhao, Hongyu

    2015-01-01

    Network has been a general tool for studying the complex interactions between different genes, proteins and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with 3 complete subgraphs, and 11 modules with 2 complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally. PMID:26451826

  11. 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.

  12. Social network analysis and dual rover communications

    NASA Astrophysics Data System (ADS)

    Litaker, Harry L.; Howard, Robert L.

    2013-10-01

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

  13. 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

  14. A SOCIAL NETWORK ANALYSIS APPROACH TO UNDERSTAND CHANGES IN A CANCER DISPARITIES COMMUNITY PARTNERSHIP NETWORK.

    PubMed

    Luque, John S; Tyson, Dinorah Martinez; Bynum, Shalanda A; Noel-Thomas, Shalewa; Wells, Kristen J; Vadaparampil, Susan T; Gwede, Clement K; Meade, Cathy D

    2011-11-01

    The Tampa Bay Community Cancer Network (TBCCN) is one of the Community Network Program sites funded (2005-10) by the National Cancer Institute's Center to Reduce Cancer Health Disparities. TBCCN was tasked to form a sustainable, community-based partnership network focused on the goal of reducing cancer health disparities among racial-ethnic minority and medically underserved populations. This article reports evaluation outcome results from a social network analysis and discusses the varying TBCCN partner roles-in education, training, and research-over a span of three years (2007-09). The network analysis included 20 local community partner organizations covering a tricounty area in Southwest Florida. In addition, multiple externally funded, community-based participatory research pilot projects with community-academic partners have either been completed or are currently in progress, covering research topics including culturally targeted colorectal and prostate cancer screening education, patient navigation focused on preventing cervical cancer in rural Latinas, and community perceptions of biobanking. The social network analysis identified a trend toward increased network decentralization based on betweenness centrality and overall increase in number of linkages, suggesting network sustainability. Degree centrality, trust, and multiplexity exhibited stability over the three-year time period. These results suggest increased interaction and interdependence among partner organizations and less dependence on the cancer center. Social network analysis enabled us to quantitatively evaluate partnership network functioning of TBCCN in terms of network structure and information and resources flows, which are integral to understanding effective coalition practice based on Community Coalition Action Theory ( Butterfoss and Kegler 2009). Sharing the results of the social network analysis with the partnership network is an important component of our coalition building efforts. A

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

    PubMed

    Rücker, Gerta

    2012-12-01

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

  16. 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.

  17. 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.

  18. 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.

  19. A Statewide Program Network That Works. NCCSCE Working Paper Series.

    ERIC Educational Resources Information Center

    Terry, Jo-Ann W.; Jacques, Edith

    The community service/continuing education (CS/CE) departments at Michigan's 29 community colleges have developed a network of joint programming in order to share and duplicate successful programs across the state. This process has been sponsored through the Michigan Community College Community Services Association (MCCCSA), which was founded in…

  20. Extracting vascular networks under physiological constraints via integer programming.

    PubMed

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

    2014-01-01

    We introduce an integer programming-based approach to vessel network extraction that enforces global physiological constraints on the vessel structure and learn this prior from a high-resolution reference network. The method accounts for both image evidence and geometric relationships between vessels by formulating and solving an integer programming problem. Starting from an over-connected network, it is pruning vessel stumps and spurious connections by evaluating bifurcation angle and connectivity of the graph. We utilize a high-resolution micro computed tomography (μCT) dataset of a cerebrovascular corrosion cast to obtain a reference network, 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.

  1. The LTS timing analysis program :

    SciTech Connect

    Armstrong, Darrell Jewell; Schwarz, Jens

    2013-08-01

    The LTS Timing Analysis program described in this report uses signals from the Tempest Lasers, Pulse Forming Lines, and Laser Spark Detectors to carry out calculations to quantify and monitor the performance of the the Z-Accelerators laser triggered SF6 switches. The program analyzes Z-shots beginning with Z2457, when Laser Spark Detector data became available for all lines.

  2. Quantitive and Sociological Analysis of Blog Networks

    NASA Astrophysics Data System (ADS)

    Bachnik, W.; Szymczyk, S.; Leszczynski, S.; Podsiadlo, R.; Rymszewicz, E.; Kurylo, L.; Makowiec, D.; Bykowska, B.

    2005-10-01

    This paper examines the emerging phenomenon of blogging, using three different Polish blogging services as the base of the research. Authors show that blog networks are sharing their characteristics with complex networks (gamma coefficients, small worlds, cliques, etc.). Elements of sociometric analysis were used to prove existence of some social structures in the blog networks.

  3. 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).

  4. MAILROOM- A LOCAL AREA NETWORK ELECTRONIC MAIL PROGRAM

    NASA Technical Reports Server (NTRS)

    Weiner, M. J.

    1994-01-01

    The Mailroom program is a Local Area Network (LAN) electronic mail program. It allows LAN users to electronically exchange notes, letters, reminders, or any sort of communication via their computer. The Mailroom program links all LAN users into a communication circle where messages can be created, sent, copied, printed, downloaded, uploaded, and deleted through a series of menu-driven screens. Mailroom includes a feature which allows users to determine if a message they have sent has been read by the receiver. Each user must be separately installed and removed from Mailroom as they join or leave the network. Mailroom comes with a program that accomplishes this with minimum of effort on the part of the Network Administrator/Manager. There is also a program that allows the Network Administrator/Manager to install Mailroom on each user's workstation so that on execution of Mailroom the user's station may be identified and the configurations settings activated. It will create its own configuration and data/supporting files during the setup and installation process. The Mailroom program is written in Microsoft QuickBasic. It was developed to run on networked IBM XT/ATs or compatibles and requires that all participating workstations share a common drive. It has been implemented under DOS 3.2 and has a memory requirement of 71K. Mailroom was developed in 1988.

  5. 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.

  6. 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.

  7. 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…

  8. 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.

  9. Neural Networks for Rapid Design and Analysis

    NASA Technical Reports Server (NTRS)

    Sparks, Dean W., Jr.; Maghami, Peiman G.

    1998-01-01

    Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.

  10. Peer Intervention Network: A Program for Underachievers.

    ERIC Educational Resources Information Center

    Kehayan, V. Alexander

    Peer Intervention Network (PIN) began in New Jersey in 1980, as a group process intervention for improving the school performance of 7th and 8th grade students with motivational and attitudinal problems which interfered with their learning. Traditionally, these students tend to develop a "delinquent" profile and frequently became…

  11. Automating network meta-analysis.

    PubMed

    van Valkenhoef, Gert; Lu, Guobing; de Brock, Bert; Hillege, Hans; Ades, A E; Welton, Nicky J

    2012-12-01

    Mixed treatment comparison (MTC) (also called network meta-analysis) is an extension of traditional meta-analysis to allow the simultaneous pooling of data from clinical trials comparing more than two treatment options. Typically, MTCs are performed using general-purpose Markov chain Monte Carlo software such as WinBUGS, requiring a model and data to be specified using a specific syntax. It would be preferable if, for the most common cases, both could be derived from a well-structured data file that can be easily checked for errors. Automation is particularly valuable for simulation studies in which the large number of MTCs that have to be estimated may preclude manual model specification and analysis. Moreover, automated model generation raises issues that provide additional insight into the nature of MTC. We present a method for the automated generation of Bayesian homogeneous variance random effects consistency models, including the choice of basic parameters and trial baselines, priors, and starting values for the Markov chain(s). We validate our method against the results of five published MTCs. The method is implemented in freely available open source software. This means that performing an MTC no longer requires manually writing a statistical model. This reduces time and effort, and facilitates error checking of the dataset. Copyright © 2012 John Wiley & Sons, Ltd.

  12. Egocentric Social Network Analysis of Pathological Gambling

    PubMed Central

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

    2012-01-01

    Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641

  13. 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.

  14. Learning oncogenetic networks by reducing to mixed integer linear programming.

    PubMed

    Shahrabi Farahani, Hossein; Lagergren, Jens

    2013-01-01

    Cancer can be a result of accumulation of different types of genetic mutations such as copy number aberrations. The data from tumors are cross-sectional and do not contain the temporal order of the genetic events. Finding the order in which the genetic events have occurred and progression pathways are of vital importance in understanding the disease. In order to model cancer progression, we propose Progression Networks, a special case of Bayesian networks, that are tailored to model disease progression. Progression networks have similarities with Conjunctive Bayesian Networks (CBNs) [1],a variation of Bayesian networks also proposed for modeling disease progression. We also describe a learning algorithm for learning Bayesian networks in general and progression networks in particular. We reduce the hard problem of learning the Bayesian and progression networks to Mixed Integer Linear Programming (MILP). MILP is a Non-deterministic Polynomial-time complete (NP-complete) problem for which very good heuristics exists. We tested our algorithm on synthetic and real cytogenetic data from renal cell carcinoma. We also compared our learned progression networks with the networks proposed in earlier publications. The software is available on the website https://bitbucket.org/farahani/diprog.

  15. A new gradient-based neural network for solving linear and quadratic programming problems.

    PubMed

    Leung, Y; Chen, K Z; Jiao, Y C; Gao, X B; Leung, K S

    2001-01-01

    A new gradient-based neural network is constructed on the basis of the duality theory, optimization theory, convex analysis theory, Lyapunov stability theory, and LaSalle invariance principle to solve linear and quadratic programming problems. In particular, a new function F(x, y) is introduced into the energy function E(x, y) such that the function E(x, y) is convex and differentiable, and the resulting network is more efficient. This network involves all the relevant necessary and sufficient optimality conditions for convex quadratic programming problems. For linear programming and quadratic programming (QP) problems with unique and infinite number of solutions, we have proven strictly that for any initial point, every trajectory of the neural network converges to an optimal solution of the QP and its dual problem. The proposed network is different from the existing networks which use the penalty method or Lagrange method, and the inequality constraints are properly handled. The simulation results show that the proposed neural network is feasible and efficient.

  16. 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…

  17. Regenerative Engine Analysis Program (REAP).

    DTIC Science & Technology

    1981-01-01

    were con- sidered in an effort to identify promising concepts for heli- copter applications. The aero/ thermodynamic characteristics of heat exchangers...AiResearch for small engines. The program, entitled WATE (Weight Analysis of Turbine Engines) accepts as inputs the geometric, thermodynamic ...Military Airplane Development; NASA-Lewis Research Center CR159431, Jan- uary 1979. 27 INPUT: - CONFIGURATION DATA - THERMODYNAMIC DATA - MECHANICAL AND

  18. Ecological network analysis for a virtual water network.

    PubMed

    Fang, Delin; Chen, Bin

    2015-06-02

    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.

  19. PedExpert: a computer program for the application of Bayesian networks to human paternity testing.

    PubMed

    Gomes, R R; Campos, S V A; Pena, S D J

    2009-01-01

    PedExpert is a Windows-based Bayesian network software, especially constructed to solve problems in parentage testing that are complex because of missing genetic information on the alleged father and/or because they involve genetic mutations. PedExpert automates the creation and manipulation of Bayesian networks, implementing algorithms that convert pedigrees and sets of indispensable information (genotypes, allele frequencies, mutation rates) into Bayesian networks. This program has a novel feature that can incorporate information about gene mutations into tables of conditional probabilities of transmission of alleles from the alleged father to the child, without adding new nodes to the network. This permits using the same Bayesian network in different modes, for analysis of cases that include mutations or not. PedExpert is user-friendly and greatly reduces the time of analysis for complex cases of paternity testing, eliminating most sources of logical and operational error.

  20. Measuring Road Network Vulnerability with Sensitivity Analysis

    PubMed Central

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

    2017-01-01

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

  1. 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

  2. Universality in complex networks: random matrix analysis.

    PubMed

    Bandyopadhyay, Jayendra N; Jalan, Sarika

    2007-08-01

    We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory. Second, we show an analogy between the onset of small-world behavior, quantified by the structural properties of networks, and the transition from Poisson to Gaussian orthogonal ensemble statistics, quantified by Brody parameter characterizing a spectral property. We also present our analysis for a protein-protein interaction network in budding yeast.

  3. NOA: a novel Network Ontology Analysis method.

    PubMed

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

    2011-07-01

    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/.

  4. NASA's Aircraft Icing Analysis Program

    NASA Technical Reports Server (NTRS)

    Shaw, R. J.

    1986-01-01

    An overview of the NASA ongoing efforts to develop an aircraft icing analysis capability is presented. Discussions are included of the overall and long term objectives of the program as well as current capabilities and limitations of the various computer codes being developed. Descriptions are given of codes being developed to analyze two and three dimensional trajectories of water droplets, airfoil ice accretion, aerodynamic performance degradation of components and complete aircraft configurations, electrothermal deicer, fluid freezing point depressant antideicer and electro-impulse deicer. The need for bench mark and verification data to support the code development is also discussed, and selected results of experimental programs are presented.

  5. 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.

  6. Tables: A Spreadsheet-Inspired Programming Model for Sensor Networks

    SciTech Connect

    Horey, James L; Maccabe, Arthur Barney; Nelson, Eric

    2010-01-01

    Current programming interfaces for sensor networks often target experienced developers and lack important features. Tables is a spreadsheet inspired programming environment that enables rapid development of complex applications by a wide range of users. Tables emphasizes ease-of-use by employing spreadsheet abstractions, including pivot tables and data-driven functions. Using these tools, users are able to construct applications that incorporate local and collective computation and communication. We evaluate the design and implementation of Tables on the TelosB platform, and show how Tables can be used to construct data monitoring, classification, and object tracking applications. We discuss the relative computation, memory, and network overhead imposed by the Tables environment. With this evaluation, we show that the Tables programming environment represents a feasible alternative to existing programming systems.

  7. HOST structural analysis program overview

    NASA Technical Reports Server (NTRS)

    Thompson, Robert L.

    1986-01-01

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

  8. Networking between community health programs: a team-work approach to improving health service provision

    PubMed Central

    2014-01-01

    Background Networking between non-government organisations in the health sector is recognised as an effective method of improving service delivery. The Uttarakhand Cluster was established in 2008 as a collaboration of community health programs in rural north India with the aim of building capacity, increasing visibility and improving linkages with the government. This qualitative research, conducted between 2011-2012, examined the factors contributing to formation and sustainability of this clustering approach. Methods Annual focus group discussions, indicator surveys and participant observation were used to document and observe the factors involved in the formation and sustainability of an NGO network in North India. Results The analysis demonstrated that relationships were central to the formation and sustainability of the cluster. The elements of small group relationships: forming, storming, norming and performing emerged as a helpful way to describe the phases which have contributed to the functioning of this network with common values, strong leadership, resource sharing and visible progress encouraging the ongoing commitment of programs to the network goals. Conclusions In conclusion, this case study demonstrates an example of a successful and effective network of community health programs. The development of relationships was seen to be to be an important part of promoting effective resource sharing, training opportunities, government networking and resource mobilisation and will be important for other health networks to consider. PMID:25015212

  9. Tracking POD's Engagement with Diversity: A Content Analysis of "To Improve the Academy" and POD Network Conference Programs from 1977 to 2011

    ERIC Educational Resources Information Center

    Grooters, Stacy E.

    2014-01-01

    This study examines the degree to which sessions from the annual Professional and Organizational Development (POD) Network Conference and articles from "To Improve the Academy" engage questions of diversity. The titles and abstracts of 3,946 conference sessions and 560 journal articles were coded for presence and type of diversity. A…

  10. 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

  11. 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.

  12. Industrial entrepreneurial network: Structural and functional analysis

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

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

  13. 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 PRN…

  14. 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…

  15. 77 FR 62243 - Rural Health Network Development Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-10-12

    ...] [FR Doc No: 2012-25195] DEPARTMENT OF HEALTH AND HUMAN SERVICES Health Resources and Services Administration Rural Health Network Development Program AGENCY: Health Resources and Services Administration (HRSA), HHS. ACTION: Notice of Non-competitive Replacement Award to Siloam Springs Regional...

  16. The Network Form of Implementing Educational Programs: Differences and Typology

    ERIC Educational Resources Information Center

    Sobolev, Alexandr Borisovich

    2016-01-01

    The article describes peculiarities of implementation and major differences in network educational programs, currently introduced in Russia. It presents a general typology of models and forms for implementing interaction between educational institutions of Russia, including teacher institutes and federal universities, as well as a typology of…

  17. 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.

  18. 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.

  19. A Layered Social and Operational Network Analysis

    DTIC Science & Technology

    2007-03-01

    Library and Information Science Research, 18: 323 – 342 (1996). Herbranson, Travis. Isolating Key Players in Clandestine Networks. MS thesis...07 A LAYERED SOCIAL AND OPERATIONAL NETWORK ANALYSIS THESIS Presented to the Faculty Department of Operational Sciences ...Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Operations Research Jennifer L. Geffre, BS

  20. 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…

  1. 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.

  2. Artificial Neural Network Analysis System

    DTIC Science & Technology

    2007-11-02

    Target detection, multi-target tracking and threat identification of ICBM and its warheads by sensor fusion and data fusion of sensors in a fuzzy neural network system based on the compound eye of a fly.

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

    PubMed

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

    2015-10-01

    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 a probabilistic model. Starting from an overconnected 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 and we perform experiments on in-vivo magnetic resonance microangiography (μMRA) images of mouse brains. We finally discuss properties of the networks obtained under different tracking and pruning approaches.

  4. Interorganizational networks: fundamental to the Accreditation Canada program.

    PubMed

    Mitchell, Jonathan I; Nicklin, Wendy; MacDonald, Bernadette

    2014-01-01

    Within the Canadian healthcare system, the term population-accountable health network defines the use of collective resources to optimize the health of a population through integrated interventions. The leadership of these networks has also been identified as a critical factor, highlighting the need for creative management of resources in determining effective, balanced sets of interventions. In this article, using specific principles embedded in the Accreditation Canada program, the benefits of a network approach are highlighted, including knowledge sharing, improving the consistency of practice through standards, and a broader systems-and-population view of healthcare delivery across the continuum of care. The implications for Canadian health leaders to leverage the benefits of interorganizational networks are discussed.

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

    DOE PAGES

    Rempfler, Markus; Schneider, Matthias; Ielacqua, Giovanna D.; ...

    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

  6. 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.

  7. 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.

  8. 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…

  9. Don’t Configure the Network, Program It! Domain-Specific Programming Languages for Network Systems

    DTIC Science & Technology

    2010-07-10

    Dynamic access control in enterprise networks. In Proc. Workshop: Research on Enterprise Networking, Barcelona, Spain, Aug. 2009. [11] Opnet ...NetDoctor. http://opnet.com/products/modules/netdoctor.htm. [12] Opnet Modeler. http://opnet.com/products/modeler/opnet_modeler.pdf, 2003. [13] J. Peterson, G

  10. 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.

  11. 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.

  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. Extending stochastic network calculus to loss analysis.

    PubMed

    Luo, Chao; 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.

  14. Statistical Analysis of Bus Networks in India

    PubMed Central

    2016-01-01

    In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590

  15. Statistical Analysis of Bus Networks in India.

    PubMed

    Chatterjee, Atanu; Manohar, Manju; Ramadurai, Gitakrishnan

    2016-01-01

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

  16. 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.

  17. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... unless such dual or multiple networks are composed of two or more persons or entities that, on February 8... 47 Telecommunication 4 2013-10-01 2013-10-01 false Affiliation agreements and network program practices; territorial exclusivity in non-network program arrangements. 73.658 Section...

  18. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... unless such dual or multiple networks are composed of two or more persons or entities that, on February 8... 47 Telecommunication 4 2012-10-01 2012-10-01 false Affiliation agreements and network program practices; territorial exclusivity in non-network program arrangements. 73.658 Section...

  19. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... unless such dual or multiple networks are composed of two or more persons or entities that, on February 8... 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...

  20. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... unless such dual or multiple networks are composed of two or more persons or entities that, on February 8... 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...

  1. 47 CFR 73.658 - Affiliation agreements and network program practices; territorial exclusivity in non-network...

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... stations unless such dual or multiple networks are composed of two or more persons or entities that, on... 47 Telecommunication 4 2014-10-01 2014-10-01 false Affiliation agreements and network program practices; territorial exclusivity in non-network program arrangements. 73.658 Section...

  2. 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.

  3. 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.

  4. Network activity-independent coordinated gene expression program for synapse assembly.

    PubMed

    Valor, Luis M; Charlesworth, Paul; Humphreys, Lawrence; Anderson, Chris N G; Grant, Seth G N

    2007-03-13

    Global biological datasets generated by genomics, transcriptomics, and proteomics provide new approaches to understanding the relationship between the genome and the synapse. Combined transcriptome analysis and multielectrode recordings of neuronal network activity were used in mouse embryonic primary neuronal cultures to examine synapse formation and activity-dependent gene regulation. Evidence for a coordinated gene expression program for assembly of synapses was observed in the expression of 642 genes encoding postsynaptic and plasticity proteins. This synaptogenesis gene expression program preceded protein expression of synapse markers and onset of spiking activity. Continued expression was followed by maturation of morphology and electrical neuronal networks, which was then followed by the expression of activity-dependent genes. Thus, two distinct sequentially active gene expression programs underlie the genomic programs of synapse function.

  5. 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.

  6. 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

  7. 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

  8. 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.

  9. A new model for programming software in body sensor networks.

    PubMed

    de A Barbosa, Talles M G; Sene, Iwens G; da Rocha, Adson F; de O Nascimento, Francisco A A; Carvalho, Joao L A; Carvalho, Hervaldo S

    2007-01-01

    A Body Sensor Network (BSN) must be designed to work autonomously. On the other hand, BSNs need mechanisms that allow changes in their behavior in order to become a clinically useful tool. The purpose of this paper is to present a new programming model that will be useful for programming BSN sensor nodes. This model is based on an intelligent intermediate-level compiler. The main purpose of the proposed compiler is to increase the efficiency in system use, and to increase the lifetime of the application, considering its requirements, hardware possibilities and specialist knowledge. With this model, it is possible to maintain the autonomous operation capability of the BSN and still offer tools that allow users with little grasp on programming techniques to program these systems.

  10. 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.

  11. The portals 4.0.1 network programming interface.

    SciTech Connect

    Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin; 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. Sandias 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

  12. The Portals 4.0 network programming interface.

    SciTech Connect

    Barrett, Brian W.; Brightwell, Ronald Brian; Pedretti, Kevin; 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. Sandias 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.

  13. [Neural network grade program of natural forest protection].

    PubMed

    Luo, Chuanwen; Chen, Yian; Hu, Haiqing; Shen, Hailong; Fan, Shaohui

    2005-06-01

    In this paper, the implement steps of natural forest protection program grading (NFPPG) with neural network (NN) were summarized, and the concepts of program illustration, patch sign unification and regress, and inclining factor were set forth. Employing Arc/Info GIS, the tree species diversity and rarity, disturbance degree, protection of channel system, and classification management in Moershan National Forest Park were described, and, used as the input factors of NN, the relationships between NFPPG and above factors were analyzed. Through artificially determining training samples, the NFFPG of Moershan National Forest Park was built. Tested with all patches in the park, the generalization of NFFPG was satisfied. NFPPG took both the classification management and the protection of forest community types into account, as well as the ecological environments. The excitation function of NFPPG was not seriously saturated, indicating the leading effect of inclining factor on the network optimization.

  14. Dynamic Programming Algorithms and Analyses for Nonserial Networks. Part I.

    DTIC Science & Technology

    1983-01-01

    Journal of Mathematical Analysis and Applications , Vol...Multistage Systems," Journal of Mathematical Analysis and Applications , Vol. 21, 1968, pp. 426-430. 4. Bellman, R.E.,A.O. Esogbue, and I. Nabeshima...the Secondary Optimization Problem in Nonserial Dynamic Programming," Journal of Mathematical Analysis and Applications , Vol. 27, 1969, pp. 565-574.

  15. 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.

  16. Program For Local-Area-Network Electronic Mail

    NASA Technical Reports Server (NTRS)

    Weiner, Michael J.

    1989-01-01

    MailRoom is computer program for local-area network (LAN) electronic mail. Enables users of LAN to exchange electronically notes, letters, reminders, or any sort of communication via their computers. Links all users of LAN into communication circle in which messages created, sent, copied, printed, downloaded, uploaded, and deleted through series of menu-driven screens. Includes feature that enables users to determine whether messages sent have been read by receivers. Written in Microsoft QuickBasic.

  17. A DC programming approach for finding communities in networks.

    PubMed

    Le Thi, Hoai An; Nguyen, Manh Cuong; Dinh, Tao Pham

    2014-12-01

    Automatic discovery of community structures in complex networks is a fundamental task in many disciplines, including physics, biology, and the social sciences. The most used criterion for characterizing the existence of a community structure in a network is modularity, a quantitative measure proposed by Newman and Girvan (2004). The discovery community can be formulated as the so-called modularity maximization problem that consists of finding a partition of nodes of a network with the highest modularity. In this letter, we propose a fast and scalable algorithm called DCAM, based on DC (difference of convex function) programming and DCA (DC algorithms), an innovative approach in nonconvex programming framework for solving the modularity maximization problem. The special structure of the problem considered here has been well exploited to get an inexpensive DCA scheme that requires only a matrix-vector product at each iteration. Starting with a very large number of communities, DCAM furnishes, as output results, an optimal partition together with the optimal number of communities [Formula: see text]; that is, the number of communities is discovered automatically during DCAM's iterations. Numerical experiments are performed on a variety of real-world network data sets with up to 4,194,304 nodes and 30,359,198 edges. The comparative results with height reference algorithms show that the proposed approach outperforms them not only on quality and rapidity but also on scalability. Moreover, it realizes a very good trade-off between the quality of solutions and the run time.

  18. 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

  19. 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.

  20. 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.

  1. Sympatry inference and network analysis in biogeography.

    PubMed

    Dos Santos, Daniel A; Fernández, Hugo R; Cuezzo, María Gabriela; Domínguez, Eduardo

    2008-06-01

    A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes.

  2. 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.

  3. 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.

  4. [Evaluation of the Malaria Evaluation Program in the national laboratory network in Colombia].

    PubMed

    García, Marisol; Mendoza, Nohora

    2002-06-01

    In 1995, the Parasitology Group--National Reference Laboratory--at the Instituto Nacional de Salud (INS) started a national malaria diagnosis program with the Public Health Laboratory Network which included training, indirect quality control, external quality control, technical assistance, advisory, reference and counter-reference, together with an annual review of the program. The purpose of this study was to carry out a three year (1997-1999) analysis of the program. In the indirect quality control program, average positive and negative concordances of 98% and 97%, respectively, and a kappa index of 0.95 were obtained by the state public health laboratories. In the external quality control program, an average concordance of 74.2% was obtained with an 89.2% participation of the registered laboratories. At the municipal level, the indirect quality control had an average concordance of 91.4% in positivity, 92.5% concordance in negativity, and a kappa index of 0.84. On the other hand, indirect quality control has been scarcely implemented by the state public health laboratories in the municipalities under their jurisdiction. In general, the program shows a good performance, despite some economic and conflict-related difficulties in the country, because people responsible at all levels for the Malaria Program have permanently carried out all other activities of the network, either according to annual programming or upon request. However, it is important to improve its coverage and the participation in its activities.

  5. Optical design and analysis program.

    PubMed

    Powell, I

    1978-11-01

    An optical design and analysis program structured for operation on a minicomputer has been developed at NRC (National Research Council of Canada). It has been designed to be used interactively giving the user both flexibility and ease of operation. The computer on which it runs at present is a Digital PDP11 with a memory of around 28K, and this represents a great saving in computer costs when compared with those of a large computer upon which most lens design work is carried out. This program has capabilities for optimizing a lens system, for pupil exploration, for fitting the computed wavefront aberration to a polynomial, and for evaluating the diffraction optical transfer function. Although only ten finite rays are traced in the optimization routine, the aberrations computed, together with the Seidel aberrations obtained from the paraxial ray trace, provide the user with adequate control of the aberrations over both aperture and field. A Double Gauss and a Maksutov-Cassegrain system are used as practical examples to illustrate this.

  6. 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.

  7. 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...

  8. NAPS: Network Analysis of Protein Structures

    PubMed Central

    Chakrabarty, Broto; Parekh, Nita

    2016-01-01

    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

  9. DINGO: differential network analysis in genomics

    PubMed Central

    Ha, Min Jin; Baladandayuthapani, Veerabhadran; Do, Kim-Anh

    2015-01-01

    Motivation: Cancer progression and development are initiated by aberrations in various molecular networks through coordinated changes across multiple genes and pathways. It is important to understand how these networks change under different stress conditions and/or patient-specific groups to infer differential patterns of activation and inhibition. Existing methods are limited to correlation networks that are independently estimated from separate group-specific data and without due consideration of relationships that are conserved across multiple groups. Method: We propose a pathway-based differential network analysis in genomics (DINGO) model for estimating group-specific networks and making inference on the differential networks. DINGO jointly estimates the group-specific conditional dependencies by decomposing them into global and group-specific components. The delineation of these components allows for a more refined picture of the major driver and passenger events in the elucidation of cancer progression and development. Results: Simulation studies demonstrate that DINGO provides more accurate group-specific conditional dependencies than achieved by using separate estimation approaches. We apply DINGO to key signaling pathways in glioblastoma to build differential networks for long-term survivors and short-term survivors in The Cancer Genome Atlas. The hub genes found by mRNA expression, DNA copy number, methylation and microRNA expression reveal several important roles in glioblastoma progression. Availability and implementation: R Package at: odin.mdacc.tmc.edu/∼vbaladan. Contact: veera@mdanderson.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26148744

  10. 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).

  11. 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

  12. Information flow analysis of interactome networks.

    PubMed

    Missiuro, Patrycja Vasilyev; Liu, Kesheng; Zou, Lihua; Ross, Brian C; Zhao, Guoyan; Liu, Jun S; Ge, Hui

    2009-04-01

    Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we combine gene expression

  13. A statistical analysis of UK financial networks

    NASA Astrophysics Data System (ADS)

    Chu, J.; Nadarajah, S.

    2017-04-01

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

  14. 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.

  15. Exploring Complexity of Deliberate Self-Poisoning through Network Analysis

    PubMed Central

    Farahbakhsh, Mostafa; Fein, Rebecca A.; Moftian, Nazila; Nasiry, Zahra

    2017-01-01

    The purpose of this research was to examine the complexity of circumstances that result in deliberate self-poisoning cases. For the purposes of this paper, the cases were patients that presented for care and were admitted to the specialty hospital in Northwest of Iran. The research examined the problems preceding deliberate self-poisoning and the interrelations among them by applying network analysis methods. The network was scored for degrees of centrality and betweenness centrality. Structural analysis of network also was conducted using block modelling. The results showed that family conflicts had the highest score for degree of centrality among women, while the highest score for degree of centrality among men belonged to those dealing with drug addiction. Analysis for degree of betweenness centrality revealed that drug addiction had the highest score among men, whereas the highest score for women on betweenness centrality was related to physical illness. Structural analysis of the network showed differences in role that various problems played in intentional self-poisoning. The findings from this research can be used by public health authorities to create prevention programs that address the problems leading to deliberate self-poisoning. PMID:28251146

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. MICTPT - A minicomputer general-purpose microwave two-port analysis program

    NASA Technical Reports Server (NTRS)

    Olson, D. H.; Rosenbaum, F. J.

    1974-01-01

    The implementation of a microwave network-analysis program for computers with 4K words of memory is described. The program is capable of the frequency analysis of networks which include interconnections of lumped elements, transmission lines, waveguides, and any two-port which is described by the elements of a scattering matrix. The network can be described mnemonically rather than by numerical codes. For each frequency in the range, the entire network is collapsed into a single equivalent A matrix, and the input impedance and other characteristics are calculated.

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

    PubMed

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

    2015-03-10

    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.

  2. Water Quality Analysis Simulation Program (WASP)

    EPA Pesticide Factsheets

    The Water Quality Analysis Simulation Program (WASP7) model helps users interpret and predict water quality responses to natural phenomena and manmade pollution for various pollution management decisions.

  3. 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).

  4. Complex network analysis of time series

    NASA Astrophysics Data System (ADS)

    Gao, Zhong-Ke; Small, Michael; Kurths, Jürgen

    2016-12-01

    Revealing complicated behaviors from time series constitutes a fundamental problem of continuing interest and it has attracted a great deal of attention from a wide variety of fields on account of its significant importance. The past decade has witnessed a rapid development of complex network studies, which allow to characterize many types of systems in nature and technology that contain a large number of components interacting with each other in a complicated manner. Recently, the complex network theory has been incorporated into the analysis of time series and fruitful achievements have been obtained. Complex network analysis of time series opens up new venues to address interdisciplinary challenges in climate dynamics, multiphase flow, brain functions, ECG dynamics, economics and traffic systems.

  5. Application of the CINGEN program a thermal network data generator

    NASA Technical Reports Server (NTRS)

    Shultz, W. E.; Schmitz, R. P.

    1975-01-01

    The application of the CINGEN computer program and two of its supporting programs for the evaluation of structural and thermal performance of physical systems was described. The CINGEN program was written and implemented to avoid the duplication effort of performing a finite element approach for structural analysis and a finite differencing technique for thermal analysis, as well as the desire for a geometrical representation of the thermal model to reduce modeling errors. The program simplifies the thermal modeling process by performing all of the capacitance and conductance calculations normally done by the analyst. Each solid element is divided into five tetrahedrons, allowing the total volume to be calculated precisely. A sample problem was illustrated.

  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. Network Analysis in Comparative Social Sciences

    ERIC Educational Resources Information Center

    Vera, Eugenia Roldan; Schupp, Thomas

    2006-01-01

    This essay describes the pertinence of Social Network Analysis (SNA) for the social sciences in general, and discusses its methodological and conceptual implications for comparative research in particular. The authors first present a basic summary of the theoretical and methodological assumptions of SNA, followed by a succinct overview of its…

  8. Ecological network analysis of China's societal metabolism.

    PubMed

    Zhang, Yan; Liu, Hong; Li, Yating; Yang, Zhifeng; Li, Shengsheng; Yang, Naijin

    2012-01-01

    Uncontrolled socioeconomic development has strong negative effects on the ecological environment, including pollution and the depletion and waste of natural resources. These serious consequences result from the high flows of materials and energy through a socioeconomic system produced by exchanges between the system and its surroundings, causing the disturbance of metabolic processes. In this paper, we developed an ecological network model for a societal system, and used China in 2006 as a case study to illustrate application of the model. We analyzed China's basic metabolic processes and used ecological network analysis to study the network relationships within the system. Basic components comprised the internal environment, five sectors (agriculture, exploitation, manufacturing, domestic, and recycling), and the external environment. We defined 21 pairs of ecological relationships in China's societal metabolic system (excluding self-mutualism within a component). Using utility and throughflow analysis, we found that exploitation, mutualism, and competition relationships accounted for 76.2, 14.3, and 9.5% of the total relationships, respectively. In our trophic level analysis, the components were divided into producers, consumers, and decomposers according to their positions in the system. Our analyses revealed ways to optimize the system's structure and adjust its functions, thereby promoting healthier socioeconomic development, and suggested ways to apply ecological network analysis in future socioeconomic research.

  9. 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.

  10. Persistent ISR: the social network analysis connection

    NASA Astrophysics Data System (ADS)

    Bowman, Elizabeth K.

    2012-06-01

    Persistent surveillance provides decision makers with unprecedented access to multisource data collected from humans and sensor assets around the globe, yet these data exist in the physical world and provide few overt clues to meaning behind actions. In this paper we explore the recent growth in online social networking and ask the questions: 1) can these sites provide value-added information to compliment physical sensing and 2) what are the mechanisms by which these data could inform situational awareness and decision making? In seeking these answers we consider the range of options provided by Social Network Analysis (SNA), and focus especially on the dynamic nature of these networks. In our discussion we focus on the wave of reform experienced by the North African nations in early 2011 known as the Arab Spring. Demonstrators made widespread use of social networking applications to coordinate, document, and publish material to aid their cause. Unlike members of covert social networks who hide their activity and associations, these demonstrators openly posted multimedia information to coordinate activity and stimulate global support. In this paper we provide a review of SNA approaches and consider how one might track network adaptations by capturing temporal and conceptual trends. We identify opportunities and challenges for merging SNA with physical sensor output, and conclude by addressing future challenges in the persistent ISR domain with respect to SNA.

  11. Link-space formalism for network analysis.

    PubMed

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

    2008-03-01

    We introduce the link-space formalism for analyzing network models with degree-degree correlations. The formalism is based on a statistical description of the fraction of links l(i,j) connecting nodes of degrees i and j. To demonstrate its use, we apply the framework to some pedagogical network models, namely, random attachment, Barabási-Albert preferential attachment, and the classical Erdos and Rényi random graph. For these three models the link-space matrix can be solved analytically. We apply the formalism to a simple one-parameter growing network model whose numerical solution exemplifies the effect of degree-degree correlations for the resulting degree distribution. We also employ the formalism to derive the degree distributions of two very simple network decay models, more specifically, that of random link deletion and random node deletion. The formalism allows detailed analysis of the correlations within networks and we also employ it to derive the form of a perfectly nonassortative network for arbitrary degree distribution.

  12. Diversity Performance Analysis on Multiple HAP Networks

    PubMed Central

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

    2015-01-01

    One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102

  13. Extracting Embedded Generalized Networks from Linear Programming Problems.

    DTIC Science & Technology

    1984-09-01

    E EXTRACTING EMBEDDED GENERALIZED NETWORKS FROM LINEAR PROGRAMMING PROBLEMS by Gerald G. Brown * . ___Richard D. McBride * R. Kevin Wood LcL7...authorized. EA Gerald ’Brown Richar-rD. McBride 46;val Postgrduate School University of Southern California Monterey, California 93943 Los Angeles...REOT UBE . OV S.SF- PERFOING’ CAORG soN UER. 7. AUTNOR(a) S. CONTRACT ON GRANT NUME111() Gerald G. Brown Richard D. McBride S. PERFORMING ORGANIZATION

  14. 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

  15. USING SOCIAL NETWORK ANALYSIS TO EVALUATE COMMUNITY CAPACITY BUILDING OF A REGIONAL COMMUNITY CANCER NETWORK

    PubMed Central

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

    2013-01-01

    The Tampa Bay Community Cancer Network (TBCCN) is one of 25 Community Network Programs funded by the National Cancer Institute’s (NCI’s) Center to Reduce Cancer Health Disparities with the objectives to create a collaborative infrastructure of academic and community based organizations and to develop effective and sustainable interventions to reduce cancer health disparities. In order to describe the network characteristics of the TBCCN as part of our ongoing evaluation efforts, we conducted social network analysis surveys with our community partners in 2007 and 2008. One key finding showed that the mean trust value for the 20 community partners in the study increased from 1.8 to 2.1 (p<0.01), suggesting a trend toward increased trust in the network. These preliminary results suggest that TBCCN has led to greater collaboration among the community partners that were formed through its capacity-building and evidence-based dissemination activities for impacting cancer health disparities at the community level. PMID:24049217

  16. 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…

  17. The USA-National Phenology Network Biophysical Program

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    SciTech Connect

    1995-09-16

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

  19. 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.

  20. FORTRAN computer program for seismic risk analysis

    USGS Publications Warehouse

    McGuire, Robin K.

    1976-01-01

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

  1. A Korean Space Situational Awareness Program : OWL Network

    NASA Astrophysics Data System (ADS)

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

    2012-09-01

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

  2. Social Network Analysis in Frontier Capital Markets

    DTIC Science & Technology

    2012-06-01

    generate results efficiently. References [Bor03] Stephen Borgatti . The key player problem. In Dynamic Social Network Modeling and Analysis: workshop...form of the equation for determining the centralization of a network is given by CX = ∑N i=1[CX( p ∗)− CX(pi)] max ∑N i=1[CX( p ∗)− CX(pi)] , (6) the...following equation: CD = ∑N i=1[CD( p ∗)− CD(pi)] (N − 1)(N − 2) . Here the maximum possible sum of differences in the denominator in (6) is given by

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  4. Programs for control of an analog-signal switching network

    SciTech Connect

    D'Ottavio, T.; Enriquez, R.; Katz, R.; Skelly, J.

    1989-01-01

    A suite of programs has been developed to control the network of analog-signal switching multiplexers in the AGS complex. The software is driven by a relational database which describes the architecture of the multiplexer tree and the set of available analog signals. Signals are routed through a three-layer multiplexer tree, to be made available at four consoles each with three 4-trace oscilloscopes. A menu-structured operator interface program is available at each console, to accept requests to route any available analog signal to any of that console's 12 oscilloscope traces. A common routing-server program provides automatic routing-server program provides automatic routing of requested signals through the layers of multiplexers, maintaining a reservation database to denote free and in-use trunks. Expansion of the analog signal system is easily accommodated in software by adding new signals, trunks, multiplexers, or consoles to the database. Programmatic control of the triggering signals for each of the oscilloscopes is also provided. 3 refs., 4 figs., 3 tabs.

  5. 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.

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

    PubMed

    Coyle, Scott M

    2016-07-02

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

  7. 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

  8. 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.

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

    ERIC Educational Resources Information Center

    Thornton, Teresa; Leahy, Jessica

    2012-01-01

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

  10. Analysis of cascading failure in gene networks.

    PubMed

    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.

  11. Complex networks analysis of language complexity

    NASA Astrophysics Data System (ADS)

    Amancio, Diego R.; Aluisio, Sandra M.; Oliveira, Osvaldo N., Jr.; Costa, Luciano da F.

    2012-12-01

    Methods from statistical physics, such as those involving complex networks, have been increasingly used in the quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus pointing to the usefulness of considering wider contexts around the concepts. Though the accuracy rate in the distinction was not as high as in methods using deep linguistic knowledge, the complex network approach is still useful for a rapid screening of texts whenever assessing complexity is essential to guarantee accessibility to readers with limited reading ability.

  12. (13)C NMR Metabolomics: INADEQUATE Network Analysis.

    PubMed

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

    2015-06-02

    The many advantages of (13)C NMR are often overshadowed by its intrinsically low sensitivity. Given that carbon makes up the backbone of most biologically relevant molecules, (13)C NMR offers a straightforward measurement of these compounds. Two-dimensional (13)C-(13)C 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 semiautomated approach called INETA (INADEQUATE network analysis) for the untargeted analysis of INADEQUATE data sets using an in silico INADEQUATE database. We demonstrate this approach using isotopically labeled Caenorhabditis elegans mixtures.

  13. 75 FR 55360 - Networking and Information Technology Research and Development (NITRD) Program: Draft NITRD 2010...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-09-10

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

  14. 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... Technology Research and Development (NITRD). ACTION: Notice, request for public comment. FOR FURTHER... Coordination Office for Networking and Information Technology Research and Development (NITRD)...

  15. 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.

  16. 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…

  17. NOLIN: A nonlinear laminate analysis program

    NASA Technical Reports Server (NTRS)

    Kibler, J. J.

    1975-01-01

    A nonlinear, plane-stress, laminate analysis program, NOLIN, was developed which accounts for laminae nonlinearity under inplane shear and transverse extensional stress. The program determines the nonlinear stress-strain behavior of symmetric laminates subjected to any combination of inplane shear and biaxial extensional loadings. The program has the ability to treat different stress-strain behavior in tension and compression, and predicts laminate failure using any or all of maximum stress, maximum strain, and quadratic interaction failure criteria. A brief description of the program is presented including discussion of the flow of information and details of the input required. Sample problems and a complete listing of the program is also provided.

  18. On control of singleton attractors in multiple Boolean networks: integer programming-based method

    PubMed Central

    2014-01-01

    Background Boolean network (BN) is a mathematical model for genetic network and control of genetic networks has become an important issue owing to their potential application in the field of drug discovery and treatment of intractable diseases. Early researches have focused primarily on the analysis of attractor control for a randomly generated BN. However, one may also consider how anti-cancer drugs act in both normal and cancer cells. Thus, the development of controls for multiple BNs is an important and interesting challenge. Results In this article, we formulate three novel problems about attractor control for two BNs (i.e., normal cell and cancer cell). The first is about finding a control that can significantly damage cancer cells but has a limited damage to normal cells. The second is about finding a control for normal cells with a guaranteed damaging effect on cancer cells. Finally, we formulate a definition for finding a control for cancer cells with limited damaging effect on normal cells. We propose integer programming-based methods for solving these problems in a unified manner, and we conduct computational experiments to illustrate the efficiency and the effectiveness of our method for our multiple-BN control problems. Conclusions We present three novel control problems for multiple BNs that are realistic control models for gene regulation networks and adopt an integer programming approach to address these problems. Experimental results indicate that our proposed method is useful and effective for moderate size BNs. PMID:24565276

  19. A novel recurrent neural network with finite-time convergence for linear programming.

    PubMed

    Liu, Qingshan; Cao, Jinde; Chen, Guanrong

    2010-11-01

    In this letter, a novel recurrent neural network based on the gradient method is proposed for solving linear programming problems. Finite-time convergence of the proposed neural network is proved by using the Lyapunov method. Compared with the existing neural networks for linear programming, the proposed neural network is globally convergent to exact optimal solutions in finite time, which is remarkable and rare in the literature of neural networks for optimization. Some numerical examples are given to show the effectiveness and excellent performance of the new recurrent neural network.

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

    NASA Technical Reports Server (NTRS)

    Rose, J. R.

    1978-01-01

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

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

    ERIC Educational Resources Information Center

    Lewis, Mary G., Comp.

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

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

    ERIC Educational Resources Information Center

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

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

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

    ERIC Educational Resources Information Center

    Sivertsen, Mary Lewis, Comp.

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

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

    ERIC Educational Resources Information Center

    Lewis, Mary G., Comp.

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

  5. Network analysis in public health: history, methods, and applications.

    PubMed

    Luke, Douglas A; Harris, Jenine K

    2007-01-01

    Network analysis is an approach to research that is uniquely suited to describing, exploring, and understanding structural and relational aspects of health. It is both a methodological tool and a theoretical paradigm that allows us to pose and answer important ecological questions in public health. In this review we trace the history of network analysis, provide a methodological overview of network techniques, and discuss where and how network analysis has been used in public health. We show how network analysis has its roots in mathematics, statistics, sociology, anthropology, psychology, biology, physics, and computer science. In public health, network analysis has been used to study primarily disease transmission, especially for HIV/AIDS and other sexually transmitted diseases; information transmission, particularly for diffusion of innovations; the role of social support and social capital; the influence of personal and social networks on health behavior; and the interorganizational structure of health systems. We conclude with future directions for network analysis in public health.

  6. 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.

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

    NASA Technical Reports Server (NTRS)

    Walter, Steven J.

    1994-01-01

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

  8. 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.

  9. 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).

  10. 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.

  11. A high-performance feedback neural network for solving convex nonlinear programming problems.

    PubMed

    Leung, Yee; Chen, Kai-Zhou; Gao, Xing-Bao

    2003-01-01

    Based on a new idea of successive approximation, this paper proposes a high-performance feedback neural network model for solving convex nonlinear programming problems. Differing from existing neural network optimization models, no dual variables, penalty parameters, or Lagrange multipliers are involved in the proposed network. It has the least number of state variables and is very simple in structure. In particular, the proposed network has better asymptotic stability. For an arbitrarily given initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem under no more than the standard assumptions. In addition, the network can also solve linear programming and convex quadratic programming problems, and the new idea of a feedback network may be used to solve other optimization problems. Feasibility and efficiency are also substantiated by simulation examples.

  12. NASA Multidisciplinary Design and Analysis Fellowship Program

    NASA Technical Reports Server (NTRS)

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

    1999-01-01

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

  13. Shuttle Electrical Power Analysis Program (SEPAP); single string circuit analysis report

    NASA Technical Reports Server (NTRS)

    Murdock, C. R.

    1974-01-01

    An evaluation is reported of the data obtained from an analysis of the distribution network characteristics of the shuttle during a spacelab mission. A description of the approach utilized in the development of the computer program and data base is provided and conclusions are drawn from the analysis of the data. Data sheets are provided for information to support the detailed discussion on each computer run.

  14. Mask Analysis Program (MAP) reference manual

    NASA Technical Reports Server (NTRS)

    Mitchell, C. L.

    1976-01-01

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

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

    USGS Publications Warehouse

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

    2006-01-01

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

  16. Transcriptional master regulator analysis in breast cancer genetic networks.

    PubMed

    Tovar, Hugo; García-Herrera, Rodrigo; Espinal-Enríquez, Jesús; Hernández-Lemus, Enrique

    2015-12-01

    Gene regulatory networks account for the delicate mechanisms that control gene expression. Under certain circumstances, gene regulatory programs may give rise to amplification cascades. Such transcriptional cascades are events in which activation of key-responsive transcription factors called master regulators trigger a series of gene expression events. The action of transcriptional master regulators is then important for the establishment of certain programs like cell development and differentiation. However, such cascades have also been related with the onset and maintenance of cancer phenotypes. Here we present a systematic implementation of a series of algorithms aimed at the inference of a gene regulatory network and analysis of transcriptional master regulators in the context of primary breast cancer cells. Such studies were performed in a highly curated database of 880 microarray gene expression experiments on biopsy-captured tissue corresponding to primary breast cancer and healthy controls. Biological function and biochemical pathway enrichment analyses were also performed to study the role that the processes controlled - at the transcriptional level - by such master regulators may have in relation to primary breast cancer. We found that transcription factors such as AGTR2, ZNF132, TFDP3 and others are master regulators in this gene regulatory network. Sets of genes controlled by these regulators are involved in processes that are well-known hallmarks of cancer. This kind of analyses may help to understand the most upstream events in the development of phenotypes, in particular, those regarding cancer biology.

  17. Finite-Element Composite-Analysis Program

    NASA Technical Reports Server (NTRS)

    Bowles, David E.

    1990-01-01

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

  18. Designing Your Own Rasch Analysis Program.

    ERIC Educational Resources Information Center

    Linacre, John M.

    Advantages and disadvantages of standard Rasch analysis computer programs are discussed. The unconditional maximum likelihood algorithm allows all observations to participate equally in determining the measures and calibrations to be obtained quickly from a data set. On the advantage side, standard Rasch programs can be used immediately, are…

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

    NASA Technical Reports Server (NTRS)

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

    1994-01-01

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

  20. 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.

  1. Network meta-analysis: an introduction for clinicians.

    PubMed

    Rouse, Benjamin; Chaimani, Anna; Li, Tianjing

    2017-02-01

    Network meta-analysis is a technique for comparing multiple treatments simultaneously in a single analysis by combining direct and indirect evidence within a network of randomized controlled trials. Network meta-analysis may assist assessing the comparative effectiveness of different treatments regularly used in clinical practice and, therefore, has become attractive among clinicians. However, if proper caution is not taken in conducting and interpreting network meta-analysis, inferences might be biased. The aim of this paper is to illustrate the process of network meta-analysis with the aid of a working example on first-line medical treatment for primary open-angle glaucoma. We discuss the key assumption of network meta-analysis, as well as the unique considerations for developing appropriate research questions, conducting the literature search, abstracting data, performing qualitative and quantitative synthesis, presenting results, drawing conclusions, and reporting the findings in a network meta-analysis.

  2. Program for Nonlinear Structural Analysis

    DTIC Science & Technology

    1981-09-01

    November 1970. 2. R. E. Jones and W. L. Salus , "Survey and Development of Finite Elements for Nonlineer Structural Analysis", Volume II, "Nonlinear Shell...1970. 2. R. E. Jones and W. L. Salus , "Survey and Development of Finite Elements for Nonlinear Structural Analysis," Volume II, "Nonlinear Shell

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

    NASA Astrophysics Data System (ADS)

    Yelles, Abdelkarim; Allili, Toufik; Alili, Azouaou

    2013-04-01

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

  4. Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation

    DTIC Science & Technology

    2014-08-01

    SUBTITLE Analysis of Cisco Open Network Environment (ONE) OpenFlow Controller Implementation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ...device. Proprietary control plane, with its closed application programming interface (API) and hidden data plane, has become a great hurdle in...Working in conjunction with an open API, OpenFlow allows the user to interface with the controller and provides remote programming of the forwarding

  5. Integrative bayesian network analysis of genomic data.

    PubMed

    Ni, Yang; Stingo, Francesco C; Baladandayuthapani, Veerabhadran

    2014-01-01

    Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.

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

    NASA Astrophysics Data System (ADS)

    Kong, Changduk; Koo, Youngju

    2011-04-01

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

  7. Networking between community health programs: a case study outlining the effectiveness, barriers and enablers

    PubMed Central

    2012-01-01

    Background In India, since the 1990s, there has been a burgeoning of NGOs involved in providing primary health care. This has resulted in a complex NGO-Government interface which is difficult for lone NGOs to navigate. The Uttarakhand Cluster, India, links such small community health programs together to build NGO capacity, increase visibility and better link to the government schemes and the formal healthcare system. This research, undertaken between 1998 and 2011, aims to examine barriers and facilitators to such linking, or clustering, and the effectiveness of this clustering approach. Methods Interviews, indicator surveys and participant observation were used to document the process and explore the enablers, the barriers and the effectiveness of networks improving community health. Results The analysis revealed that when activating, framing, mobilising and synthesizing the Uttarakhand Cluster, key brokers and network players were important in bridging between organisations. The ties (or relationships) that held the cluster together included homophily around common faith, common friendships and geographical location and common mission. Self interest whereby members sought funds, visibility, credibility, increased capacity and access to trainings was also a commonly identified motivating factor for networking. Barriers to network synthesizing included lack of funding, poor communication, limited time and lack of human resources. Risk aversion and mistrust remained significant barriers to overcome for such a network. Conclusions In conclusion, specific enabling factors allowed the clustering approach to be effective at increasing access to resources, creating collaborative opportunities and increasing visibility, credibility and confidence of the cluster members. These findings add to knowledge regarding social network formation and collaboration, and such knowledge will assist in the conceptualisation, formation and success of potential health networks in India

  8. User's guide to the culvert analysis program

    USGS Publications Warehouse

    Fulford, Janice M.

    1995-01-01

    This user's guide contains information on using the culvert analysis program (CAP). The procedure used is based on that presented in Techniques of Water- Resources Investigations of the United States Geological Survey, book 3, chapter A3, "Measurement of Peak Discharge at Culverts by Indirect Methods." The program uses input files that have formats compatible with those used by the Water-Surface Profile (WSPRO) program. The program can be used to compute rating surfaces or curves that describe the behavior of flow through a culvert or to compute discharges from measurements of upstream and downstream water-surface elevations.

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

    SciTech Connect

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

    1981-02-01

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

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

    USGS Publications Warehouse

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

    2014-01-01

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

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

    USGS Publications Warehouse

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

    2010-01-01

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

  12. SURE reliability analysis: Program and mathematics

    NASA Technical Reports Server (NTRS)

    Butler, Ricky W.; White, Allan L.

    1988-01-01

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

  13. Understanding resilience in industrial symbiosis networks: insights from network analysis.

    PubMed

    Chopra, Shauhrat S; Khanna, Vikas

    2014-08-01

    Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks.

  14. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

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

  15. Gap analysis of the European Earth Observation Networks

    NASA Astrophysics Data System (ADS)

    Closa, Guillem; Serral, Ivette; Maso, Joan

    2016-04-01

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

  16. Checking the reliability of a linear-programming based approach towards detecting community structures in networks.

    PubMed

    Chen, W Y C; Dress, A W M; Yu, W Q

    2007-09-01

    Here, the reliability of a recent approach to use parameterised linear programming for detecting community structures in network has been investigated. Using a one-parameter family of objective functions, a number of "perturbation experiments' document that our approach works rather well. A real-life network and a family of benchmark network are also analysed.

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

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

    NASA Technical Reports Server (NTRS)

    1976-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Wong, M. D.

    1974-01-01

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

  20. A new one-layer neural network for linear and quadratic programming.

    PubMed

    Gao, Xingbao; Liao, Li-Zhi

    2010-06-01

    In this paper, we present a new neural network for solving linear and quadratic programming problems in real time by introducing some new vectors. The proposed neural network is stable in the sense of Lyapunov and can converge to an exact optimal solution of the original problem when the objective function is convex on the set defined by equality constraints. Compared with existing one-layer neural networks for quadratic programming problems, the proposed neural network has the least neurons and requires weak stability conditions. The validity and transient behavior of the proposed neural network are demonstrated by some simulation results.

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    PubMed

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

    2014-12-01

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

  3. A national streamflow network gap analysis

    USGS Publications Warehouse

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

    2013-01-01

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

  4. Network Analysis of Social Interactions in Laboratories

    NASA Astrophysics Data System (ADS)

    Warren, Aaron R.

    2008-10-01

    An ongoing study of the structure, function, and evolution of individual activity within lab groups is introduced. This study makes extensive use of techniques from social network analysis. These techniques allow rigorous quantification and hypothesis-testing of the interactions inherent in social groups and the impact of intrinsic characteristics of individuals on their social interactions. As these techniques are novel within the physics education research community, an overview of their meaning and application is given. We then present preliminary results from videotaped laboratory groups involving mixed populations of traditional and non-traditional students in an introductory algebra-based physics course.

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

    PubMed

    Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie

    2015-06-01

    End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital.

  6. A class of finite-time dual neural networks for solving quadratic programming problems and its k-winners-take-all application.

    PubMed

    Li, Shuai; Li, Yangming; Wang, Zheng

    2013-03-01

    This paper presents a class of recurrent neural networks to solve quadratic programming problems. Different from most existing recurrent neural networks for solving quadratic programming problems, the proposed neural network model converges in finite time and the activation function is not required to be a hard-limiting function for finite convergence time. The stability, finite-time convergence property and the optimality of the proposed neural network for solving the original quadratic programming problem are proven in theory. Extensive simulations are performed to evaluate the performance of the neural network with different parameters. In addition, the proposed neural network is applied to solving the k-winner-take-all (k-WTA) problem. Both theoretical analysis and numerical simulations validate the effectiveness of our method for solving the k-WTA problem.

  7. The nuclear analysis program at MURR

    SciTech Connect

    Glascock, M.D. )

    1993-01-01

    The University of Missouri-Columbia (MU) has continually upgraded research facilities and programs at the MU research reactor (MURR) throughout its 26-yr history. The Nuclear Analysis Program (NAP) area has participated in these upgrades over the years. As one of the largest activation analysis laboratories on a university campus, the activities of the NAP are broadly representative of the diversity of applications for activation analysis and related nuclear science. This paper describes the MURR's NAP and several of the research, education, and service projects in which the laboratory is currently engaged.

  8. Energy Analysis Program 1990 annual report

    SciTech Connect

    Not Available

    1992-01-01

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

  9. Towards Distributed Memory Parallel Program Analysis

    SciTech Connect

    Quinlan, D; Barany, G; Panas, T

    2008-06-17

    This paper presents a parallel attribute evaluation for distributed memory parallel computer architectures where previously only shared memory parallel support for this technique has been developed. Attribute evaluation is a part of how attribute grammars are used for program analysis within modern compilers. Within this work, we have extended ROSE, a open compiler infrastructure, with a distributed memory parallel attribute evaluation mechanism to support user defined global program analysis required for some forms of security analysis which can not be addressed by a file by file view of large scale applications. As a result, user defined security analyses may now run in parallel without the user having to specify the way data is communicated between processors. The automation of communication enables an extensible open-source parallel program analysis infrastructure.

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

    PubMed

    Pagadrai, Sasikanth; Yilmaz, Muhittin; Valluri, Pratyush

    2016-08-01

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

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

    PubMed Central

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

    2008-01-01

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

  12. Sediment Analysis Network for Decision Support (SANDS)

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

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

    ERIC Educational Resources Information Center

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

    2014-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  15. Spatial analysis using unsupervised neural networks

    NASA Astrophysics Data System (ADS)

    Murnion, Shane D.

    1996-11-01

    Site selection case studies are often used in training exercises or demonstrations to illustrate the advantages of using a geographical information system (GIS). A typical site selection case study might answer the question "where should I locate a new convenience store?" Current GIS can solve spatial analysis problems that are well defined efficiently. Unfortunately many "real world" problems are poorly defined, for example combinatorial spatial optimisation problems. In these problems the value of any solution depends on a number of factors, each of which must be changed and tested to generate an optimum solution. The large number of possible combinations that must be examined can render such problems insoluble using conventional analysis techniques. In this paper an example of a combinatorial spatial optimisation problem, which is nonpolynomial complete in nature, is examined. The problem can be defined as finding the optimum location for multiple retail sites, where the chosen retail sites will compete with each other for customers. It is shown that a solution can be determined using a relatively unsophisticated unsupervised Hopfield neural network algorithm. The neural network solution is generated within an efficient time-frame and it is shown that counter-intuitively, the algorithm becomes more efficient as the complexity of the problem increases.

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  17. Modeling and Analysis of Modular Structure in Diverse Biological Networks.

    PubMed

    Bader, Al-Anzi; Sherif, Gerges; Noah, Olsman; Christopher, Ormerod; Georgios, Piliouras; John, Ormerod; Kai, Zinn

    2017-04-07

    Biological networks, like most engineered networks, are not the product of a singular design but rather are the result of a long process of refinement and optimization. Many large real-world networks are comprised of well-defined and meaningful smaller modules. While engineered networks are designed and refined by humans with particular goals in mind, biological networks are created by the selective pressures of evolution. In this paper, we seek to define aspects of network architecture that are shared among different types of evolved biological networks. First, we developed a new mathematical model, the Stochastic Block Model with Path Selection (SBM-PS) that simulates biological network formation based on the selection of edges that increase clustering. SBM-PS can produce modular networks whose properties resemble those of real networks. Second, we analyzed three real networks of very different types, and showed that all three can be fit well by the SBM-PS model. Third, we showed that modular elements within the three networks correspond to meaningful biological structures. The networks chosen for analysis were a proteomic network composed of all proteins required for mitochondrial function in budding yeast, a mesoscale anatomical network composed of axonal connections among regions of the mouse brain, and the connectome of individual neurons in the nematode C. elegans. We find that the three networks have common architectural features, and each can be divided into subnetworks with characteristic topologies that control specific phenotypic outputs.

  18. Traffic chaotic dynamics modeling and analysis of deterministic network

    NASA Astrophysics Data System (ADS)

    Wu, Weiqiang; Huang, Ning; Wu, Zhitao

    2016-07-01

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

  19. Energy analysis program, FY 1979

    NASA Astrophysics Data System (ADS)

    1980-04-01

    Energy analysis attempts to understand the volitional choices of energy use and supply available to human society, and the multi-faceted consequences of choosing any one of them. Topics deal with economic impacts; assessments of regional issues and impacts; air quality evaluation; institutional and political issues in California power plant siting; assessment of environmental standards; water issues; characterization of aquatic systems dissolved oxygen profiles; modeling; computer-generated interactive graphics; energy assessment in Hawaii; solar energy in communities; utilities solar financial data; population impacts of geothermal development; energy conservation in colleges and residential sectors; energy policy; decision making; building energy performance standards; standards for residential appliances; and impact of energy performance standards on demand for peak electrical energy.

  20. Vehicle dynamic analysis using neuronal network algorithms

    NASA Astrophysics Data System (ADS)

    Oloeriu, Florin; Mocian, Oana

    2014-06-01

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

  1. Honeycomb: Visual Analysis of Large Scale Social Networks

    NASA Astrophysics Data System (ADS)

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

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

  2. Use of artificial neural network for spatial rainfall analysis

    NASA Astrophysics Data System (ADS)

    Paraskevas, Tsangaratos; Dimitrios, Rozos; Andreas, Benardos

    2014-04-01

    In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.

  3. Compressing Test and Evaluation by Using Flow Data for Scalable Network Traffic Analysis

    DTIC Science & Technology

    2014-10-01

    For example, low quality of service may be caused by many factors including high traffic volume (and associated congestion ), proximity of sender...Scalable Network Traffic Analysis 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER...by ANSI Std Z39-18 788Defense ARJ, October 2014, Vol. 21 No. 4 : 788–802 Compressing Test and Evaluation by Using Data for Scalable Network Traffic

  4. Weighted network analysis of earthquake seismic data

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  5. Space station interior noise analysis program

    NASA Astrophysics Data System (ADS)

    Stusnick, E.; Burn, M.

    1987-02-01

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

  6. Space station interior noise analysis program

    NASA Technical Reports Server (NTRS)

    Stusnick, E.; Burn, M.

    1987-01-01

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

  7. OPTI - OPTICAL COMMUNICATIONS LINK ANALYSIS PROGRAM

    NASA Technical Reports Server (NTRS)

    Marshall, W. K.

    1994-01-01

    The Optical Communication Link Analysis Program, OPTI, analyzes optical and near-infrared communication links that use pulse position modulation (PPM) and direct detection. The program prompts for inputs of system component parameters, modulation format and other operational parameters, background noise sources, and the desired link bit error rate. From these inputs, link margin is determined and a link design control table (DCT) is generated. The program also allows the user to save sets of input parameters defining a given link and read them back into the program at a later time. Further, the program has the capability of altering automatically any of the input parameters to achieve a desired link margin. The program provides a table of extended background sources, e.g. planets, the moon, and the sun. To compute background noise, only the distance from the receiver to the noise source(s) must be entered. This determines whether or not the whole object is in the field-of-view. The program assumes that each object is a blackbody (at 5900K) with an overall visible magnitude scaled to match the tabulated data. Also provided is a table of 19 bright stars. If the noise source is one or several of these, then only the name(s) of the star(s) are required. Noise sources that are not among those contained in the program can be entered as "additional noise sources". In this case required information includes whether or not the source is a point or extended source, its radiance (for extended sources) or irradiance, and receiver to source distance in A.U. (for point sources). The OPTI program is written in FORTRAN-77 and was designed to be used on the IBM PC and PC/AT personal computers. (Note: The 8087/80287 math coprocessor option is highly recommended for use with this program.) The program will also compile under UNIX 4.3 BSD FORTRAN-77 with minor changes. OPTI was developed in 1987.

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

    PubMed Central

    Castet, Jean-Francois; Saleh, Joseph H.

    2013-01-01

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

  9. Spreadsheet Analysis Of Queuing In A Computer Network

    NASA Technical Reports Server (NTRS)

    Galant, David C.

    1992-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Benbenek, Daniel; Soloff, Jason; Lieb, Erica

    2010-01-01

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

  11. Analysis and monitoring design for networks

    SciTech Connect

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

    1998-06-01

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

  12. Traffic Driven Analysis of Cellular and WiFi Networks

    ERIC Educational Resources Information Center

    Paul, Utpal Kumar

    2012-01-01

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

  13. Network-Based Visual Analysis of Tabular Data

    ERIC Educational Resources Information Center

    Liu, Zhicheng

    2012-01-01

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

  14. A Network Text Analysis of David Ayer's "Fury"

    ERIC Educational Resources Information Center

    Hunter, Starling David; Smith, Susan

    2015-01-01

    Network Text Analysis (NTA) involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In…

  15. Network analysis of global influenza spread.

    PubMed

    Chan, Joseph; Holmes, Antony; Rabadan, Raul

    2010-11-18

    Although vaccines pose the best means of preventing influenza infection, strain selection and optimal implementation remain difficult due to antigenic drift and a lack of understanding global spread. Detecting viral movement by sequence analysis is complicated by skewed geographic and seasonal distributions in viral isolates. We propose a probabilistic method that accounts for sampling bias through spatiotemporal clustering and modeling regional and seasonal transmission as a binomial process. Analysis of H3N2 not only confirmed East-Southeast Asia as a source of new seasonal variants, but also increased the resolution of observed transmission to a country level. H1N1 data revealed similar viral spread from the tropics. Network analysis suggested China and Hong Kong as the origins of new seasonal H3N2 strains and the United States as a region where increased vaccination would maximally disrupt global spread of the virus. These techniques provide a promising methodology for the analysis of any seasonal virus, as well as for the continued surveillance of influenza.

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

    SciTech Connect

    Medina, Richard M

    2012-01-01

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

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

    SciTech Connect

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

    2010-07-01

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

  18. Co-occurrence network analysis of modern Chinese poems

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  19. An Evaluation of Artificial Neural Network Modeling for Manpower Analysis

    DTIC Science & Technology

    1993-09-01

    This thesis evaluates the capabilities of artificial neural networks in forecasting the take-rates of the Voluntary Separations Incentive/Special...Separations Benefit (VSI/SSB) programs for male, Marine Corps Enlisted Personnel in the grades of E-5 and E-6. The Artificial Neural Networks models are...results indicate that artificial neural networks provide forecasting results at least as good as, if not better than, those obtained using classical

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

    ERIC Educational Resources Information Center

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

    2015-01-01

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

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

    ERIC Educational Resources Information Center

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

    2010-01-01

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

  2. Global Rural Autism Asperger Information Network: A Distance Learning Inservice Training Program.

    ERIC Educational Resources Information Center

    Bock, Marjorie A.; Swinney, Lori; Smart, Kathy

    The University of North Dakota's Global Rural Autism Asperger Information Network (GRAAIN) provides a special graduate certificate program in Autistic Spectrum Disorder (ASD) consisting of six online courses. The program started over 4 years ago as a pilot program to provide specialized ASD training to educators and personnel serving children with…

  3. Addressing cancer disparities via community network mobilization and intersectoral partnerships: a social network analysis.

    PubMed

    Ramanadhan, Shoba; Salhi, Carmel; Achille, Erline; Baril, Nashira; D'Entremont, Kerrie; Grullon, Milagro; Judge, Christine; Oppenheimer, Sarah; Reeves, Chrasandra; Savage, Clara; Viswanath, Kasisomayajula

    2012-01-01

    Community mobilization and collaboration among diverse partners are vital components of the effort to reduce and eliminate cancer disparities in the United States. We studied the development and impact of intersectoral connections among the members of the Massachusetts Community Network for Cancer Education, Research, and Training (MassCONECT). As one of the Community Network Program sites funded by the National Cancer Institute, this infrastructure-building initiative utilized principles of Community-based Participatory Research (CBPR) to unite community coalitions, researchers, policymakers, and other important stakeholders to address cancer disparities in three Massachusetts communities: Boston, Lawrence, and Worcester. We conducted a cross-sectional, sociometric network analysis four years after the network was formed. A total of 38 of 55 members participated in the study (69% response rate). Over four years of collaboration, the number of intersectoral connections reported by members (intersectoral out-degree) increased, as did the extent to which such connections were reported reciprocally (intersectoral reciprocity). We assessed relationships between these markers of intersectoral collaboration and three intermediate outcomes in the effort to reduce and eliminate cancer disparities: delivery of community activities, policy engagement, and grants/publications. We found a positive and statistically significant relationship between intersectoral out-degree and community activities and policy engagement (the relationship was borderline significant for grants/publications). We found a positive and statistically significant relationship between intersectoral reciprocity and community activities and grants/publications (the relationship was borderline significant for policy engagement). The study suggests that intersectoral connections may be important drivers of diverse intermediate outcomes in the effort to reduce and eliminate cancer disparities. The findings

  4. Visual analysis and exploration of complex corporate shareholder networks

    NASA Astrophysics Data System (ADS)

    Tekušová, Tatiana; Kohlhammer, Jörn

    2008-01-01

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

  5. Spectrum-based network visualization for topology analysis.

    PubMed

    Hu, Xianlin; Lu, Aidong; Wu, Xintao

    2013-01-01

    Network visualization techniques have been widely used to explore social networks, which are crucial to many application domains. A proposed visual-analytics approach provides functions that were previously hard to obtain. Based on recent achievements in spectrum-based analysis, it uses the features of node distribution and coordinates in the high-dimensional spectral space. Specifically, three-stage node projection and dispersion on a k-dimensional sphere in the spectral space determines the network layout. To assist interactive exploration of network topologies, network visualization and interactive analysis let users filter nodes and edges in a way that's meaningful to the global topology structure.

  6. Network and eigenvalue analysis of financial transaction networks

    NASA Astrophysics Data System (ADS)

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

    2009-10-01

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

  7. Dynamic network data envelopment analysis for university hospitals evaluation

    PubMed Central

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

    2016-01-01

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

  8. Analysis of Wideband Beamformers Designed with Artificial Neural Networks

    DTIC Science & Technology

    1990-12-01

    TECHNICAL REPORT 0-90-1 ANALYSIS OF WIDEBAND BEAMFORMERS DESIGNED WITH ARTIFICIAL NEURAL NETWORKS by Cary Cox Instrumentation Services Division...included. A briel tutorial on beamformers and neural networks is also provided. 14. SUBJECT TERMS 15, NUMBER OF PAGES Artificial neural networks Fecdforwa:,l...Beamformers Designed with Artificial Neural Networks ". The study was conducted under the general supervision of Messrs. George P. Bonner, Chief

  9. SIMS analysis: Development and evaluation program summary

    SciTech Connect

    Groenewold, G.S.; Appelhans, A.D.; Ingram, J.C.; Delmore, J.E.; Dahl, D.A.

    1996-11-01

    This report provides an overview of the ``SIMS Analysis: Development and Evaluation Program``, which was executed at the Idaho National Engineering Laboratory from mid-FY-92 to the end of FY-96. It should be noted that prior to FY-1994 the name of the program was ``In-Situ SIMS Analysis``. This report will not go into exhaustive detail regarding program accomplishments, because this information is contained in annual reports which are referenced herein. In summary, the program resulted in the design and construction of an ion trap secondary ion mass spectrometer (IT-SIMS), which is capable of the rapid analysis of environmental samples for adsorbed surface contaminants. This instrument achieves efficient secondary ion desorption by use of a molecular, massive ReO{sub 4}{sup {minus}} primary ion particle. The instrument manages surface charge buildup using a self-discharging principle, which is compatible with the pulsed nature of the ion trap. The instrument can achieve high selectivity and sensitivity using its selective ion storage and MS/MS capability. The instrument was used for detection of tri-n-butyl phosphate, salt cake (tank cake) characterization, and toxic metal speciation studies (specifically mercury). Technology transfer was also an important component of this program. The approach that was taken toward technology transfer was that of component transfer. This resulted in transfer of data acquisition and instrument control software in FY-94, and ongoing efforts to transfer primary ion gun and detector technology to other manufacturers.

  10. Method and tool for network vulnerability analysis

    DOEpatents

    Swiler, Laura Painton; Phillips, Cynthia A.

    2006-03-14

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

  11. NASA Multidisciplinary Design and Analysis Fellowship Program

    NASA Technical Reports Server (NTRS)

    1995-01-01

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

  12. BASIC Programming In Water And Wastewater Analysis

    NASA Technical Reports Server (NTRS)

    Dreschel, Thomas

    1988-01-01

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

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

    ERIC Educational Resources Information Center

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

    2009-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Miller, K. H.

    1976-01-01

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

  15. Children's Animated TV Programs: A Content Analysis

    ERIC Educational Resources Information Center

    Lambert, E. Beverley; Clancy, Susan

    2004-01-01

    This study describes the use of content analysis to develop a framework for analysing children's animated television programs (in this case, "Bob the Builder") and as such represents the initial stage of a larger project. Results indicate this popular TV series for preschoolers presents contradictory social messages about the roles of…

  16. Educational Partnerships Program: Analysis of Project Characteristics.

    ERIC Educational Resources Information Center

    Danzberger, Jacqueline P.

    An eight-part descriptive analysis is presented of the 18 projects funded through OERI's Educational Partnerships Program (EPP) in September of 1990. The EPP supports alliances between public schools and/or higher education and the private sector to encourage excellence in education. The 18 projects include: Anchorage Vocational Academic Institute…

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

    NASA Technical Reports Server (NTRS)

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

    1981-01-01

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

  18. Analysis of an evolving email network

    NASA Astrophysics Data System (ADS)

    Zhu, Chaopin; Kuh, Anthony; Wang, Juan; de Wilde, Philippe

    2006-10-01

    In this paper we study an evolving email network model first introduced by Wang and De Wilde, to the best of our knowledge. The model is analyzed by formulating the network topology as a random process and studying the dynamics of the process. Our analytical results show a number of steady state properties about the email traffic between different nodes and the aggregate networking behavior (i.e., degree distribution, clustering coefficient, average path length, and phase transition), and also confirm the empirical results obtained by Wang and De Wilde. We also conducted simulations confirming the analytical results. Extensive simulations were run to evaluate email traffic behavior at the link and network levels, phase transition phenomena, and also studying the behavior of email traffic in a hierarchical network. The methods established here are also applicable to many other practical networks including sensor networks and social networks.

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

    PubMed Central

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

    2015-01-01

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

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

    USGS Publications Warehouse

    Schroder, LeRoy J.; Malo, Bernard A.; ,

    1985-01-01

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

  1. Analysis and Design of Neural Networks

    DTIC Science & Technology

    1992-01-01

    The training problem for feedforward neural networks is nonlinear parameter estimation that can be solved by a variety of optimization techniques...Much of the literature of neural networks has focused on variants of gradient descent. The training of neural networks using such techniques is known to...be a slow process with more sophisticated techniques not always performing significantly better. It is shown that feedforward neural networks can

  2. Analysis of Municipal Pipe Network Franchise Institution

    NASA Astrophysics Data System (ADS)

    Yong, Sun; Haichuan, Tian; Feng, Xu; Huixia, Zhou

    Franchise institution of municipal pipe network has some particularity due to the characteristic of itself. According to the exposition of Chinese municipal pipe network industry franchise institution, the article investigates the necessity of implementing municipal pipe network franchise institution in China, the role of government in the process and so on. And this offers support for the successful implementation of municipal pipe network franchise institution in China.

  3. The feasibility program with security constraints and network rearrangement costs - Application to mixed /analogue and digital/ transmission networks

    NASA Astrophysics Data System (ADS)

    Serreault, J.-Y.; Minoux, M.

    1980-02-01

    This paper presents a second version of the 'feasibility program' (SECURAD) developed by the CNET. This program enables the routing at minimal costs of several thousand of requirements (expressed in circuits or groups of circuits) on very large mixed (analogue and digital) transmission networks, while respecting given capacities and taking into account security constraints and network-rearrangement costs. Consideration is given to a procedure for determining lower bounds for the cost of the optimal solution by solving a dual problem, and thus checking the quality of the approximate solutions obtained.

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

    ERIC Educational Resources Information Center

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

    2006-01-01

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

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

    ERIC Educational Resources Information Center

    Dingo, Rebecca

    2008-01-01

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

  6. Methodologies and techniques for analysis of network flow data

    SciTech Connect

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

    2004-12-01

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

  7. Northern Network. Final Report. Program No. 13.680.

    ERIC Educational Resources Information Center

    Threlkeld, Robert M.; And Others

    This report describes the 1980-81 development of a multistate, multimedia, multi-agency audioconferencing network for human services in Maine and New Hampshire, under a grant which was designed to: (1) establish a 20-site audioconferencing network in vocational rehabilitation offices; (2) provide training and technical assistance to the agencies…

  8. Application-oriented programming model for sensor networks embedded in the human body.

    PubMed

    Barbosa, Talles M G de A; Sene, Iwens G; da Rocha, Adson F; Nascimento, Fransisco A de O; Carvalho, Hervaldo S; Camapum, Juliana F

    2006-01-01

    This work presents a new programming model for sensor networks embedded in the human body which is based on the concept of multi-programming application-oriented software. This model was conceived with a top-down approach of four layers and its main goal is to allow the healthcare professionals to program and to reconfigure the network locally or by the Internet. In order to evaluate this hypothesis, a benchmarking was executed in order to allow the assessment of the mean time spent in the programming of a multi-functional sensor node used for the measurement and transmission of the electrocardiogram.

  9. FY 2013 Request for Proposals for the Pollution Prevention Information Network Grants Program

    EPA Pesticide Factsheets

    The Pollution Prevention Information Network (PPIN) grant program funds regional centers that serve both unique regional pollution prevention (P2) information needs and national audience needs for information on source reduction and related P2 practices.

  10. Report: Results of Technical Network Vulnerability Assessment: EPA’s Great Lakes National Program Office

    EPA Pesticide Factsheets

    Report #09-P-0185, June 30, 2009. Vulnerability testing conducted in May 2009 of EPA’s Great Lakes National Program Office network identified Internet Protocol addresses with several high-risk vulnerabilities associated with one device.

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

    PubMed

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

    2012-02-01

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

  12. Multifractality and Network Analysis of Phase Transition

    PubMed Central

    Li, Wei; Yang, Chunbin; Han, Jihui; Su, Zhu; Zou, Yijiang

    2017-01-01

    Many models and real complex systems possess critical thresholds at which the systems shift dramatically from one sate to another. The discovery of early-warnings in the vicinity of critical points are of great importance to estimate how far the systems are away from the critical states. Multifractal Detrended Fluctuation analysis (MF-DFA) and visibility graph method have been employed to investigate the multifractal and geometrical properties of the magnetization time series of the two-dimensional Ising model. Multifractality of the time series near the critical point has been uncovered from the generalized Hurst exponents and singularity spectrum. Both long-term correlation and broad probability density function are identified to be the sources of multifractality. Heterogeneous nature of the networks constructed from magnetization time series have validated the fractal properties. Evolution of the topological quantities of the visibility graph, along with the variation of multifractality, serve as new early-warnings of phase transition. Those methods and results may provide new insights about the analysis of phase transition problems and can be used as early-warnings for a variety of complex systems. PMID:28107414

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

    NASA Technical Reports Server (NTRS)

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

    2013-01-01

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

  14. A Critical Agency Network Model for Building an Integrated Outreach Program

    ERIC Educational Resources Information Center

    Kiyama, Judy Marquez; Lee, Jenny J.; Rhoades, Gary

    2012-01-01

    This study considers a distinct case of a college outreach program that integrates student affairs staff, academic administrators, and faculty across campus. The authors find that social networks and critical agency help to understand the integration of these various professionals and offer a critical agency network model of enacting change.…

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

    ERIC Educational Resources Information Center

    Pham, Andy V.

    2014-01-01

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

  16. Applying temporal network analysis to the venture capital market

    NASA Astrophysics Data System (ADS)

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

    2015-10-01

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

  17. Random matrix analysis of complex networks.

    PubMed

    Jalan, Sarika; Bandyopadhyay, Jayendra N

    2007-10-01

    We study complex networks under random matrix theory (RMT) framework. Using nearest-neighbor and next-nearest-neighbor spacing distributions we analyze the eigenvalues of the adjacency matrix of various model networks, namely, random, scale-free, and small-world networks. These distributions follow the Gaussian orthogonal ensemble statistic of RMT. To probe long-range correlations in the eigenvalues we study spectral rigidity via the Delta_{3} statistic of RMT as well. It follows RMT prediction of linear behavior in semilogarithmic scale with the slope being approximately 1pi;{2} . Random and scale-free networks follow RMT prediction for very large scale. A small-world network follows it for sufficiently large scale, but much less than the random and scale-free networks.

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

    NASA Astrophysics Data System (ADS)

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

    1998-05-01

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

  19. Network analysis of human heartbeat dynamics

    NASA Astrophysics Data System (ADS)

    Shao, Zhi-Gang

    2010-02-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

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

    NASA Technical Reports Server (NTRS)

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

    1985-01-01

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

  2. Graph theoretical analysis of complex networks in the brain.

    PubMed

    Stam, Cornelis J; Reijneveld, Jaap C

    2007-07-05

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-07-01

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

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

    SciTech Connect

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

    2014-07-10

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

  5. egoSlider: Visual Analysis of Egocentric Network Evolution.

    PubMed

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

    2016-01-01

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

  6. Network component analysis provides quantitative insights on an Arabidopsis transcription factor-gene regulatory network

    PubMed Central

    2013-01-01

    Background Gene regulatory networks (GRNs) are models of molecule-gene interactions instrumental in the coordination of gene expression. Transcription factor (TF)-GRNs are an important subset of GRNs that characterize gene expression as the effect of TFs acting on their target genes. Although such networks can qualitatively summarize TF-gene interactions, it is highly desirable to quantitatively determine the strengths of the interactions in a TF-GRN as well as the magnitudes of TF activities. To our knowledge, such analysis is rare in plant biology. A computational methodology developed for this purpose is network component analysis (NCA), which has been used for studying large-scale microbial TF-GRNs to obtain nontrivial, mechanistic insights. In this work, we employed NCA to quantitatively analyze a plant TF-GRN important in floral development using available regulatory information from AGRIS, by processing previously reported gene expression data from four shoot apical meristem cell types. Results The NCA model satisfactorily accounted for gene expression measurements in a TF-GRN of seven TFs (LFY, AG, SEPALLATA3 [SEP3], AP2, AGL15, HY5 and AP3/PI) and 55 genes. NCA found strong interactions between certain TF-gene pairs including LFY → MYB17, AG → CRC, AP2 → RD20, AGL15 → RAV2 and HY5 → HLH1, and the direction of the interaction (activation or repression) for some AGL15 targets for which this information was not previously available. The activity trends of four TFs - LFY, AG, HY5 and AP3/PI as deduced by NCA correlated well with the changes in expression levels of the genes encoding these TFs across all four cell types; such a correlation was not observed for SEP3, AP2 and AGL15. Conclusions For the first time, we have reported the use of NCA to quantitatively analyze a plant TF-GRN important in floral development for obtaining nontrivial information about connectivity strengths between TFs and their target genes as well as TF

  7. Network Analysis Guided Synthesis of Weisaconitine D and Liljestrandinine

    PubMed Central

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

    2015-01-01

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

  8. Sampling design optimization of a mussel watch-type monitoring program, the French Monitoring Network

    SciTech Connect

    Beliaeff, B.; Claisse, D.; Smith, P.J.

    1995-12-31

    In the French Monitoring Network, trace element and organic concentration in biota has been measured for 15 years on a quarterly basis at over 80 sites scattered along the French coastline. A reduction in the sampling effort may be needed as a result of budget restrictions. A constant budget, however, would allow the advancement of certain research and development projects, such as the feasibility of new chemical analysis. The basic problem confronting the program sampling design optimization is finding optimal numbers of sites in a given non-heterogeneous area and of sampling events within a year at each site. First, they determine a site specific cost function integrating analysis, personnel, and computer costs. Then, within-year and between-site variance components are estimated from the results of a linear model which includes a seasonal component. These two steps provide a cost-precision optimum for each contaminant. An example is given using the data from the 4 sites of the Loire estuary. Over all sites, significant `U`-shaped trends are estimated for Pb, PCBs, {Sigma}DDT and {alpha}-HCH, while PAHs show a significant inverted `U`-shaped curve. For most chemicals the within-year variance appears to be much higher than the between sites variance. This leads to the conclusion that, for this case, reducing the number of sites by two is preferable economically and in terms of monitoring efficiency to reducing the sampling frequency by the same factor. Further implications for the French Monitoring Network are discussed.

  9. Evaluation of a stalled airfoil analysis program

    NASA Technical Reports Server (NTRS)

    Rumsey, C. L.

    1985-01-01

    The Stalled Airfoil Analysis Program (SAAP) is a computer code for predicting the aerodynamic characteristics of an airfoil up to, and beyond, stall. SAAP is presently evaluated through comparisons with experiments and with two other theoretical methods over an extensive range of airfoils and Reynolds number conditions. SAAP modeled drag more accurately than either of the other methods, and at angles of attack below stall yielded a smoother lift variation with angle of attack.

  10. Graphical tools for network meta-analysis in STATA.

    PubMed

    Chaimani, Anna; Higgins, Julian P T; Mavridis, Dimitris; Spyridonos, Panagiota; Salanti, Georgia

    2013-01-01

    Network meta-analysis synthesizes direct and indirect evidence in a network of trials that compare multiple interventions and has the potential to rank the competing treatments according to the studied outcome. Despite its usefulness network meta-analysis is often criticized for its complexity and for being accessible only to researchers with strong statistical and computational skills. The evaluation of the underlying model assumptions, the statistical technicalities and presentation of the results in a concise and understandable way are all challenging aspects in the network meta-analysis methodology. In this paper we aim to make the methodology accessible to non-statisticians by presenting and explaining a series of graphical tools via worked examples. To this end, we provide a set of STATA routines that can be easily employed to present the evidence base, evaluate the assumptions, fit the network meta-analysis model and interpret its results.

  11. Functional holography analysis: Simplifying the complexity of dynamical networks

    NASA Astrophysics Data System (ADS)

    Baruchi, Itay; Grossman, Danny; Volman, Vladislav; Shein, Mark; Hunter, John; Towle, Vernon L.; Ben-Jacob, Eshel

    2006-03-01

    We present a novel functional holography (FH) analysis devised to study the dynamics of task-performing dynamical networks. The latter term refers to networks composed of dynamical systems or elements, like gene networks or neural networks. The new approach is based on the realization that task-performing networks follow some underlying principles that are reflected in their activity. Therefore, the analysis is designed to decipher the existence of simple causal motives that are expected to be embedded in the observed complex activity of the networks under study. First we evaluate the matrix of similarities (correlations) between the activities of the network's components. We then perform collective normalization of the similarities (or affinity transformation) to construct a matrix of functional correlations. Using dimension reduction algorithms on the affinity matrix, the matrix is projected onto a principal three-dimensional space of the leading eigenvectors computed by the algorithm. To retrieve back information that is lost in the dimension reduction, we connect the nodes by colored lines that represent the level of the similarities to construct a holographic network in the principal space. Next we calculate the activity propagation in the network (temporal ordering) using different methods like temporal center of mass and cross correlations. The causal information is superimposed on the holographic network by coloring the nodes locations according to the temporal ordering of their activities. First, we illustrate the analysis for simple, artificially constructed examples. Then we demonstrate that by applying the FH analysis to modeled and real neural networks as well as recorded brain activity, hidden causal manifolds with simple yet characteristic geometrical and topological features are deciphered in the complex activity. The term "functional holography" is used to indicate that the goal of the analysis is to extract the maximum amount of functional

  12. A new neural network model for solving random interval linear programming problems.

    PubMed

    Arjmandzadeh, Ziba; Safi, Mohammadreza; Nazemi, Alireza

    2017-05-01

    This paper presents a neural network model for solving random interval linear programming problems. The original problem involving random interval variable coefficients is first transformed into an equivalent convex second order cone programming problem. A neural network model is then constructed for solving the obtained convex second order cone problem. Employing Lyapunov function approach, it is also shown that the proposed neural network model is stable in the sense of Lyapunov and it is globally convergent to an exact satisfactory solution of the original problem. Several illustrative examples are solved in support of this technique.

  13. Design and analysis of the satellite laser communications network

    NASA Astrophysics Data System (ADS)

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

    2015-02-01

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

  14. Findings from an organizational network analysis to support local public health management.

    PubMed

    Merrill, Jacqueline; Caldwell, Michael; Rockoff, Maxine L; Gebbie, Kristine; Carley, Kathleen M; Bakken, Suzanne

    2008-07-01

    We assessed the feasibility of using organizational network analysis in a local public health organization. The research setting was an urban/suburban county health department with 156 employees. The goal of the research was to study communication and information flow in the department and to assess the technique for public health management. Network data were derived from survey questionnaires. Computational analysis was performed with the Organizational Risk Analyzer. Analysis revealed centralized communication, limited interdependencies, potential knowledge loss through retirement, and possible informational silos. The findings suggested opportunities for more cross program coordination but also suggested the presences of potentially efficient communication paths and potentially beneficial social connectedness. Managers found the findings useful to support decision making. Public health organizations must be effective in an increasingly complex environment. Network analysis can help build public health capacity for complex system management.

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  16. Statistical network analysis for functional MRI: summary networks and group comparisons

    PubMed Central

    Ginestet, Cedric E.; Fournel, Arnaud P.; Simmons, Andrew

    2014-01-01

    Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges in that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i) the construction of summary networks, such as how to compute and visualize the summary network from a sample of network-valued data points; and (ii) how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN). In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks. PMID:24834049

  17. From sensor networks to connected analysis tools

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

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

    PubMed Central

    Belza, Basia; Leith, Katherine; Allen, Peg; Coe, Norma B.; Anderson, Lynda A.

    2015-01-01

    Introduction Addressing chronic disease burden requires the creation of collaborative networks to promote systemic changes and engage stakeholders. Although many such networks exist, they are rarely assessed with tools that account for their complexity. This study examined the structure of mentorship and collaboration relationships among members of the Healthy Aging Research Network (HAN) using social network analysis (SNA). Methods We invited 97 HAN members and partners to complete an online social network survey that included closed-ended questions about HAN-specific mentorship and collaboration during the previous 12 months. Collaboration was measured by examining the activity of the network on 6 types of products: published articles, in-progress manuscripts, grant applications, tools, research projects, and presentations. We computed network-level measures such as density, number of components, and centralization to assess the cohesiveness of the network. Results Sixty-three respondents completed the survey (response rate, 65%). Responses, which included information about collaboration with nonrespondents, suggested that 74% of HAN members were connected through mentorship ties and that all 97 members were connected through at least one form of collaboration. Mentorship and collaboration ties were present both within and across boundaries of HAN member organizations. Conclusion SNA of public health collaborative networks provides understanding about the structure of relationships that are formed as a result of participation in network activities. This approach may offer members and funders a way to assess the impact of such networks that goes beyond simply measuring products and participation at the individual level. PMID:26292061

  19. Trauma-Exposed Latina Immigrants’ Networks: A Social Network Analysis Approach

    PubMed Central

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

    2015-01-01

    Objective Trauma exposure among Latina immigrants is common. Social support networks can buffer the impact of trauma on mental health. This study characterizes the social networks of trauma-exposed Latina immigrants using a social network analysis perspective. Methods In 2011–2012 a convenience sample (n=28) of Latina immigrants with trauma exposure and presumptive depression or posttraumatic stress disorder was recruited from a community clinic in Washington DC. Participants completed a social network assessment and listed up to ten persons in their network (alters). E-Net was used to describe the aggregate structural, interactional, and functional characteristics of networks and Node-XL was used in a case study to diagram one network. Results Most participants listed children (93%), siblings (82%), and friends (71%) as alters, and most alters lived in the US (69%). Perceived emotional support and positive social interaction were higher compared to tangible, language, information, and financial support. A case study illustrates the use of network visualizations to assess the strengths and weaknesses of social networks. Conclusions Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted. PMID:28078194

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

    ERIC Educational Resources Information Center

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

    2014-01-01

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

  1. Network Analysis Using Spatio-Temporal Patterns

    NASA Astrophysics Data System (ADS)

    Miranda, Gisele H. B.; Machicao, Jeaneth; Bruno, Odemir M.

    2016-08-01

    Different network models have been proposed along the last years inspired by real-world topologies. The characterization of these models implies the understanding of the underlying network phenomena, which accounts structural and dynamic properties. Several mathematical tools can be employed to characterize such properties as Cellular Automata (CA), which can be defined as dynamical systems of discrete nature composed by spatially distributed units governed by deterministic rules. In this paper, we proposed a method based on the modeling of one specific CA over distinct network topologies in order to perform the classification of the network model. The proposed methodology consists in the modeling of a binary totalistic CA over a network. The transition function that governs each CA cell is based on the density of living neighbors. Secondly, the distribution of the Shannon entropy is obtained from the evolved spatio-temporal pattern of the referred CA and used as a network descriptor. The experiments were performed using a dataset composed of four different types of networks: random, small-world, scale-free and geographical. We also used cross-validation for training purposes. We evaluated the accuracy of classification as a function of the initial number of living neighbors, and, also, as a function of a threshold parameter related to the density of living neighbors. The results show high accuracy values in distinguishing among the network models which demonstrates the feasibility of the proposed method.

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

    SciTech Connect

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

    2009-09-01

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

  3. Landscape Characterization and Representativeness Analysis for Understanding Sampling Network Coverage

    SciTech Connect

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

    2014-08-01

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

  4. A novel meta-analysis approach of cancer transcriptomes reveals prevailing transcriptional networks in cancer cells.

    PubMed

    Niida, Atsushi; Imoto, Seiya; Nagasaki, Masao; Yamaguchi, Rui; Miyano, Satoru

    2010-01-01

    Although microarray technology has revealed transcriptomic diversities underlining various cancer phenotypes, transcriptional programs controlling them have not been well elucidated. To decode transcriptional programs governing cancer transcriptomes, we have recently developed a computational method termed EEM, which searches for expression modules from prescribed gene sets defined by prior biological knowledge like TF binding motifs. In this paper, we extend our EEM approach to predict cancer transcriptional networks. Starting from functional TF binding motifs and expression modules identified by EEM, we predict cancer transcriptional networks containing regulatory TFs, associated GO terms, and interactions between TF binding motifs. To systematically analyze transcriptional programs in broad types of cancer, we applied our EEM-based network prediction method to 122 microarray datasets collected from public databases. The data sets contain about 15000 experiments for tumor samples of various tissue origins including breast, colon, lung etc. This EEM based meta-analysis successfully revealed a prevailing cancer transcriptional network which functions in a large fraction of cancer transcriptomes; they include cell-cycle and immune related sub-networks. This study demonstrates broad applicability of EEM, and opens a way to comprehensive understanding of transcriptional networks in cancer cells.

  5. The Leadership Development Network: Lessons Learned from a Field-Based Program for Principals.

    ERIC Educational Resources Information Center

    Thiessen, Dennis

    1989-01-01

    Describes the Leadership Development Network (LDN) in Canada, a field-based program for principals. Through a school improvement project, leadership development journal, meetings, and communication with other program participants, LDN engages principals in their own development as leaders and in the development of teachers who implement school…

  6. Program Excellence Network of the Academy of Human Resource Development: Its Purpose and Activities

    ERIC Educational Resources Information Center

    Ruona, Wendy E. A.

    2009-01-01

    This article features the Program Excellence Network (PEN) of the Academy of Human Resource Development (AHRD) which was established in September 2006 in response to a proposal brought forward by the author. The mission of PEN is to strengthen HRD academic programs and promote excellence in teaching HRD. PEN provides a forum for its members to…

  7. Information for integration. A senior services program spurs development of a multi-hospital integrated network.

    PubMed

    Sampsel, D; McNichols, S; Kordash, R D; Bonitati, D

    1994-09-01

    In 1985 St. Charles Hospital, Oregon, OH, and Mercy Hospital of Toledo, OH, launched a plan to jointly offer a continuum of services to area seniors. A multidisciplinary team of professionals from both hospitals decided that a membership program (titled the Senior Advantage Program) would be the most effective way to market the services and make them available. As part of the program's development, professionals from the two facilities created a personal computer-based software package that enabled them to capture and update information about Senior Advantage participants. The software program includes a detailed application form and a section for recording enrollees' service utilization. The program enables care givers to enter data when they interact with clients in any healthcare or community-based setting. To complement the personal computer software, a program to construct a central data base was written for the two hospitals' main computer systems. In 1991 St. Charles and Mercy hospitals joined two other facilities to form First InterHealth Network, a for-profit integrated delivery network. The Senior Advantage Program became the basis for the first package of services offered by First InterHealth. In 1992 the program became the catalyst for yet another collaborative venture, linking two rural Ohio Mercy hospitals to St. Charles and Mercy hospitals. The expanded network encouraged rural patients to remain within the Mercy network, utilizing inner-city and suburban Mercy-sponsored hospitals when appropriate.

  8. Stories from the Fussy Baby Network: The Latino Family Services Drop-in Program

    ERIC Educational Resources Information Center

    Gilkerson, Linda

    2009-01-01

    The Fussy Baby Network, a program of the Erikson Institute, partnered with a local church to engage Latino families in a group drop-in program designed to offer parenting education, support, and early intervention services. The group format provides a safe and trusting environment where parents decrease feelings of isolation, offer support to one…

  9. Sample size and power considerations in network meta-analysis

    PubMed Central

    2012-01-01

    Background Network meta-analysis is becoming increasingly popular for establishing comparative effectiveness among multiple interventions for the same disease. Network meta-analysis inherits all methodological challenges of standard pairwise meta-analysis, but with increased complexity due to the multitude of intervention comparisons. One issue that is now widely recognized in pairwise meta-analysis is the issue of sample size and statistical power. This issue, however, has so far only received little attention in network meta-analysis. To date, no approaches have been proposed for evaluating the adequacy of the sample size, and thus power, in a treatment network. Findings In this article, we develop easy-to-use flexible methods for estimating the ‘effective sample size’ in indirect comparison meta-analysis and network meta-analysis. The effective sample size for a particular treatment comparison can be interpreted as the number of patients in a pairwise meta-analysis that would provide the same degree and strength of evidence as that which is provided in the indirect comparison or network meta-analysis. We further develop methods for retrospectively estimating the statistical power for each comparison in a network meta-analysis. We illustrate the performance of the proposed methods for estimating effective sample size and statistical power using data from a network meta-analysis on interventions for smoking cessation including over 100 trials. Conclusion The proposed methods are easy to use and will be of high value to regulatory agencies and decision makers who must assess the strength of the evidence supporting comparative effectiveness estimates. PMID:22992327

  10. Integrated Network Decompositions and Dynamic Programming for Graph Optimization (INDDGO)

    SciTech Connect

    2012-05-31

    The INDDGO software package offers a set of tools for finding exact solutions to graph optimization problems via tree decompositions and dynamic programming algorithms. Currently the framework offers serial and parallel (distributed memory) algorithms for finding tree decompositions and solving the maximum weighted independent set problem. The parallel dynamic programming algorithm is implemented on top of the MADNESS task-based runtime.

  11. The Electronic Library Program: Developing Networked Electronic Library Collections.

    ERIC Educational Resources Information Center

    Butler, Brett

    1991-01-01

    The Memex Research Institute (MRI), an independent nonprofit research and development organization, has created an electronic library program of shared research and development to make the collective vision of Vannevar Bush's "memex" more concrete. Program is working toward the creation of large, publicly available indexed electronic image…

  12. Ionogram analysis with the generalised program POLAN

    SciTech Connect

    Titheridge, J.E.

    1985-12-01

    Different methods for the real-height analysis of ionograms, and their fields of application, are surveyed. A flexible new procedure is developed to give maximum accuracy and reliability in an automatic, one-pass analysis. The POLynomial ANalysis program POLAN uses polynomial real-height sections of any required degree, fitting any number of data points. By choice of a single parameter (MODE) it can reproduce all current methods from linear-laminations to single or overlapping polynomials. In addition a wide range of least-squares modes are available; these are preferable for most purposes, particularly with oversampled data (as from digital ionosondes). The mode of analysis changes automatically within the program to give an optimized least-squares calculation in the start, peak and valley regions. Physically unacceptable solutions are adjusted by imposing limits on the profile parameters. The new profile coefficients (and the new fitting error) are obtained directly and rapidly from the previous solution. This permits repeated application of the adjustments, as required, and cancellation of any change if it produces an unacceptably large increase in the virtual-height fitting error.

  13. Network component analysis: reconstruction of regulatory signals in biological systems.

    PubMed

    Liao, James C; Boscolo, Riccardo; Yang, Young-Lyeol; Tran, Linh My; Sabatti, Chiara; Roychowdhury, Vwani P

    2003-12-23

    High-dimensional data sets generated by high-throughput technologies, such as DNA microarray, are often the outputs of complex networked systems driven by hidden regulatory signals. Traditional statistical methods for computing low-dimensional or hidden representations of these data sets, such as principal component analysis and independent component analysis, ignore the underlying network structures and provide decompositions based purely on a priori statistical constraints on the computed component signals. The resulting decomposition thus provides a phenomenological model for the observed data and does not necessarily contain physically or biologically meaningful signals. Here, we develop a method, called network component analysis, for uncovering hidden regulatory signals from outputs of networked systems, when only a partial knowledge of the underlying network topology is available. The a priori network structure information is first tested for compliance with a set of identifiability criteria. For networks that satisfy the criteria, the signals from the regulatory nodes and their strengths of influence on each output node can be faithfully reconstructed. This method is first validated experimentally by using the absorbance spectra of a network of various hemoglobin species. The method is then applied to microarray data generated from yeast Saccharamyces cerevisiae and the activities of various transcription factors during cell cycle are reconstructed by using recently discovered connectivity information for the underlying transcriptional regulatory networks.

  14. Protein Co-Expression Network Analysis (ProCoNA)

    SciTech Connect

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

    2013-06-01

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

  15. Natural Time Analysis and Complex Networks

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  16. Energy Analysis Program. 1992 Annual report

    SciTech Connect

    Not Available

    1993-06-01

    The Program became deeply involved in establishing 4 Washington, D.C., project office diving the last few months of fiscal year 1942. This project office, which reports to the Energy & Environment Division, will receive the majority of its support from the Energy Analysis Program. We anticipate having two staff scientists and support personnel in offices within a few blocks of DOE. Our expectation is that this office will carry out a series of projects that are better managed closer to DOE. We also anticipate that our representation in Washington will improve and we hope to expand the Program, its activities, and impact, in police-relevant analyses. In spite of the growth that we have achieved, the Program continues to emphasize (1) energy efficiency of buildings, (2) appliance energy efficiency standards, (3) energy demand forecasting, (4) utility policy studies, especially integrated resource planning issues, and (5) international energy studies, with considerate emphasis on developing countries and economies in transition. These continuing interests are reflected in the articles that appear in this report.

  17. Assessing group interaction with social language network analysis.

    SciTech Connect

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

    2010-04-01

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

  18. An Analysis of Stopping Criteria in Artificial Neural Networks

    DTIC Science & Technology

    1994-03-01

    I’AD-A278 491(1 AN ANALYSIS OF STOPPING CRITERIA IN ARTIFICIAL NEURAL NETWORKS THESIS Bruce Kostal Captain, USAF AFIT/GST/ENS/94M 07 D I ELECTE APR...ANALYSIS OF STOPPING CRITERIA IN ARTIFICIAL NEURAL NETWORKS THESIS Bruce Kostal Captain, USAF AFIT/GST/ENS/94M-07 ETIC ELECTE 94-12275 APR2 1994 U Approved...for public release; distributi6 unlimited D94󈧮i •6 AFIT/GST/ENS/94M-07 AN ANALYSIS OF STOPPING CRITERIA IN ARTIFICIAL NEURAL NETWORKS THESIS

  19. Assessing Group Interaction with Social Language Network Analysis

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Technical Reports Server (NTRS)

    Eberlein, Susan; Yates, Gigi

    1988-01-01

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

  1. Integer programming-based method for designing synthetic metabolic networks by Minimum Reaction Insertion in a Boolean model.

    PubMed

    Lu, Wei; Tamura, Takeyuki; Song, Jiangning; Akutsu, Tatsuya

    2014-01-01

    In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA)-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at "http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html."

  2. Integer Programming-Based Method for Designing Synthetic Metabolic Networks by Minimum Reaction Insertion in a Boolean Model

    PubMed Central

    Song, Jiangning; Akutsu, Tatsuya

    2014-01-01

    In this paper, we consider the Minimum Reaction Insertion (MRI) problem for finding the minimum number of additional reactions from a reference metabolic network to a host metabolic network so that a target compound becomes producible in the revised host metabolic network in a Boolean model. Although a similar problem for larger networks is solvable in a flux balance analysis (FBA)-based model, the solution of the FBA-based model tends to include more reactions than that of the Boolean model. However, solving MRI using the Boolean model is computationally more expensive than using the FBA-based model since the Boolean model needs more integer variables. Therefore, in this study, to solve MRI for larger networks in the Boolean model, we have developed an efficient Integer Programming formalization method in which the number of integer variables is reduced by the notion of feedback vertex set and minimal valid assignment. As a result of computer experiments conducted using the data of metabolic networks of E. coli and reference networks downloaded from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we have found that the developed method can appropriately solve MRI in the Boolean model and is applicable to large scale-networks for which an exhaustive search does not work. We have also compared the developed method with the existing connectivity-based methods and FBA-based methods, and show the difference between the solutions of our method and the existing methods. A theoretical analysis of MRI is also conducted, and the NP-completeness of MRI is proved in the Boolean model. Our developed software is available at “http://sunflower.kuicr.kyoto-u.ac.jp/~rogi/minRect/minRect.html.” PMID:24651476

  3. Performance analysis of a VSAT network

    NASA Astrophysics Data System (ADS)

    Karam, Fouad G.; Miller, Neville; Karam, Antoine

    With the growing need for efficient satellite networking facilities, the very small aperture terminal (VSAT) technology emerges as the leading edge of satellite communications. Achieving the required performance of a VSAT network is dictated by the multiple access technique utilized. Determining the inbound access method best suited for a particular application involves trade-offs between response time and space segment utilization. In this paper, the slotted Aloha and dedicated stream access techniques are compared. It is shown that network performance is dependent on the traffic offered from remote earth stations as well as the sensitivity of customer's applications to satellite delay.

  4. Dynamic Network-Based Epistasis Analysis: Boolean Examples

    PubMed Central

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

    2011-01-01

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

  5. 76 FR 11310 - Alternatives Analysis Program Discretionary Funding Allocations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-03-01

    ...: Federal Transit Administration (FTA), DOT. ACTION: Alternatives Analysis Program Announcement of Project...) announces the selection of projects funded with unallocated Section 5339 Alternatives Analysis Program funds... potential sponsors of major transit capital investments (``New Starts'' and ``Small Starts'' projects)...

  6. South Asian Ethnics in Britain and BBC: Content Analysis of a Television Program.

    ERIC Educational Resources Information Center

    Mohapatra, Manindra K.

    This study uses content analysis of "Network East," an ethnic television program aired on British television, to identify the major concerns of the South Asian community in Britain. Most South Asians, comprised of Indians, Pakistanis, Bangladeshis, and Sri Lankans, live in the urban centers of London, Birmingham, Leicester, and Bradford.…

  7. Social Network Analysis to Evaluate an Interdisciplinary Research Center

    ERIC Educational Resources Information Center

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

    2007-01-01

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

  8. An Analysis of the Structure and Evolution of Networks

    ERIC Educational Resources Information Center

    Hua, Guangying

    2011-01-01

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

  9. A Graph Oriented Approach for Network Forensic Analysis

    ERIC Educational Resources Information Center

    Wang, Wei

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

    Scholtes, Ingo; Wider, Nicolas; Garas, Antonios

    2016-03-01

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

  11. Integer programming-based approach to allocation of reporter genes for cell array analysis.

    PubMed

    Hayashida, Morihiro; Sun, Fuyan; Aburatani, Sachiyo; Horimoto, Katsuhisa; Akutsu, Tatsuya

    2008-01-01

    In this paper, we consider the problem of selecting the most effective set of reporter genes for analysis of biological networks using cell microarrays. We propose two graph theoretic formulations of the reporter gene allocation problem, and show that both problems are hard to approximate. We propose integer programming-based methods for solving practical instances of these problems optimally. We apply them to apoptosis pathway maps, and discuss the biological significance of the result. We also apply them to artificial networks, the result of which shows that optimal solutions can be obtained within several seconds for networks with 10,000 nodes.

  12. INDDGO: Integrated Network Decomposition & Dynamic programming for Graph Optimization

    SciTech Connect

    Groer, Christopher S; Sullivan, Blair D; Weerapurage, Dinesh P

    2012-10-01

    It is well-known that dynamic programming algorithms can utilize tree decompositions to provide a way to solve some \\emph{NP}-hard problems on graphs where the complexity is polynomial in the number of nodes and edges in the graph, but exponential in the width of the underlying tree decomposition. However, there has been relatively little computational work done to determine the practical utility of such dynamic programming algorithms. We have developed software to construct tree decompositions using various heuristics and have created a fast, memory-efficient dynamic programming implementation for solving maximum weighted independent set. We describe our software and the algorithms we have implemented, focusing on memory saving techniques for the dynamic programming. We compare the running time and memory usage of our implementation with other techniques for solving maximum weighted independent set, including a commercial integer programming solver and a semi-definite programming solver. Our results indicate that it is possible to solve some instances where the underlying decomposition has width much larger than suggested by the literature. For certain types of problems, our dynamic programming code runs several times faster than these other methods.

  13. Using a Computerized Information Network for Assessing Programming Needs.

    ERIC Educational Resources Information Center

    Vanek, Eugenia Poporad; And Others

    1994-01-01

    When 90 physicians were surveyed, half received instructions for responding via electronic mail (8 responses) and half were told to reply by mail (6 responses). Limited response suggests unwillingness or uncertainty about using technology. A computer network must be viewed as faster, more efficient, and less costly for it to be used. (SK)

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

    PubMed Central

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

    2015-01-01

    Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics) can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI) and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA) toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i) an open-source, Matlab-based, cross-platform (Windows and UNIX OS) package with a graphical user interface (GUI); (ii) allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii) providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv) allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v) including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI) data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website.1 PMID:26175682

  15. Velocity fluctuation analysis via dynamic programming

    SciTech Connect

    Schlossberg, D. J.; Gupta, D. K.; Fonck, R. J.; McKee, G. R.; Shafer, M. W.

    2006-10-15

    A new method of calculating one-dimensional velocity fluctuations from spatially resolved density fluctuation measurements is presented. The algorithm uses vector-matching methods of dynamic programming that match structures, such as turbulent fluctuations, in two data sets. The associated time delay between data sets is estimated by determining an optimal path to transform one vector to another. This time-delay-estimation (TDE) method establishes a new benchmark for velocity analysis by achieving higher sensitivity and frequency response than previously developed methods, such as time-resolved cross correlations and wavelets. TDE has been successfully applied to beam emission spectroscopy measurements of density fluctuations to obtain poloidal flow fluctuations associated with such phenomena as the geodesic acoustic mode. The dynamic programming algorithm should allow extension to high frequency velocity fluctuations associated with underlying electrostatic potential and resulting ExB fluctuations.

  16. The Stock Price Prediction and Sell-buy Strategy Model by Genetic Network Programming

    NASA Astrophysics Data System (ADS)

    Mori, Shigeo; Hirasawa, Kotaro; Hu, Jinglu

    Various stock prices predicting and sell-buy strategy models have been so far proposed. They are classified as the fundamental analysis using the achievements of the companies and the trend of business, etc., and the technical analysis which carries out the numerical analysis of the movement of stock prices. On the other hand, as one of the methods for data mining which finds out the regularity from a vast quantity of stock price data, Genetic Algorithm (GA) has been so far applied widely. As a concrete example, the optimal values of parameters of stock indices like various moving averages and rates of deviation, etc. is computed by GA, and there have been developed various methods for predicting stock prices and determinig sell-buy strategy based on it. However, it is hard to determine which is the most effective index by the conventional GA. Moreover, the most effective one depends on the brands. So in this paper, a stock price prediction and sell-buy strategy model which searches for the optimal combination of various indices in the technical analysis has been proposed using Genetic Network programming and its effectiveness is confirmed by simulations.

  17. Multiobjective blockmodeling for social network analysis.

    PubMed

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

    2013-07-01

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

  18. SUPERSONIC TRANSPORT DEVELOPMENT AND PRODUCTION. VOLUME I. COST ANALYSIS PROGRAM.

    DTIC Science & Technology

    SUPERSONIC AIRCRAFT, *COSTS), (*AIRCRAFT INDUSTRY, INDUSTRIAL PRODUCTION ), MANAGEMENT ENGINEERING, AIRFRAMES, ECONOMICS, COMPUTER PROGRAMS, STATISTICAL ANALYSIS, MONEY, AIRCRAFT ENGINES, FEASIBILITY STUDIES

  19. Network traffic analysis using dispersion patterns

    SciTech Connect

    Khan, F. N.

    2010-03-15

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

  20. Topological Analysis of Wireless Networks (TAWN)

    DTIC Science & Technology

    2016-05-31

    Michael American University Department of Mathematics and Statistics 4400 Massachusetts Ave NW Washington, DC 20016 N/A Defense Advanced Research...protocol, activity, and channel conditions can be associated to such a cell complex using a mathematical object called a sheaf. We leveraged the existing... mathematical literature on sheaves that describes how to draw global (network-wide) inferences from them. Wireless network, local homology, sheaf

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

    PubMed

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

    2013-01-01

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

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

    NASA Technical Reports Server (NTRS)

    Alam, J.; Berke, L.

    1991-01-01

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

  3. Analysis of community structure in networks of correlated data

    SciTech Connect

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

    2008-12-25

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

  4. Trends in Network Prime-Time Programming, 1953-74

    ERIC Educational Resources Information Center

    Dominick, Joseph R.; Pearce, Millard C.

    1976-01-01

    Examines major television programming content trends by reviewing prime-time entertainment series that premiered during the fall season of each year from 1953-74, and concludes that audiences are being offered fewer and fewer content choices. (MH)

  5. An Analysis of the Radio Program Manager Occupation.

    ERIC Educational Resources Information Center

    Friedberg, Jerry; Stella, Phillip.

    This occupational analysis data was assembled to help broadcasting arts teachers develop a course of study in program management for junior and senior high school students. Following a job description for a program manager, the remainder of the content in standard task analysis format presents an analysis of nine program management duties (tasks).…

  6. On spectral techniques in analysis of Boolean networks

    NASA Astrophysics Data System (ADS)

    Kesseli, Juha; Rämö, Pauli; Yli-Harja, Olli

    2005-06-01

    In this work we present results that can be used for analysis of Boolean networks. The results utilize Fourier spectra of the functions in the network. An accurate formula is given for Derrida plots of networks of finite size N based on a result on Boolean functions presented in another context. Derrida plots are widely used to examine the stability issues of Boolean networks. For the limit N→∞, we give a computationally simple form that can be used as a good approximation for rather small networks as well. A formula for Derrida plots of random Boolean networks (RBNs) presented earlier in the literature is given an alternative derivation. It is shown that the information contained in the Derrida plot is equal to the average Fourier spectrum of the functions in the network. In the case of random networks the mean Derrida plot can be obtained from the mean spectrum of the functions. The method is applied to real data by using the Boolean functions found in genetic regulatory networks of eukaryotic cells in an earlier study. Conventionally, Derrida plots and stability analysis have been computed with statistical sampling resulting in poorer accuracy.

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

    PubMed Central

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  9. Changing Social Networks Among Homeless Individuals: A Prospective Evaluation of a Job- and Life-Skills Training Program.

    PubMed

    Gray, Heather M; Shaffer, Paige M; Nelson, Sarah E; Shaffer, Howard J

    2016-10-01

    Social networks play important roles in mental and physical health among the general population. Building healthier social networks might contribute to the development of self-sufficiency among people struggling to overcome homelessness and substance use disorders. In this study of homeless adults completing a job- and life-skills program (i.e., the Moving Ahead Program at St. Francis House, Boston), we prospectively examined changes in social network quality, size, and composition. Among the sample of participants (n = 150), we observed positive changes in social network quality over time. However, social network size and composition did not change among the full sample. The subset of participants who reported abstaining from alcohol during the months before starting the program reported healthy changes in their social networks; specifically, while completing the program, they re-structured their social networks such that fewer members of their network used alcohol to intoxication. We discuss practical implications of these findings.

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

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  11. Neural networks in structural analysis and design - An overview

    NASA Technical Reports Server (NTRS)

    Hajela, P.; Berke, L.

    1992-01-01

    The present paper provides an overview of the state-of-the-art in the application of neural networks in problems of structural analysis and design, including a survey of published applications in structural engineering. Such applications have included, among others, the use of neural networks in modeling nonlinear analysis of structures, as a rapid reanalysis capability in optimal design, and in developing problem parameter sensitivity of optimal solutions for use in multilevel decomposition based design. While most of the applications reported in the literature have been restricted to the use of the multilayer perceptron architecture and minor variations thereof, other network architectures have also been successfully explored, including the ART network, the counterpropagation network and the Hopfield-Tank model.

  12. Recent Research in Artificial Intelligence, Heuristic Programming, and Network Protocols

    DTIC Science & Technology

    1974-07-01

    and Joshua Lederberg , Co-principal Investigators NETWORK PROTOCOL DEVELOPMENT PROJECT Vinton Cerf, Principal Investigator ABSTRACT This is a...by Edward Feigenbaum, Professor of Computer Science, and Joshua Lederberg , Professor of Genetics, and was initially an element of the Artificial...Quam, J. Lederberg , E. Levinthal. R. Tucker, B. Eros». J. Pollack. Variable Features on Mars II: Mariner 9 Global Results, Journal of Geophysical

  13. Analysis of Network Topologies Underlying Ethylene Growth Response Kinetics

    PubMed Central

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

    2016-01-01

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

  14. Expansion of epicyclic gear dynamic analysis program

    NASA Technical Reports Server (NTRS)

    Boyd, Linda Smith; Pike, James A.

    1987-01-01

    The multiple mesh/single stage dynamics program is a gear tooth analysis program which determines detailed geometry, dynamic loads, stresses, and surface damage factors. The program can analyze a variety of both epicyclic and single mesh systems with spur or helical gear teeth including internal, external, and buttress tooth forms. The modifications refine the options for the flexible carrier and flexible ring gear rim and adds three options: a floating Sun gear option; a natural frequency option; and a finite element compliance formulation for helical gear teeth. The option for a floating Sun incorporates two additional degrees of freedom at the Sun center. The natural frequency option evaluates the frequencies of planetary, star, or differential systems as well as the effect of additional springs at the Sun center and those due to a flexible carrier and/or ring gear rim. The helical tooth pair finite element calculated compliance is obtained from an automated element breakup of the helical teeth and then is used with the basic gear dynamic solution and stress postprocessing routines. The flexible carrier or ring gear rim option for planetary and star spur gear systems allows the output torque per carrier and ring gear rim segment to vary based on the dynamic response of the entire system, while the total output torque remains constant.

  15. Overview of NASA Astrophysics Program Analysis Groups

    NASA Astrophysics Data System (ADS)

    Sanders, Wilton T.; Sambruna, Rita M.; Perez, Mario R.; Hudgins, Douglas M.

    2015-01-01

    NASA Astrophysics Program Analysis Groups (PAGs) are responsible for facilitating and coordinating community input into the development and execution of NASAs three astrophysics science themes: Cosmic Origins (COPAG), Exoplanet Exploration (ExoPAG), and Physics of the Cosmos (PhysPAG). The PAGs provide a community-based, interdisciplinary forum for analyses that support and inform planning and prioritization of activities within the Astrophysics Division programs. Operations and structure of the PAGs are described in their Terms of Reference (TOR), which can be found on the three science theme Program Office web pages. The Astrophysics PAGs report their input and findings to NASA through the Astrophysics Subcommittee of the NASA Advisory Council, of which all the PAG Chairs are members. In this presentation, we will provide an overview of the ongoing activities of NASAs Astrophysics PAGs in the context of the opportunities and challenges currently facing the Astrophysics Division. NASA Headquarters representatives for the COPAG, ExoPAG, and PhysPAG will all be present and available to answer questions about the programmatic role of the Astrophysics PAGs.

  16. Overview of NASA Astrophysics Program Analysis Groups

    NASA Astrophysics Data System (ADS)

    Garcia, Michael R.; Hudgins, D. M.; Sambruna, R. M.

    2014-01-01

    NASA Astrophysics Program Analysis Groups (PAGs) are responsible for facilitating and coordinating community input into the developmentand execution of NASAs three astrophysics science themes: Cosmic Origins (COPAG), Exoplanet Exploration (ExoPAG), and Physics of the Cosmos (PhysPAG). The PAGs provide a community-based, interdisciplinary forum for analyses that support and inform planning and prioritization of activities within the Astrophysics Division programs. Operations and structure of the PAGs are described in the Terms of Reference (TOR) which can be found on the three science theme Program Office web pages. The Astrophysics PAGs report their input and findings to NASA through the Astrophysics Subcommittee of the NASA Advisory Council, of which all the PAG Chairs are members. In this presentation, we will provide an overview of the ongoing activities of NASAs Astrophysics PAGs in the context of the opportunities and challenges currently facing the Astrophysics Division. NASA Headquarters representatives for the COPAG, ExoPAG, and PhysPAG will all be present and available to answer questions about the programmatic role of the Astrophysics PAGs.

  17. Earth resources data analysis program, phase 2

    NASA Technical Reports Server (NTRS)

    1974-01-01

    The efforts and findings of the Earth Resources Data Analysis Program are summarized. Results of a detailed study of the needs of EOD with respect to an applications development system (ADS) for the analysis of remotely sensed data, including an evaluation of four existing systems with respect to these needs are described. Recommendations as to possible courses for EOD to follow to obtain a viable ADS are presented. Algorithmic development comprised of several subtasks is discussed. These subtasks include the following: (1) two algorithms for multivariate density estimation; (2) a data smoothing algorithm; (3) a method for optimally estimating prior probabilities of unclassified data; and (4) further applications of the modified Cholesky decomposition in various calculations. Little effort was expended on task 3, however, two reports were reviewed.

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    PubMed

    Wu, Guanming; Haw, Robin

    2017-01-01

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

  20. SANDS - Sediment Analysis Network for Decision Support

    NASA Astrophysics Data System (ADS)

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

    2010-12-01

    Since the year 2000, Eastern Louisiana, coastal Mississippi, Alabama, and the western Florida panhandle have been affected by 28 tropical storms, seven of which were hurricanes. These tropical cyclones have significantly altered normal coastal processes and characteristics in the Gulf region through sediment disturbance. Although tides, seasonality, and agricultural development influence suspended sediment and sediment deposition over periods of time, tropical storm activity has the capability of moving the largest sediment loads in the shortest periods of time for coastal areas. The SANDS project is also investigating the effects of sediment immersed oil from the Deepwater Horizon disaster in April 2010 which has the potential to resurface as a result of tropical storm activity. The importance of sediments upon water quality, coastal erosion, habitats and nutrients has made their study and monitoring vital to decision makers in the region. Currently agencies such as United States Army Corps of Engineers (USACE), NASA, and Geological Survey of Alabama (GSA) are employing a variety of in-situ and airborne based measurements to assess and monitor sediment loading and deposition. These methods provide highly accurate information but are limited in geographic range, are not continuous over a region and, in the case of airborne LIDAR are expensive and do not recur on a regular basis. Multi-temporal and multi-spectral satellite imagery that shows tropical-storm-induced suspended sediment and storm-surge sediment deposits can provide decision makers with immediate and long-term information about the impacts of tropical storms and hurricanes. It can also be valuable for those conducting research and for projects related to coastal issues such as recovery, planning, management, and mitigation. The Sediment Analysis Network for Decision Support has generated a number of decision support products derived from MODIS, Landsat and SeaWiFS instruments that potentially support

  1. Multilayer Network Analysis of Nuclear Reactions

    PubMed Central

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

    2016-01-01

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

  2. Sentiment analysis on smoking in social networks.

    PubMed

    Sofean, Mustafa; Smith, Matthew

    2013-01-01

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

  3. Logistic map analysis of biomolecular network evolution

    NASA Astrophysics Data System (ADS)

    Stein, R. R.; Isambert, H.

    2011-11-01

    We study the expansion of biomolecular networks from the view point of first evolutionary principles based on the duplication and divergence of ancestral genes. The expansion of gene families and subnetworks is analyzed in terms of logistic map compositions, which capture the varying functional constraints of individual genes in the course of evolution. Using a mean-field approach, we then demonstrate the existence of spontaneous growth-rate variations between gene families and discuss the relevance of such heterogeneous expansions for the emergent properties of actual biomolecular networks.

  4. Overview 2010 of ARL Program on Network Science for Human Decision Making

    DTIC Science & Technology

    2011-01-01

    IN FRACTAL PHYSIOLOGY       OVERVIEW 2010 OF ARL PROGRAM ON NETWORK SCIENCE FOR HUMAN DECISION MAKING   Bruce J West Journal Name: Frontiers in...2:76. doi:10.3389/fphys.2011.00076 Article URL: http://www.frontiersin.org/Journal/Abstract.aspx?s=454& name= fractal %20physiology&ART_DOI=10.3389...functions: transportation, electrical power, food distribution, finance , and health care to name a few. The 1 2 interoperability of these networks

  5. Semantic web for integrated network analysis in biomedicine.

    PubMed

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

    2009-03-01

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

  6. [Social network analysis and eating disorders: a study concerning blogs].

    PubMed

    Bastianelli, Alessia; Spoto, Andrea; Vidotto, Giulio

    2011-01-01

    This study is aimed at analyzing the structure of relations among blogs referring to Eating Disorders (ED). Through the use Of Social Network Analysis (SNA) we investigated both the groups and their structure in order to study the social processes within the network. A formal analysis of the ED blogs' characteristics has been carried out. This analysis provided us with information about network Centrality and Cohesion parameters. Results allow us to highlight the most relevant blogs in the network. Even if the extremely variable nature of the blogs does not allow to have a precise picture of the blogosphere referring to ED, this first attempt to apply SNA in this field allowed us to suggest interesting remarks about EBD both from the research and from the social perspective.

  7. Energy balance for analysis of complex metabolic networks.

    PubMed Central

    Beard, Daniel A; Liang, Shou-dan; Qian, Hong

    2002-01-01

    Predicting behavior of large-scale biochemical networks represents one of the greatest challenges of bioinformatics and computational biology. Computational tools for predicting fluxes in biochemical networks are applied in the fields of integrated and systems biology, bioinformatics, and genomics, and to aid in drug discovery and identification of potential drug targets. Approaches, such as flux balance analysis (FBA), that account for the known stoichiometry of the reaction network while avoiding implementation of detailed reaction kinetics are promising tools for the analysis of large complex networks. Here we introduce energy balance analysis (EBA)--the theory and methodology for enforcing the laws of thermodynamics in such simulations--making the results more physically realistic and revealing greater insight into the regulatory and control mechanisms operating in complex large-scale systems. We show that EBA eliminates thermodynamically infeasible results associated with FBA. PMID:12080101

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

    NASA Astrophysics Data System (ADS)

    Stocco, Gabriel; Savell, Robert; Cybenko, George

    2010-04-01

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

  9. GEODYN system support program, volume 4. [computer program for trajectory analysis of artificial satellites

    NASA Technical Reports Server (NTRS)

    Mullins, N. E.

    1972-01-01

    The GEODYN Orbit Determination and Geodetic Parameter Estimation System consists of a set of computer programs designed to determine and analyze definitive satellite orbits and their associated geodetic and measurement parameters. This manual describes the Support Programs used by the GEODYN System. The mathematics and programming descriptions are detailed. The operational procedures of each program are presented. GEODYN ancillary analysis programs may be grouped into three different categories: (1) orbit comparison - DELTA (2) data analysis using reference orbits - GEORGE, and (3) pass geometry computations - GROUNDTRACK. All of the above three programs use one or more tapes written by the GEODYN program in either a data reduction or orbit generator run.

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

    NASA Astrophysics Data System (ADS)

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

    2004-09-01

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

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

    PubMed

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

    2004-09-16

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

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

    NASA Technical Reports Server (NTRS)

    Lee, Charles H.; Cheung, Kar-Ming

    2012-01-01

    In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.

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

    PubMed Central

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

    2014-01-01

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

  14. Detecting Network Communities: An Application to Phylogenetic Analysis

    PubMed Central

    Andrade, Roberto F. S.; Rocha-Neto, Ivan C.; Santos, Leonardo B. L.; de Santana, Charles N.; Diniz, Marcelo V. C.; Lobão, Thierry Petit; Goés-Neto, Aristóteles; Pinho, Suani T. R.; El-Hani, Charbel N.

    2011-01-01

    This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis. PMID:21573202

  15. Tractable Analysis for Large Social Networks

    ERIC Educational Resources Information Center

    Zhang, Bin

    2012-01-01

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

  16. Maize metabolic network construction and transcriptome analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

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

  17. Using Citation Network Analysis in Educational Technology

    ERIC Educational Resources Information Center

    Cho, Yonjoo; Park, Sunyoung

    2012-01-01

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

  18. Network Analysis with the Enron Email Corpus

    ERIC Educational Resources Information Center

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

    2015-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

  20. Analysis and logical modeling of biological signaling transduction networks

    NASA Astrophysics Data System (ADS)

    Sun, Zhongyao

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

  1. Radar sensitivity and resolution in presence of range sidelobe reducing networks designed using linear programming

    NASA Astrophysics Data System (ADS)

    Bicocchi, R.; Melacci, P. T.; Bucciarelli, T.

    1984-06-01

    The design of a sidelobe-reduction network for coherent high-resolution radars using Barker codes and the results of an analytical investigation of its performance are presented and illustrated graphically. Compression is achieved by a matched filter followed by a weighting network designed using linear programming to minimize the implementation to adapt to different operating modes. It is found that the network gives significant increases in sensitivity and resolution while limiting mismatching losses to about 0.2 dB. A typical digital implementation requires only 66 devices for 10-bit input and sampling rate 150 nsec.

  2. LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

    SciTech Connect

    Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.; Akyol, Bora A.; Oehmen, Christopher S.

    2013-09-28

    Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the data in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.

  3. Issues in performing a network meta-analysis.

    PubMed

    Senn, Stephen; Gavini, Francois; Magrez, David; Scheen, André

    2013-04-01

    The example of the analysis of a collection of trials in diabetes consisting of a sparsely connected network of 10 treatments is used to make some points about approaches to analysis. In particular various graphical and tabular presentations, both of the network and of the results are provided and the connection to the literature of incomplete blocks is made. It is clear from this example that is inappropriate to treat the main effect of trial as random and the implications of this for analysis are discussed. It is also argued that the generalisation from a classic random-effect meta-analysis to one applied to a network usually involves strong assumptions about the variance components involved. Despite this, it is concluded that such an analysis can be a useful way of exploring a set of trials.

  4. New policy to manage tools in flexible manufacturing systems using network part programs

    NASA Astrophysics Data System (ADS)

    Matta, Andrea; Tolio, Tullio; Grieco, Antonio; Nucci, Francesco

    2000-10-01

    The high investment related to the acquisition of Flexible Manufacturing Systems forces firms to a better utilization of the machines. Different actions can be taken in order to avoid idle times of the machines: reduction of the unproductive times (time dedicated to rapid movements, tool exchange, pallet exchange, etc.), improvement of machines and, not last, a better management of the resources. The paper proposes a new policy for the management of tool operations in parallel machine FMS to minimize the idle times due to the lack of tools. The proposed policy uses new opportunities in manufacturing technology related with the use of network part programs in NC machines. It is already known in literature the potentiality of network part programs, more flexible than traditional sequential part programs that execute simply the rigid list of operations. Network part programs allow the different alternative ways to process each part. The way in which network part programs are executed by machines depends on the state of the tools and availability of the tools. The proposed method has been compared with other existing ones based on a real test case, a parallel machine FMS with two machines and a tool carrier.

  5. Knowledge-directed electroencephalography (EEG) signal analysis with recurrent context-learning neural networks

    NASA Astrophysics Data System (ADS)

    Fu, Li-Min

    1994-06-01

    EEG signal analysis is a key to the understanding of brain activities. Traditionally, this process involves quantifying the signal in terms of frequency and amplitude, on which basis a number of waveforms have been identified. The complexity of EEG signals warrants the construction of a computer program for automatic interpretation. Symbolic knowledge is being built up for correlating the quantity of certain waveforms and brain behavior, and this knowledge can be readily programmed into a knowledge-based system (expert system) for various purposes such as cognitive research, neurological evaluation, and clinical diagnosis. The presented approach employs a knowledge-based neural network in conjunction with a recurrent neural network model as a memory deice which conducts context processing. This research emphasizes the need for the exploitation of `knowledge' and `context' in signal analysis.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed Central

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

    2016-01-01

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

  8. Space Environmental Viewing and Analysis Network (SEVAN) - A Network of Neutron Monitors in Bulgaria

    NASA Astrophysics Data System (ADS)

    Georgieva, K.

    2006-11-01

    katyagerogieva@msn.com A network of middle to low latitude particle detectors called SEVAN (Space Environmental Viewing and Analysis Network) aims to improve fundamental research of the space weather conditions and provide possibilities to perform short and long-term forecasts of the dangerous consequences of the space storms. The network will detect changing fluxes of the most species of secondary cosmic rays at different altitudes and latitudes, thus constituting powerful integrated device in exploring solar modulation effects. Recently two more countries have decided to host cosmic ray monitors - Bulgaria and Croatia.

  9. Comprehensive Analysis: A Holistic Approach to Program Review.

    ERIC Educational Resources Information Center

    Messina, Robert C.; Fagans, Alice C.

    In response to problems with the cyclical model of program review and reduced state and county funding, Burlington County College (BCC), in New Jersey, implemented a comprehensive analysis process to holistically assess program performance and resource allocation. First, program review goals were established and the major programs/services at BCC…

  10. Network Configuration of Oracle and Database Programming Using SQL

    NASA Technical Reports Server (NTRS)

    Davis, Melton; Abdurrashid, Jibril; Diaz, Philip; Harris, W. C.

    2000-01-01

    A database can be defined as a collection of information organized in such a way that it can be retrieved and used. A database management system (DBMS) can further be defined as the tool that enables us to manage and interact with the database. The Oracle 8 Server is a state-of-the-art information management environment. It is a repository for very large amounts of data, and gives users rapid access to that data. The Oracle 8 Server allows for sharing of data between applications; the information is stored in one place and used by many systems. My research will focus primarily on SQL (Structured Query Language) programming. SQL is the way you define and manipulate data in Oracle's relational database. SQL is the industry standard adopted by all database vendors. When programming with SQL, you work on sets of data (i.e., information is not processed one record at a time).

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

    PubMed Central

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

    2016-01-01

    The spatial distribution of urban service facilities is largely constrained by the road network. In this study, network point pattern analysis and correlation analysis were used to analyze the relationship between road network and healthcare facility distribution. The weighted network kernel density estimation method proposed in this study identifies significant differences between the outside and inside areas of the Ming city wall. The results of network K-function analysis show that private hospitals are more evenly distributed than public hospitals, and pharmacy stores tend to cluster around hospitals along the road network. After computing the correlation analysis between different categorized hospitals and street centrality, we find that the distribution of these hospitals correlates highly with the street centralities, and that the correlations are higher with private and small hospitals than with public and large hospitals. The comprehensive analysis results could help examine the reasonability of existing urban healthcare facility distribution and optimize the location of new healthcare facilities. PMID:27548197

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

    PubMed

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

    2016-08-18

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

  13. Spatial analysis of the Chania prefecture: Crete triangulation network quality

    NASA Astrophysics Data System (ADS)

    Achilleos, Georgios

    2016-08-01

    The network of trigonometric points of a region is the basis upon which any form of cartographic work is attached to the national geodetic coordinate system (data collection, processing, output presentations) and not only. The products of the cartographic work (cartographic representations), provide the background which is used in cases of spatial planning and development strategy. This trigonometric network, except that, provides to a single cartographic work, the ability to exist within a unified official state geodetic reference system, simultaneously determines the quality of the result, since the trigonometric network data that are used, have their own quality. In this paper, we present the research of spatial quality of the trigonometric network of Chania Prefecture in Crete. This analysis examines the triangulation network points, both with respect to their spatial position (distribution in space), and in their accuracy (horizontally and vertically).

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

    SciTech Connect

    LeBlanc, C.; Hruska, S.I.; Katholi, C.R.; Unnasch, T.R.

    1994-12-31

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

  15. Random matrix analysis of localization properties of gene coexpression network.

    PubMed

    Jalan, Sarika; Solymosi, Norbert; Vattay, Gábor; Li, Baowen

    2010-04-01

    We analyze gene coexpression network under the random matrix theory framework. The nearest-neighbor spacing distribution of the adjacency matrix of this network follows Gaussian orthogonal statistics of random matrix theory (RMT). Spectral rigidity test follows random matrix prediction for a certain range and deviates afterwards. Eigenvector analysis of the network using inverse participation ratio suggests that the statistics of bulk of the eigenvalues of network is consistent with those of the real symmetric random matrix, whereas few eigenvalues are localized. Based on these IPR calculations, we can divide eigenvalues in three sets: (a) The nondegenerate part that follows RMT. (b) The nondegenerate part, at both ends and at intermediate eigenvalues, which deviates from RMT and expected to contain information about important nodes in the network. (c) The degenerate part with zero eigenvalue, which fluctuates around RMT-predicted value. We identify nodes corresponding to the dominant modes of the corresponding eigenvectors and analyze their structural properties.

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

    NASA Astrophysics Data System (ADS)

    Matesanz, David; Ortega, Guillermo J.

    2015-10-01

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

  17. A systematic review protocol: social network analysis of tobacco use

    PubMed Central

    2014-01-01

    Background Tobacco use is the single most preventable cause of death in the world. Evidence indicates that behaviours such as tobacco use can influence social networks, and that social network structures can influence behaviours. Social network analysis provides a set of analytic tools to undertake methodical analysis of social networks. We will undertake a systematic review to provide a comprehensive synthesis of the literature regarding social network analysis and tobacco use. The review will answer the following research questions: among participants who use tobacco, does social network structure/position influence tobacco use? Does tobacco use influence peer selection? Does peer selection influence tobacco use? Methods We will follow the Preferred Reporting Items for Systemic Reviews and Meta-Analyses (PRISMA) guidelines and search the following databases for relevant articles: CINAHL (Cumulative Index to Nursing and Allied Health Literature); Informit Health Collection; PsycINFO; PubMed/MEDLINE; Scopus/Embase; Web of Science; and the Wiley Online Library. Keywords include tobacco; smoking; smokeless; cigarettes; cigar and ‘social network’ and reference lists of included articles will be hand searched. Studies will be included that provide descriptions of social network analysis of tobacco use. Qualitative, quantitative and mixed method data that meets the inclusion criteria for the review, including methodological rigour, credibility and quality standards, will be synthesized using narrative synthesis. Results will be presented using outcome statistics that address each of the research questions. Discussion This systematic review will provide a timely evidence base on the role of social network analysis of tobacco use, forming a basis for future research, policy and practice in this area. This systematic review will synthesise the evidence, supporting the hypothesis that social network structures can influence tobacco use. This will also include exploring

  18. DATA MONITORING AND ANALYSIS PROGRAM MANUAL

    SciTech Connect

    Gravois, Melanie

    2007-07-06

    This procedure provides guidelines and techniques for analyzing and trending data using statistical methods for Lawrence Berkeley National Laboratory (LBNL). This procedure outlines the steps used in data analysis and trending. It includes guidelines for performing data analysis and for monitoring (or controlling) processes using performance indicators. This procedure is used when trending and analyzing item characteristics and reliability, process implementation, and other quality-related information to identify items, services, activities, and processes needing improvement, in accordance with 10 CFR Part 830, Subpart A, U.S. Department of Energy (DOE) Order 414.1C, and University of California (UC) Assurance Plan for LBNL. Trend codes, outlined in Attachment 4, are assigned to issues at the time of initiation and entry into the Corrective Action Tracking System (CATS) database in accordance with LBNL/PUB-5519 (1), Issues Management Program Manual. Throughout this procedure, the term performance is used to encompass all aspects of performance including quality, timeliness, efficiency, effectiveness, and reliability. Data analysis tools are appropriate whenever quantitative information describing the performance of an item, service, or process can be obtained.

  19. Network Configuration Analysis for Formation Flying Satellites

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  20. Complex networks analysis of obstructive nephropathy data

    NASA Astrophysics Data System (ADS)

    Zanin, M.; Boccaletti, S.

    2011-09-01

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