Science.gov

Sample records for network advanced analysis

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  2. System analysis of power transients in advanced WDM networks

    NASA Astrophysics Data System (ADS)

    Gorinevsky, Dimitry; Farber, Gennady

    2002-06-01

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

  3. Advancing complementary and alternative medicine through social network analysis and agent-based modeling.

    PubMed

    Frantz, Terrill L

    2012-01-01

    This paper introduces the contemporary perspectives and techniques of social network analysis (SNA) and agent-based modeling (ABM) and advocates applying them to advance various aspects of complementary and alternative medicine (CAM). SNA and ABM are invaluable methods for representing, analyzing and projecting complex, relational, social phenomena; they provide both an insightful vantage point and a set of analytic tools that can be useful in a wide range of contexts. Applying these methods in the CAM context can aid the ongoing advances in the CAM field, in both its scientific aspects and in developing broader acceptance in associated stakeholder communities. PMID:22327550

  4. Space lab system analysis: Advanced Solid Rocket Motor (ASRM) communications networks analysis

    NASA Technical Reports Server (NTRS)

    Ingels, Frank M.; Moorhead, Robert J., II; Moorhead, Jane N.; Shearin, C. Mark; Thompson, Dale R.

    1990-01-01

    A synopsis of research on computer viruses and computer security is presented. A review of seven technical meetings attended is compiled. A technical discussion on the communication plans for the ASRM facility is presented, with a brief tutorial on the potential local area network media and protocols.

  5. Targeted drugs for unselected patients with advanced non-small-cell lung cancer: a network meta-analysis

    PubMed Central

    Zhao, Yueguang; Wang, Fang; Li, Shanshan; Wang, Xiaojie; Shou, Tao; Luo, Ying

    2016-01-01

    Background Currently, targeted therapy has shown encouraging treatment benefits in selected patients with advanced non-small cell lung cancer (NSCLC). However, the comparative benefits of targeted drugs and chemotherapy (CT) treatments in unselected patients are not clear. We therefore conduct a network meta-analysis to assess the relative efficacy and safety of these regimens. Methods PubMed, EMBASE, Cochrane Library and abstracts from major scientific meetings were searched for eligible literatures. The odds ratio (OR) for objective response rate (ORR) and safety was used for pooling effect sizes. Bayesian network meta-analysis was conducted to calculate the efficacy and safety of all included treatments. All tests of statistical significance were two sided. Results A total of 13,060 patients from 24 randomized controlled trials (RCT) were assessed. The targeted agents included bevacizumab (Bev), gefitinib (Gef), erlotinib (Erl) and cetuximab (Cet). Network meta-analysis showed that Bev + CT had a statistically significantly higher incidence of ORR relative to the other six different treatments, including placebo (OR =6.47; 95% CI, 3.85–10.29), Erl (OR =2.81; 95% CI, 2.08–3.70), CT (OR =1.92; 95% CI, 1.61–2.28), Gef (OR =1.40; 95% CI, 1.10–1.75), Erl + CT (OR =1.46; 95% CI, 1.17–1.80) and Gef + CT (OR =1.75; 95% CI, 1.36–2.22), whereas placebo and Erl were associated with statistically significantly lower incidence of ORR. Trend analyses of rank probability revealed that Bev + CT had the highest probability of being the best treatment arm in term of ORR, followed by Cet + CT. Meanwhile, Cet + CT showed significant severer rash and thrombocytopenia compared with Bev + CT. Gef was probable to be the rank 3 for ORR but was associated with relatively low risk for grade ≥3 toxicities. Conclusions Our study suggested that Bev + CT may offer better ORR in the treatment of unselected patients with advanced NSCLC. Future studies will be needed to investigate

  6. Advanced local area network concepts

    NASA Technical Reports Server (NTRS)

    Grant, Terry

    1985-01-01

    Development of a good model of the data traffic requirements for Local Area Networks (LANs) onboard the Space Station is the driving problem in this work. A parameterized workload model is under development. An analysis contract has been started specifically to capture the distributed processing requirements for the Space Station and then to develop a top level model to simulate how various processing scenarios can handle the workload and what data communication patterns result. A summary of the Local Area Network Extendsible Simulator 2 Requirements Specification and excerpts from a grant report on the topological design of fiber optic local area networks with application to Expressnet are given.

  7. 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

  8. Advance Network Reservation and Provisioning for Science

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2009-07-10

    We are witnessing a new era that offers new opportunities to conduct scientific research with the help of recent advancements in computational and storage technologies. Computational intensive science spans multiple scientific domains, such as particle physics, climate modeling, and bio-informatics simulations. These large-scale applications necessitate collaborators to access very large data sets resulting from simulations performed in geographically distributed institutions. Furthermore, often scientific experimental facilities generate massive data sets that need to be transferred to validate the simulation data in remote collaborating sites. A major component needed to support these needs is the communication infrastructure which enables high performance visualization, large volume data analysis, and also provides access to computational resources. In order to provide high-speed on-demand data access between collaborating institutions, national governments support next generation research networks such as Internet 2 and ESnet (Energy Sciences Network). Delivering network-as-a-service that provides predictable performance, efficient resource utilization and better coordination between compute and storage resources is highly desirable. In this paper, we study network provisioning and advanced bandwidth reservation in ESnet for on-demand high performance data transfers. We present a novel approach for path finding in time-dependent transport networks with bandwidth guarantees. We plan to improve the current ESnet advance network reservation system, OSCARS [3], by presenting to the clients, the possible reservation options and alternatives for earliest completion time and shortest transfer duration. The Energy Sciences Network (ESnet) provides high bandwidth connections between research laboratories and academic institutions for data sharing and video/voice communication. The ESnet On-Demand Secure Circuits and Advance Reservation System (OSCARS) establishes

  9. Communication services for advanced network applications.

    SciTech Connect

    Bresnahan, J.; Foster, I.; Insley, J.; Toonen, B.; Tuecke, S.

    1999-06-10

    Advanced network applications such as remote instrument control, collaborative environments, and remote I/O are distinguished by traditional applications such as videoconferencing by their need to create multiple, heterogeneous flows with different characteristics. For example, a single application may require remote I/O for raw datasets, shared controls for a collaborative analysis system, streaming video for image rendering data, and audio for collaboration. Furthermore, each flow can have different requirements in terms of reliability, network quality of service, security, etc. They argue that new approaches to communication services, protocols, and network architecture are required both to provide high-level abstractions for common flow types and to support user-level management of flow creation and quality. They describe experiences with the development of such applications and communication services.

  10. Analysis of space network loading

    NASA Technical Reports Server (NTRS)

    Simons, Mark; Larrson, Gus

    1994-01-01

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

  11. Recent advances in elementary flux modes and yield space analysis as useful tools in metabolic network studies.

    PubMed

    Horvat, Predrag; Koller, Martin; Braunegg, Gerhart

    2015-09-01

    A review of the use of elementary flux modes (EFMs) and their applications in metabolic engineering covered with yield space analysis (YSA) is presented. EFMs are an invaluable tool in mathematical modeling of biochemical processes. They are described from their inception in 1994, followed by various improvements of their computation in later years. YSA constitutes another precious tool for metabolic network modeling, and is presented in details along with EFMs in this article. The application of these techniques is discussed for several case studies of metabolic network modeling provided in respective original articles. The article is concluded by some case studies in which the application of EFMs and YSA turned out to be most useful, such as the analysis of intracellular polyhydroxyalkanoate (PHA) formation and consumption in Cupriavidus necator, including the constraint-based description of the steady-state flux cone of the strain's metabolic network, the profound analysis of a continuous five-stage bioreactor cascade for PHA production by C. necator using EFMs and, finally, the study of metabolic fluxes in the metabolic network of C. necator cultivated on glycerol. PMID:26066363

  12. Advancements in metro optical network architectures

    NASA Astrophysics Data System (ADS)

    Paraschis, Loukas

    2005-02-01

    This paper discusses the innovation in network architectures, and optical transport, that enables metropolitan networks to cost-effectively scale to hundreds Gb/s of capacity, and to hundreds km of reach, and to also meet the diverse service needs of enterprise and residential applications. A converged metro network, where Ethernet/IP services, and traditional TDM traffic operate over an intelligent WDM transport layer is increasingly becoming the most attractive architecture addressing the primary need of network operators for significantly improved capital and operational network cost. At the same time, this converged network has to leverage advanced technology, and introduce intelligence in order to significantly improve the deployment and manageability of WDM transport. The most important system advancements and the associated technology innovations that enhance the cost-effectiveness of metropolitan optical networks are being reviewed.

  13. Advanced radio over fiber network technologies.

    PubMed

    Novak, Dalma; Waterhouse, Rod

    2013-09-23

    The evolution of wireless communication networks supporting emerging broadband services and applications offers new opportunities for realizing integrated optical and wireless network infrastructures. We report on some of our recent activities investigating advanced technologies for next generation converged optical wireless networks. Developments in Active Antenna Systems, mobile fronthaul architectures, and 60 GHz fiber distributed wireless networks are described. We also discuss the potential for analog radio over fiber distribution links as a viable solution for meeting the capacity requirements of new network architectures. PMID:24104183

  14. Advanced Networks in Motion Mobile Sensorweb

    NASA Technical Reports Server (NTRS)

    Ivancic, William D.; Stewart, David H.

    2011-01-01

    Advanced mobile networking technology applicable to mobile sensor platforms was developed, deployed and demonstrated. A two-tier sensorweb design was developed. The first tier utilized mobile network technology to provide mobility. The second tier, which sits above the first tier, utilizes 6LowPAN (Internet Protocol version 6 Low Power Wireless Personal Area Networks) sensors. The entire network was IPv6 enabled. Successful mobile sensorweb system field tests took place in late August and early September of 2009. The entire network utilized IPv6 and was monitored and controlled using a remote Web browser via IPv6 technology. This paper describes the mobile networking and 6LowPAN sensorweb design, implementation, deployment and testing as well as wireless systems and network monitoring software developed to support testing and validation.

  15. Advances in neural networks research: an introduction.

    PubMed

    Kozma, Robert; Bressler, Steven; Perlovsky, Leonid; Venayagamoorthy, Ganesh Kumar

    2009-01-01

    The present Special Issue "Advances in Neural Networks Research: IJCNN2009" provides a state-of-art overview of the field of neural networks. It includes 39 papers from selected areas of the 2009 International Joint Conference on Neural Networks (IJCNN2009). IJCNN2009 took place on June 14-19, 2009 in Atlanta, Georgia, USA, and it represents an exemplary collaboration between the International Neural Networks Society and the IEEE Computational Intelligence Society. Topics in this issue include neuroscience and cognitive science, computational intelligence and machine learning, hybrid techniques, nonlinear dynamics and chaos, various soft computing technologies, intelligent signal processing and pattern recognition, bioinformatics and biomedicine, and engineering applications. PMID:19632811

  16. Efficacy of the Additional Neoadjuvant Chemotherapy to Concurrent Chemoradiotherapy for Patients with Locoregionally Advanced Nasopharyngeal Carcinoma: a Bayesian Network Meta-analysis of Randomized Controlled Trials

    PubMed Central

    Chen, Yu-Pei; Guo, Rui; Liu, Na; Liu, Xu; Mao, Yan-Ping; Tang, Ling-Long; Zhou, Guan-Qun; Lin, Ai-Hua; Sun, Ying; Ma, Jun

    2015-01-01

    Background: Due to the lack of studies, it remains unclear whether the additional neoadjuvant chemotherapy (NACT) to concurrent chemoradiotherapy (CCRT) is superior to CCRT alone for locoregionally advanced nasopharyngeal carcinoma (NPC). The main objective of this Bayesian network meta-analysis was to determine the efficacy of NACT+CCRT as compared with CCRT alone. Methods: We comprehensively searched databases and extracted data from randomized controlled trials involving NPC patients who received NACT+CCRT, CCRT, NACT+radiotherapy (RT), or RT. Overall survival (OS) with hazard ratio (HR), and locoregional recurrence rate (LRR) and distant metastasis rate (DMR) with relative risks (RRs), were concerned. Results: Nine trials involving 1988 patients were analyzed. In the network meta-analysis, there was significant benefit of NACT+CCRT over CCRT for DMR (RR=0.54, 95% credible interval [CrI]=0.27-0.94). However, NACT+CCRT had a tendency to worsen locoregional control significantly as compared with CCRT (RR =1.71, 95%CrI =0.94-2.84), and no significant improvement in OS was found (HR =0.73, 95%CrI=0.40-1.23). Conclusions: NACT+CCRT is associated with reduced distant failure as compared with CCRT alone, and whether the additional NACT can improve survival for locoregionally advanced NPC should be further explored. Optimizing regimens and identifying patients at high risk of metastasis may enhance the efficacy of NACT+CCRT. PMID:26284140

  17. Advanced networks and computing in healthcare

    PubMed Central

    Ackerman, Michael

    2011-01-01

    As computing and network capabilities continue to rise, it becomes increasingly important to understand the varied applications for using them to provide healthcare. The objective of this review is to identify key characteristics and attributes of healthcare applications involving the use of advanced computing and communication technologies, drawing upon 45 research and development projects in telemedicine and other aspects of healthcare funded by the National Library of Medicine over the past 12 years. Only projects publishing in the professional literature were included in the review. Four projects did not publish beyond their final reports. In addition, the authors drew on their first-hand experience as project officers, reviewers and monitors of the work. Major themes in the corpus of work were identified, characterizing key attributes of advanced computing and network applications in healthcare. Advanced computing and network applications are relevant to a range of healthcare settings and specialties, but they are most appropriate for solving a narrower range of problems in each. Healthcare projects undertaken primarily to explore potential have also demonstrated effectiveness and depend on the quality of network service as much as bandwidth. Many applications are enabling, making it possible to provide service or conduct research that previously was not possible or to achieve outcomes in addition to those for which projects were undertaken. Most notable are advances in imaging and visualization, collaboration and sense of presence, and mobility in communication and information-resource use. PMID:21486877

  18. Advanced networks and computing in healthcare.

    PubMed

    Ackerman, Michael; Locatis, Craig

    2011-01-01

    As computing and network capabilities continue to rise, it becomes increasingly important to understand the varied applications for using them to provide healthcare. The objective of this review is to identify key characteristics and attributes of healthcare applications involving the use of advanced computing and communication technologies, drawing upon 45 research and development projects in telemedicine and other aspects of healthcare funded by the National Library of Medicine over the past 12 years. Only projects publishing in the professional literature were included in the review. Four projects did not publish beyond their final reports. In addition, the authors drew on their first-hand experience as project officers, reviewers and monitors of the work. Major themes in the corpus of work were identified, characterizing key attributes of advanced computing and network applications in healthcare. Advanced computing and network applications are relevant to a range of healthcare settings and specialties, but they are most appropriate for solving a narrower range of problems in each. Healthcare projects undertaken primarily to explore potential have also demonstrated effectiveness and depend on the quality of network service as much as bandwidth. Many applications are enabling, making it possible to provide service or conduct research that previously was not possible or to achieve outcomes in addition to those for which projects were undertaken. Most notable are advances in imaging and visualization, collaboration and sense of presence, and mobility in communication and information-resource use. PMID:21486877

  19. Advanced Scientific Computing Research Network Requirements

    SciTech Connect

    Bacon, Charles; Bell, Greg; Canon, Shane; Dart, Eli; Dattoria, Vince; Goodwin, Dave; Lee, Jason; Hicks, Susan; Holohan, Ed; Klasky, Scott; Lauzon, Carolyn; Rogers, Jim; Shipman, Galen; Skinner, David; Tierney, Brian

    2013-03-08

    The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In October 2012, ESnet and the Office of Advanced Scientific Computing Research (ASCR) of the DOE SC organized a review to characterize the networking requirements of the programs funded by the ASCR program office. The requirements identified at the review are summarized in the Findings section, and are described in more detail in the body of the report.

  20. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 3: Advanced networks and economics

    NASA Technical Reports Server (NTRS)

    1986-01-01

    This study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  1. Advanced PFBC transient analysis

    SciTech Connect

    White, J.S.; Bonk, D.L.

    1997-05-01

    Transient modeling and analysis of advanced Pressurized Fluidized Bed Combustion (PFBC) systems is a research area that is currently under investigation by the US Department of Energy`s Federal Energy Technology Center (FETC). The object of the effort is to identify key operating parameters that affect plant performance and then quantify the basic response of major sub-systems to changes in operating conditions. PC-TRAX{trademark}, a commercially available dynamic software program, was chosen and applied in this modeling and analysis effort. This paper describes the development of a series of TRAX-based transient models of advanced PFBC power plants. These power plants burn coal or other suitable fuel in a PFBC, and the high temperature flue gas supports low-Btu fuel gas or natural gas combustion in a gas turbine topping combustor. When it is utilized, the low-Btu fuel gas is produced in a bubbling bed carbonizer. High temperature, high pressure combustion products exiting the topping combustor are expanded in a modified gas turbine to generate electrical power. Waste heat from the system is used to raise and superheat steam for a reheat steam turbine bottoming cycle that generates additional electrical power. Basic control/instrumentation models were developed and modeled in PC-TRAX and used to investigate off-design plant performance. System performance for various transient conditions and control philosophies was studied.

  2. Advanced mobile networking, sensing, and controls.

    SciTech Connect

    Feddema, John Todd; Kilman, Dominique Marie; Byrne, Raymond Harry; Young, Joseph G.; Lewis, Christopher L.; Van Leeuwen, Brian P.; Robinett, Rush D. III; Harrington, John J.

    2005-03-01

    This report describes an integrated approach for designing communication, sensing, and control systems for mobile distributed systems. Graph theoretic methods are used to analyze the input/output reachability and structural controllability and observability of a decentralized system. Embedded in each network node, this analysis will automatically reconfigure an ad hoc communication network for the sensing and control task at hand. The graph analysis can also be used to create the optimal communication flow control based upon the spatial distribution of the network nodes. Edge coloring algorithms tell us that the minimum number of time slots in a planar network is equal to either the maximum number of adjacent nodes (or degree) of the undirected graph plus some small number. Therefore, the more spread out that the nodes are, the fewer number of time slots are needed for communication, and the smaller the latency between nodes. In a coupled system, this results in a more responsive sensor network and control system. Network protocols are developed to propagate this information, and distributed algorithms are developed to automatically adjust the number of time slots available for communication. These protocols and algorithms must be extremely efficient and only updated as network nodes move. In addition, queuing theory is used to analyze the delay characteristics of Carrier Sense Multiple Access (CSMA) networks. This report documents the analysis, simulation, and implementation of these algorithms performed under this Laboratory Directed Research and Development (LDRD) effort.

  3. Advance lightpath provisioning in interdomain optical networks

    NASA Astrophysics Data System (ADS)

    Hafid, A.; Maach, A.; Khair, M. G.; Drissi, J.

    2005-11-01

    In interconnected optical networks, users submit lightpath requests at the time they wish to establish the lightpath. The service provider consults the information gathered by the interdomain routing protocols for available resources. For each request, the network must decide immediately whether to accept or reject the request. In this model, there is always the uncertainty of whether the user will be able to establish the desired lightpath at the desired time or not. Furthermore, in the context of a number of applications, e.g., grid applications, users need to set up lightpaths in advance to perform their activities that are planned in advance. We propose a new interdomain routing protocol called Advance Optical Routing Border Gateway Protocol (AORBGP) and a scheme that allows the setup of interdomain lightpaths in advance. AORBGP allows gathering information about interdomain paths and availability of wavelengths in the future. The proposed advance lightpath setup scheme makes use of AORBGP to get information about available resources (i.e., wavelengths) required to process lightpath setup requests. One of the key innovations of the scheme is that it provides the user with alternatives, carefully selected, when his or her request cannot be accommodated because of resource shortages. Indeed, the scheme provides the user with options to set up a lightpath later than the requested start time or with shorter duration than the requested duration. We performed a set of simulations to evaluate the benefits of the proposed scheme and the effect of a number of parameters on the performance of AORBGP.

  4. Communication Network Analysis Methods.

    ERIC Educational Resources Information Center

    Farace, Richard V.; Mabee, Timothy

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

  5. A perspective on the advancement of natural language processing tasks via topological analysis of complex networks. Comment on "Approaching human language with complex networks" by Cong and Liu

    NASA Astrophysics Data System (ADS)

    Amancio, Diego Raphael

    2014-12-01

    Concepts and methods of complex networks have been applied to probe the properties of a myriad of real systems [1]. The finding that written texts modeled as graphs share several properties of other completely different real systems has inspired the study of language as a complex system [2]. Actually, language can be represented as a complex network in its several levels of complexity. As a consequence, morphological, syntactical and semantical properties have been employed in the construction of linguistic networks [3]. Even the character level has been useful to unfold particular patterns [4,5]. In the review by Cong and Liu [6], the authors emphasize the need to use the topological information of complex networks modeling the various spheres of the language to better understand its origins, evolution and organization. In addition, the authors cite the use of networks in applications aiming at holistic typology and stylistic variations. In this context, I will discuss some possible directions that could be followed in future research directed towards the understanding of language via topological characterization of complex linguistic networks. In addition, I will comment the use of network models for language processing applications. Additional prospects for future practical research lines will also be discussed in this comment.

  6. 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

  7. Nanocarbon networks for advanced rechargeable lithium batteries.

    PubMed

    Xin, Sen; Guo, Yu-Guo; Wan, Li-Jun

    2012-10-16

    Carbon is one of the essential elements in energy storage. In rechargeable lithium batteries, researchers have considered many types of nanostructured carbons, such as carbon nanoparticles, carbon nanotubes, graphene, and nanoporous carbon, as anode materials and, especially, as key components for building advanced composite electrode materials. Nanocarbons can form efficient three-dimensional conducting networks that improve the performance of electrode materials suffering from the limited kinetics of lithium storage. Although the porous structure guarantees a fast migration of Li ions, the nanocarbon network can serve as an effective matrix for dispersing the active materials to prevent them from agglomerating. The nanocarbon network also affords an efficient electron pathway to provide better electrical contacts. Because of their structural stability and flexibility, nanocarbon networks can alleviate the stress and volume changes that occur in active materials during the Li insertion/extraction process. Through the elegant design of hierarchical electrode materials with nanocarbon networks, researchers can improve both the kinetic performance and the structural stability of the electrode material, which leads to optimal battery capacity, cycling stability, and rate capability. This Account summarizes recent progress in the structural design, chemical synthesis, and characterization of the electrochemical properties of nanocarbon networks for Li-ion batteries. In such systems, storage occurs primarily in the non-carbon components, while carbon acts as the conductor and as the structural buffer. We emphasize representative nanocarbon networks including those that use carbon nanotubes and graphene. We discuss the role of carbon in enhancing the performance of various electrode materials in areas such as Li storage, Li ion and electron transport, and structural stability during cycling. We especially highlight the use of graphene to construct the carbon conducting

  8. Collaboration and entanglement: An actor-network theory analysis of team-based intraprofessional care for patients with advanced heart failure.

    PubMed

    McDougall, A; Goldszmidt, M; Kinsella, E A; Smith, S; Lingard, L

    2016-09-01

    Despite calls for more interprofessional and intraprofessional team-based approaches in healthcare, we lack sufficient understanding of how this happens in the context of patient care teams. This multi-perspective, team-based interview study examined how medical teams negotiated collaborative tensions. From 2011 to 2013, 50 patients across five sites in three Canadian provinces were interviewed about their care experiences and were asked to identify members of their health care teams. Patient-identified team members were subsequently interviewed to form 50 "Team Sampling Units" (TSUs), consisting of 209 interviews with patients, caregivers and healthcare providers. Results are gathered from a focused analysis of 13 TSUs where intraprofessional collaborative tensions involved treating fluid overload, or edema, a common HF symptom. Drawing on actor-network theory (ANT), the analysis focused on intraprofessional collaboration between specialty care teams in cardiology and nephrology. The study found that despite a shared narrative of common purpose between cardiology teams and nephrology teams, fluid management tools and techniques formed sites of collaborative tension. In particular, care activities involved asynchronous clinical interpretations, geographically distributed specialist care, fragmented forms of communication, and uncertainty due to clinical complexity. Teams 'disentangled' fluid in order to focus on its physiological function and mobilisation. Teams also used distinct 'framings' of fluid management that created perceived collaborative tensions. This study advances collaborative entanglement as a conceptual framework for understanding, teaching, and potentially ameliorating some of the tensions that manifest during intraprofessional care for patients with complex, chronic disease. PMID:27490299

  9. Advanced Optical Burst Switched Network Concepts

    NASA Astrophysics Data System (ADS)

    Nejabati, Reza; Aracil, Javier; Castoldi, Piero; de Leenheer, Marc; Simeonidou, Dimitra; Valcarenghi, Luca; Zervas, Georgios; Wu, Jian

    In recent years, as the bandwidth and the speed of networks have increased significantly, a new generation of network-based applications using the concept of distributed computing and collaborative services is emerging (e.g., Grid computing applications). The use of the available fiber and DWDM infrastructure for these applications is a logical choice offering huge amounts of cheap bandwidth and ensuring global reach of computing resources [230]. Currently, there is a great deal of interest in deploying optical circuit (wavelength) switched network infrastructure for distributed computing applications that require long-lived wavelength paths and address the specific needs of a small number of well-known users. Typical users are particle physicists who, due to their international collaborations and experiments, generate enormous amounts of data (Petabytes per year). These users require a network infrastructures that can support processing and analysis of large datasets through globally distributed computing resources [230]. However, providing wavelength granularity bandwidth services is not an efficient and scalable solution for applications and services that address a wider base of user communities with different traffic profiles and connectivity requirements. Examples of such applications may be: scientific collaboration in smaller scale (e.g., bioinformatics, environmental research), distributed virtual laboratories (e.g., remote instrumentation), e-health, national security and defense, personalized learning environments and digital libraries, evolving broadband user services (i.e., high resolution home video editing, real-time rendering, high definition interactive TV). As a specific example, in e-health services and in particular mammography applications due to the size and quantity of images produced by remote mammography, stringent network requirements are necessary. Initial calculations have shown that for 100 patients to be screened remotely, the network

  10. 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.

  11. Analysis of network statistics

    NASA Astrophysics Data System (ADS)

    Cottrell, R. L. A.

    1987-08-01

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

  12. Advanced systems engineering and network planning support

    NASA Technical Reports Server (NTRS)

    Walters, David H.; Barrett, Larry K.; Boyd, Ronald; Bazaj, Suresh; Mitchell, Lionel; Brosi, Fred

    1990-01-01

    The objective of this task was to take a fresh look at the NASA Space Network Control (SNC) element for the Advanced Tracking and Data Relay Satellite System (ATDRSS) such that it can be made more efficient and responsive to the user by introducing new concepts and technologies appropriate for the 1997 timeframe. In particular, it was desired to investigate the technologies and concepts employed in similar systems that may be applicable to the SNC. The recommendations resulting from this study include resource partitioning, on-line access to subsets of the SN schedule, fluid scheduling, increased use of demand access on the MA service, automating Inter-System Control functions using monitor by exception, increase automation for distributed data management and distributed work management, viewing SN operational control in terms of the OSI Management framework, and the introduction of automated interface management.

  13. 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.

  14. Advanced Economic Analysis

    NASA Technical Reports Server (NTRS)

    Greenberg, Marc W.; Laing, William

    2013-01-01

    An Economic Analysis (EA) is a systematic approach to the problem of choosing the best method of allocating scarce resources to achieve a given objective. An EA helps guide decisions on the "worth" of pursuing an action that departs from status quo ... an EA is the crux of decision-support.

  15. 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.

  16. Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

    DOE PAGESBeta

    Bracale, Antonio; Barros, Julio; Cacciapuoti, Angela Sara; Chang, Gary; Dall'Anese, Emiliano

    2015-06-10

    Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users andmore » vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.« less

  17. Guest Editorial Introduction to the Special Issue on 'Advanced Signal Processing Techniques and Telecommunications Network Infrastructures for Smart Grid Analysis, Monitoring, and Management'

    SciTech Connect

    Bracale, Antonio; Barros, Julio; Cacciapuoti, Angela Sara; Chang, Gary; Dall'Anese, Emiliano

    2015-06-10

    Electrical power systems are undergoing a radical change in structure, components, and operational paradigms, and are progressively approaching the new concept of smart grids (SGs). Future power distribution systems will be characterized by the simultaneous presence of various distributed resources, such as renewable energy systems (i.e., photovoltaic power plant and wind farms), storage systems, and controllable/non-controllable loads. Control and optimization architectures will enable network-wide coordination of these grid components in order to improve system efficiency and reliability and to limit greenhouse gas emissions. In this context, the energy flows will be bidirectional from large power plants to end users and vice versa; producers and consumers will continuously interact at different voltage levels to determine in advance the requests of loads and to adapt the production and demand for electricity flexibly and efficiently also taking into account the presence of storage systems.

  18. Neural Networks for Readability Analysis.

    ERIC Educational Resources Information Center

    McEneaney, John E.

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

  19. Optical Multiple Access Network (OMAN) for advanced processing satellite applications

    NASA Technical Reports Server (NTRS)

    Mendez, Antonio J.; Gagliardi, Robert M.; Park, Eugene; Ivancic, William D.; Sherman, Bradley D.

    1991-01-01

    An OMAN breadboard for exploring advanced processing satellite circuit switch applications is introduced. Network architecture, hardware trade offs, and multiple user interference issues are presented. The breadboard test set up and experimental results are discussed.

  20. Recent advancements towards green optical networks

    NASA Astrophysics Data System (ADS)

    Davidson, Alan; Glesk, Ivan; Buis, Adrianus; Wang, Junjia; Chen, Lawrence

    2014-12-01

    Recent years have seen a rapid growth in demand for ultra high speed data transmission with end users expecting fast, high bandwidth network access. With this rapid growth in demand, data centres are under pressure to provide ever increasing data rates through their networks and at the same time improve the quality of data handling in terms of reduced latency, increased scalability and improved channel speed for users. However as data rates increase, present technology based on well-established CMOS technology is becoming increasingly difficult to scale and consequently data networks are struggling to satisfy current network demand. In this paper the interrelated issues of electronic scalability, power consumption, limited copper interconnect bandwidth and the limited speed of CMOS electronics will be explored alongside the tremendous bandwidth potential of optical fibre based photonic networks. Some applications of photonics to help alleviate the speed and latency in data networks will be discussed.

  1. Advanced data services over optical transport networks

    NASA Astrophysics Data System (ADS)

    Ong, Lyndon; Razdan, Rajender; Wang, Yalin

    2005-11-01

    Work on optical network control plane protocols has enabled faster and more efficient provisioning and management of carrier core optical networks, thereby reducing operational costs and capital expenditure. Many potential data applications for such capabilities, however, require Ethernet as the physical interface into the network, rather than SONET/SDH or OTN (Optical Transport Network) interfaces. Support of such services over an optical network becomes a multi-layer networking problem, wherein the client layer is packet based (e.g., Ethernet) and the server layer is optical (SONET/SDH or OTN). This paper discusses the enhancements that have been created in SONET/SDH and OTN networks (e.g., GFP, VCAT, LCAS) for the efficient transport of Ethernet and other data networking protocols, and the related extensions to control plane protocols that are necessary to allow for the support of multi-layer networking. Different control-plane models are being pursued in standards bodies such as ITU-T and IETF, and prototyping is being carried out and tested in the OIF. These various approaches are discussed in detail here, with focus placed on the prototyping work that has been done in the OIF, especially for the OIF 2005 Interoperability Demonstration.

  2. An online system for metabolic network analysis

    PubMed Central

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

    2014-01-01

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

  3. Recent Advances in Magnetoseismology Using Network Observations by Ground Magnetometers

    NASA Astrophysics Data System (ADS)

    Chi, P. J.; Russell, C. T.

    2011-12-01

    The rise of modern, synchronized networks of ground magnetometers in recent years has inspired and advanced research and development in magnetoseismology. Like the practice in other geophysical disciplines, magnetoseismology can infer the structure of the magnetosphere from the observations of normal-mode frequencies of the magnetic field. It can also time and locate impulsive events by measuring the signal arrival time at multiple ground stations. We highlight recent advances in using network observations by ground magnetometers for both types of magnetoseismic research. In the area of normal-mode magnetoseismology the increase in ground magnetometers has enabled ever more station pairs suitable for the gradient analysis. We demonstrate progress in automatic detection of field line resonance frequencies and the results that reveal longitudinal structure of the plasmasphere. As a relatively young research topic, travel-time magnetoseismology has shown its capability to time and locate sudden impulses and substorm onsets by using ground-based magnetometer observations. These initial successes in turn motivated detailed examination of MHD wave propagation in the magnetosphere. In the end we discuss how these magnetoseismic studies shed light on the regions in the world where future establishment of ground magnetometers is desirable.

  4. Advance Liquid Metal Reactor Discrete Dynamic Event Tree/Bayesian Network Analysis and Incident Management Guidelines (Risk Management for Sodium Fast Reactors)

    SciTech Connect

    Denman, Matthew R.; Groth, Katrina M.; Cardoni, Jeffrey N.; Wheeler, Timothy A.

    2015-04-01

    Accident management is an important component to maintaining risk at acceptable levels for all complex systems, such as nuclear power plants. With the introduction of self-correcting, or inherently safe, reactor designs the focus has shifted from management by operators to allowing the system's design to manage the accident. Inherently and passively safe designs are laudable, but nonetheless extreme boundary conditions can interfere with the design attributes which facilitate inherent safety, thus resulting in unanticipated and undesirable end states. This report examines an inherently safe and small sodium fast reactor experiencing a beyond design basis seismic event with the intend of exploring two issues : (1) can human intervention either improve or worsen the potential end states and (2) can a Bayesian Network be constructed to infer the state of the reactor to inform (1). ACKNOWLEDGEMENTS The authors would like to acknowledge the U.S. Department of Energy's Office of Nuclear Energy for funding this research through Work Package SR-14SN100303 under the Advanced Reactor Concepts program. The authors also acknowledge the PRA teams at Argonne National Laboratory, Oak Ridge National Laboratory, and Idaho National Laboratory for their continue d contributions to the advanced reactor PRA mission area.

  5. Advanced telerobotic control using neural networks

    NASA Technical Reports Server (NTRS)

    Pap, Robert M.; Atkins, Mark; Cox, Chadwick; Glover, Charles; Kissel, Ralph; Saeks, Richard

    1993-01-01

    Accurate Automation is designing and developing adaptive decentralized joint controllers using neural networks. We are then implementing these in hardware for the Marshall Space Flight Center PFMA as well as to be usable for the Remote Manipulator System (RMS) robot arm. Our design is being realized in hardware after completion of the software simulation. This is implemented using a Functional-Link neural network.

  6. Advanced medical video services through context-aware medical networks.

    PubMed

    Doukas, Charalampos N; Maglogiannis, Ilias; Pliakas, Thomas

    2007-01-01

    The aim of this paper is to present a framework for advanced medical video delivery services, through network and patient-state awareness. Under this scope a context-aware medical networking platform is described. The developed platform enables proper medical video data coding and transmission according to both a) network availability and/or quality and b) patient status, optimizing thus network performance and telediagnosis. An evaluation platform has been developed based on scalable H.264 coding of medical videos. Corresponding results of video transmission over a WiMax network have proved the effectiveness and efficiency of the platform providing proper video content delivery. PMID:18002643

  7. 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.

  8. Advanced information processing system: Input/output network management software

    NASA Technical Reports Server (NTRS)

    Nagle, Gail; Alger, Linda; Kemp, Alexander

    1988-01-01

    The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

  9. Advances in total scattering analysis

    SciTech Connect

    Proffen, Thomas E; Kim, Hyunjeong

    2008-01-01

    In recent years the analysis of the total scattering pattern has become an invaluable tool to study disordered crystalline and nanocrystalline materials. Traditional crystallographic structure determination is based on Bragg intensities and yields the long range average atomic structure. By including diffuse scattering into the analysis, the local and medium range atomic structure can be unravelled. Here we give an overview of recent experimental advances, using X-rays as well as neutron scattering as well as current trends in modelling of total scattering data.

  10. Networking Technologies Enable Advances in Earth Science

    NASA Technical Reports Server (NTRS)

    Johnson, Marjory; Freeman, Kenneth; Gilstrap, Raymond; Beck, Richard

    2004-01-01

    This paper describes an experiment to prototype a new way of conducting science by applying networking and distributed computing technologies to an Earth Science application. A combination of satellite, wireless, and terrestrial networking provided geologists at a remote field site with interactive access to supercomputer facilities at two NASA centers, thus enabling them to validate and calibrate remotely sensed geological data in near-real time. This represents a fundamental shift in the way that Earth scientists analyze remotely sensed data. In this paper we describe the experiment and the network infrastructure that enabled it, analyze the data flow during the experiment, and discuss the scientific impact of the results.

  11. Environmental Monitoring Networks Optimization Using Advanced Active Learning Algorithms

    NASA Astrophysics Data System (ADS)

    Kanevski, Mikhail; Volpi, Michele; Copa, Loris

    2010-05-01

    The problem of environmental monitoring networks optimization (MNO) belongs to one of the basic and fundamental tasks in spatio-temporal data collection, analysis, and modeling. There are several approaches to this problem, which can be considered as a design or redesign of monitoring network by applying some optimization criteria. The most developed and widespread methods are based on geostatistics (family of kriging models, conditional stochastic simulations). In geostatistics the variance is mainly used as an optimization criterion which has some advantages and drawbacks. In the present research we study an application of advanced techniques following from the statistical learning theory (SLT) - support vector machines (SVM) and the optimization of monitoring networks when dealing with a classification problem (data are discrete values/classes: hydrogeological units, soil types, pollution decision levels, etc.) is considered. SVM is a universal nonlinear modeling tool for classification problems in high dimensional spaces. The SVM solution is maximizing the decision boundary between classes and has a good generalization property for noisy data. The sparse solution of SVM is based on support vectors - data which contribute to the solution with nonzero weights. Fundamentally the MNO for classification problems can be considered as a task of selecting new measurement points which increase the quality of spatial classification and reduce the testing error (error on new independent measurements). In SLT this is a typical problem of active learning - a selection of the new unlabelled points which efficiently reduce the testing error. A classical approach (margin sampling) to active learning is to sample the points closest to the classification boundary. This solution is suboptimal when points (or generally the dataset) are redundant for the same class. In the present research we propose and study two new advanced methods of active learning adapted to the solution of

  12. SINET3: advanced optical and IP hybrid network

    NASA Astrophysics Data System (ADS)

    Urushidani, Shigeo

    2007-11-01

    This paper introduces the new Japanese academic backbone network called SINET3, which has been in full-scale operation since June 2007. SINET3 provides a wide variety of network services, such as multi-layer transfer, enriched VPN, enhanced QoS, and layer-1 bandwidth on demand (BoD) services to create an innovative and prolific science infrastructure for more than 700 universities and research institutions. The network applies an advanced hybrid network architecture composed of 75 layer-1 switches and 12 high-performance IP routers to accommodate such diversified services in a single network platform, and provides sufficient bandwidth using Japan's first STM256 (40 Gbps) lines. The network adopts lots of the latest networking technologies, such as next-generation SDH (VCAT/GFP/LCAS), GMPLS, advanced MPLS, and logical-router technologies, for high network convergence, flexible resource assignment, and high service availability. This paper covers the network services, network design, and networking technologies of SINET3.

  13. Optical protocols for advanced spacecraft networks

    NASA Technical Reports Server (NTRS)

    Bergman, Larry A.

    1991-01-01

    Most present day fiber optic networks are in fact extensions of copper wire networks. As a result, their speed is still limited by electronics even though optics is capable of running three orders of magnitude faster. Also, the fact that photons do not interact with one another (as electrons do) provides optical communication systems with some unique properties or new functionality that is not readily taken advantage of with conventional approaches. Some of the motivation for implementing network protocols in the optical domain, a few possible approaches including optical code-division multiple-access (CDMA), and how this class of networks can extend the technology life cycle of the Space Station Freedom (SSF) with increased performance and functionality are described.

  14. The Analysis of Social Networks

    PubMed Central

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

    2009-01-01

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

  15. 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.

  16. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 2: Fiber optic technology and long distance networks

    NASA Technical Reports Server (NTRS)

    1986-01-01

    The study projects until 2000 the evolution of long distance fiber optic networks in the U.S. Volume 1 is the Executive Summary. Volume 2 focuses on fiber optic components and systems that are directly related to the operation of long-haul networks. Optimistic, pessimistic and most likely scenarios of technology development are presented. The activities of national and regional companies implementing fiber long haul networks are also highlighted, along with an analysis of the market and regulatory forces affecting network evolution. Volume 3 presents advanced fiber optic network concept definitions. Inter-LATA traffic is quantified and forms the basis for the construction of 11-, 15-, 17-, and 23-node networks. Using the technology projections from Volume 2, a financial model identifies cost drivers and determines circuit mile costs between any two LATAs. A comparison of fiber optics with alternative transmission concludes the report.

  17. Recent advances in symmetric and network dynamics

    NASA Astrophysics Data System (ADS)

    Golubitsky, Martin; Stewart, Ian

    2015-09-01

    We summarize some of the main results discovered over the past three decades concerning symmetric dynamical systems and networks of dynamical systems, with a focus on pattern formation. In both of these contexts, extra constraints on the dynamical system are imposed, and the generic phenomena can change. The main areas discussed are time-periodic states, mode interactions, and non-compact symmetry groups such as the Euclidean group. We consider both dynamics and bifurcations. We summarize applications of these ideas to pattern formation in a variety of physical and biological systems, and explain how the methods were motivated by transferring to new contexts René Thom's general viewpoint, one version of which became known as "catastrophe theory." We emphasize the role of symmetry-breaking in the creation of patterns. Topics include equivariant Hopf bifurcation, which gives conditions for a periodic state to bifurcate from an equilibrium, and the H/K theorem, which classifies the pairs of setwise and pointwise symmetries of periodic states in equivariant dynamics. We discuss mode interactions, which organize multiple bifurcations into a single degenerate bifurcation, and systems with non-compact symmetry groups, where new technical issues arise. We transfer many of the ideas to the context of networks of coupled dynamical systems, and interpret synchrony and phase relations in network dynamics as a type of pattern, in which space is discretized into finitely many nodes, while time remains continuous. We also describe a variety of applications including animal locomotion, Couette-Taylor flow, flames, the Belousov-Zhabotinskii reaction, binocular rivalry, and a nonlinear filter based on anomalous growth rates for the amplitude of periodic oscillations in a feed-forward network.

  18. Recent advances in symmetric and network dynamics.

    PubMed

    Golubitsky, Martin; Stewart, Ian

    2015-09-01

    We summarize some of the main results discovered over the past three decades concerning symmetric dynamical systems and networks of dynamical systems, with a focus on pattern formation. In both of these contexts, extra constraints on the dynamical system are imposed, and the generic phenomena can change. The main areas discussed are time-periodic states, mode interactions, and non-compact symmetry groups such as the Euclidean group. We consider both dynamics and bifurcations. We summarize applications of these ideas to pattern formation in a variety of physical and biological systems, and explain how the methods were motivated by transferring to new contexts René Thom's general viewpoint, one version of which became known as "catastrophe theory." We emphasize the role of symmetry-breaking in the creation of patterns. Topics include equivariant Hopf bifurcation, which gives conditions for a periodic state to bifurcate from an equilibrium, and the H/K theorem, which classifies the pairs of setwise and pointwise symmetries of periodic states in equivariant dynamics. We discuss mode interactions, which organize multiple bifurcations into a single degenerate bifurcation, and systems with non-compact symmetry groups, where new technical issues arise. We transfer many of the ideas to the context of networks of coupled dynamical systems, and interpret synchrony and phase relations in network dynamics as a type of pattern, in which space is discretized into finitely many nodes, while time remains continuous. We also describe a variety of applications including animal locomotion, Couette-Taylor flow, flames, the Belousov-Zhabotinskii reaction, binocular rivalry, and a nonlinear filter based on anomalous growth rates for the amplitude of periodic oscillations in a feed-forward network. PMID:26428565

  19. Conceptualizing and Advancing Research Networking Systems.

    PubMed

    Schleyer, Titus; Butler, Brian S; Song, Mei; Spallek, Heiko

    2012-03-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers' need for comprehensive information and potential collaborators' desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user's primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems. PMID:24376309

  20. Conceptualizing and Advancing Research Networking Systems

    PubMed Central

    SCHLEYER, TITUS; BUTLER, BRIAN S.; SONG, MEI; SPALLEK, HEIKO

    2013-01-01

    Science in general, and biomedical research in particular, is becoming more collaborative. As a result, collaboration with the right individuals, teams, and institutions is increasingly crucial for scientific progress. We propose Research Networking Systems (RNS) as a new type of system designed to help scientists identify and choose collaborators, and suggest a corresponding research agenda. The research agenda covers four areas: foundations, presentation, architecture, and evaluation. Foundations includes project-, institution- and discipline-specific motivational factors; the role of social networks; and impression formation based on information beyond expertise and interests. Presentation addresses representing expertise in a comprehensive and up-to-date manner; the role of controlled vocabularies and folksonomies; the tension between seekers’ need for comprehensive information and potential collaborators’ desire to control how they are seen by others; and the need to support serendipitous discovery of collaborative opportunities. Architecture considers aggregation and synthesis of information from multiple sources, social system interoperability, and integration with the user’s primary work context. Lastly, evaluation focuses on assessment of collaboration decisions, measurement of user-specific costs and benefits, and how the large-scale impact of RNS could be evaluated with longitudinal and naturalistic methods. We hope that this article stimulates the human-computer interaction, computer-supported cooperative work, and related communities to pursue a broad and comprehensive agenda for developing research networking systems. PMID:24376309

  1. Live cumulative network meta-analysis: protocol for second-line treatments in advanced non-small-cell lung cancer with wild-type or unknown status for epidermal growth factor receptor

    PubMed Central

    Créquit, Perrine; Trinquart, Ludovic; Ravaud, Philippe

    2016-01-01

    Introduction Many second-line treatments for advanced non-small-cell lung cancer (NSCLC) have been assessed in randomised controlled trials, but which treatments work the best remains unclear. Novel treatments are being rapidly developed. We need a comprehensive up-to-date evidence synthesis of all these treatments. We present the protocol for a live cumulative network meta-analysis (NMA) to address this need. Methods and analysis We will consider trials of second-line treatments in patients with advanced NSCLC with wild-type or unknown epidermal growth factor receptor status. We will consider any single agent of cytotoxic chemotherapy, targeted therapy, combination of cytotoxic chemotherapy and targeted therapy and any combination of targeted therapies. The primary outcomes will be overall survival and progression-free survival. The live cumulative NMA will be initiated with a NMA and then iterations will be repeated at regular intervals to keep the NMA up-to-date over time. We have defined the update frequency as 4 months, based on an assessment of the pace of evidence production on this topic. Each iteration will consist of six methodological steps: adaptive search for treatments and trials, screening of reports and selection of trials, data extraction, assessment of risk of bias, update of the network of trials and synthesis, and dissemination. We will set up a research community in lung cancer, with different groups of contributors of different skills. We will distribute tasks through online crowdsourcing. This proof-of-concept study in second-line treatments of advanced NSCLC will allow one for assessing the feasibility of live cumulative NMA and opening the path for this new form of synthesis. Ethics and dissemination Ethical approval is not required because our study will not include confidential participant data and interventions. The description of all the steps and the results of this live cumulative NMA will be available online. Trial registration

  2. Automated sensor networks to advance ocean science

    NASA Astrophysics Data System (ADS)

    Schofield, O.; Orcutt, J. A.; Arrott, M.; Vernon, F. L.; Peach, C. L.; Meisinger, M.; Krueger, I.; Kleinert, J.; Chao, Y.; Chien, S.; Thompson, D. R.; Chave, A. D.; Balasuriya, A.

    2010-12-01

    The National Science Foundation has funded the Ocean Observatories Initiative (OOI), which over the next five years will deploy infrastructure to expand scientist’s ability to remotely study the ocean. The deployed infrastructure will be linked by a robust cyberinfrastructure (CI) that will integrate marine observatories into a coherent system-of-systems. OOI is committed to engaging the ocean sciences community during the construction pahse. For the CI, this is being enabled by using a “spiral design strategy” allowing for input throughout the construction phase. In Fall 2009, the OOI CI development team used an existing ocean observing network in the Mid-Atlantic Bight (MAB) to test OOI CI software. The objective of this CI test was to aggregate data from ships, autonomous underwater vehicles (AUVs), shore-based radars, and satellites and make it available to five different data-assimilating ocean forecast models. Scientists used these multi-model forecasts to automate future glider missions in order to demonstrate the feasibility of two-way interactivity between the sensor web and predictive models. The CI software coordinated and prioritized the shared resources that allowed for the semi-automated reconfiguration of assett-tasking, and thus enabled an autonomous execution of observation plans for the fixed and mobile observation platforms. Efforts were coordinated through a web portal that provided an access point for the observational data and model forecasts. Researchers could use the CI software in tandem with the web data portal to assess the performance of individual numerical model results, or multi-model ensembles, through real-time comparisons with satellite, shore-based radar, and in situ robotic measurements. The resulting sensor net will enable a new means to explore and study the world’s oceans by providing scientists a responsive network in the world’s oceans that can be accessed via any wireless network.

  3. The ADVANCE network: accelerating data value across a national community health center network

    PubMed Central

    DeVoe, Jennifer E; Gold, Rachel; Cottrell, Erika; Bauer, Vance; Brickman, Andrew; Puro, Jon; Nelson, Christine; Mayer, Kenneth H; Sears, Abigail; Burdick, Tim; Merrell, Jonathan; Matthews, Paul; Fields, Scott

    2014-01-01

    The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network (CDRN) is led by the OCHIN Community Health Information Network in partnership with Health Choice Network and Fenway Health. The ADVANCE CDRN will ‘horizontally’ integrate outpatient electronic health record data for over one million federally qualified health center patients, and ‘vertically’ integrate hospital, health plan, and community data for these patients, often under-represented in research studies. Patient investigators, community investigators, and academic investigators with diverse expertise will work together to meet project goals related to data integration, patient engagement and recruitment, and the development of streamlined regulatory policies. By enhancing the data and research infrastructure of participating organizations, the ADVANCE CDRN will serve as a ‘community laboratory’ for including disadvantaged and vulnerable patients in patient-centered outcomes research that is aligned with the priorities of patients, clinics, and communities in our network. PMID:24821740

  4. Characteristics and Impact of the Further Mathematics Knowledge Networks: Analysis of an English Professional Development Initiative on the Teaching of Advanced Mathematics

    ERIC Educational Resources Information Center

    Ruthven, Kenneth

    2014-01-01

    Reports from 13 Further Mathematics Knowledge Networks supported by the National Centre for Excellence in the Teaching of Mathematics [NCETM] are analysed. After summarizing basic characteristics of the networks regarding leadership, composition and pattern of activity, each of the following aspects is examined in greater depth: Developmental aims…

  5. Advanced Energy Storage Management in Distribution Network

    SciTech Connect

    Liu, Guodong; Ceylan, Oguzhan; Xiao, Bailu; Starke, Michael R; Ollis, T Ben; King, Daniel J; Irminger, Philip; Tomsovic, Kevin

    2016-01-01

    With increasing penetration of distributed generation (DG) in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative mixed integer quadratic constrained quadratic programming model to optimize the operation of a three phase unbalanced distribution system with high penetration of Photovoltaic (PV) panels, DG and energy storage (ES) is developed. The proposed model minimizes not only the operating cost, including fuel cost and purchasing cost, but also voltage deviations and power loss. The optimization model is based on the linearized sensitivity coefficients between state variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DG and ES). To avoid slow convergence when close to the optimum, a golden search method is introduced to control the step size and accelerate the convergence. The proposed algorithm is demonstrated on modified IEEE 13 nodes test feeders with multiple PV panels, DG and ES. Numerical simulation results validate the proposed algorithm. Various scenarios of system configuration are studied and some critical findings are concluded.

  6. Localization of gravitational wave sources with networks of advanced detectors

    SciTech Connect

    Klimenko, S.; Mitselmakher, G.; Pankow, C.; Vedovato, G.; Drago, M.; Prodi, G.; Mazzolo, G.; Salemi, F.; Re, V.; Yakushin, I.

    2011-05-15

    Coincident observations with gravitational wave (GW) detectors and other astronomical instruments are among the main objectives of the experiments with the network of LIGO, Virgo, and GEO detectors. They will become a necessary part of the future GW astronomy as the next generation of advanced detectors comes online. The success of such joint observations directly depends on the source localization capabilities of the GW detectors. In this paper we present studies of the sky localization of transient GW sources with the future advanced detector networks and describe their fundamental properties. By reconstructing sky coordinates of ad hoc signals injected into simulated detector noise, we study the accuracy of the source localization and its dependence on the strength of injected signals, waveforms, and network configurations.

  7. Neural network ultrasound image analysis

    NASA Astrophysics Data System (ADS)

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

    1993-09-01

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

  8. Vector Network Analysis

    Energy Science and Technology Software Center (ESTSC)

    1997-10-20

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

  9. The space physics analysis network

    NASA Astrophysics Data System (ADS)

    Green, James L.

    1988-04-01

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

  10. Data communication requirements for the advanced NAS network

    NASA Technical Reports Server (NTRS)

    Levin, Eugene; Eaton, C. K.; Young, Bruce

    1986-01-01

    The goal of the Numerical Aerodynamic Simulation (NAS) Program is to provide a powerful computational environment for advanced research and development in aeronautics and related disciplines. The present NAS system consists of a Cray 2 supercomputer connected by a data network to a large mass storage system, to sophisticated local graphics workstations, and by remote communications to researchers throughout the United States. The program plan is to continue acquiring the most powerful supercomputers as they become available. In the 1987/1988 time period it is anticipated that a computer with 4 times the processing speed of a Cray 2 will be obtained and by 1990 an additional supercomputer with 16 times the speed of the Cray 2. The implications of this 20-fold increase in processing power on the data communications requirements are described. The analysis was based on models of the projected workload and system architecture. The results are presented together with the estimates of their sensitivity to assumptions inherent in the models.

  11. Regression analysis of networked data

    PubMed Central

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

    2016-01-01

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

  12. Gigabit Satellite Network for NASA's Advanced Communication Technology Satellite (ACTS)

    NASA Technical Reports Server (NTRS)

    Hoder, Douglas; Bergamo, Marcos

    1996-01-01

    The advanced communication technology satellite (ACTS) gigabit satellite network provides long-haul point-to-point and point-to-multipoint full-duplex SONET services over NASA's ACTS. at rates up to 622 Mbit/s (SONET OC-12), with signal quality comparable to that obtained with terrestrial fiber networks. Data multiplexing over the satellite is accomplished using time-division multiple access (TDMA) techniques coordinated with the switching and beam hopping facilities provided by ACTS. Transmissions through the satellite are protected with Reed-Solomon encoding. providing virtually error-free transmission under most weather conditions. Unique to the system are a TDMA frame structure and satellite synchronization mechanism that allow: (a) very efficient utilization of the satellite capacity: (b) over-the-satellite dosed-loop synchronization of the network in configurations with up to 64 ground stations: and (c) ground station initial acquisition without collisions with existing signalling or data traffic. The user interfaces are compatible with SONET standards, performing the function of conventional SONET multiplexers and. as such. can be: readily integrated with standard SONET fiber-based terrestrial networks. Management of the network is based upon the simple network management protocol (SNMP). and includes an over-the-satellite signalling network and backup terrestrial internet (IP-based) connectivity. A description of the ground stations is also included.

  13. Advances, experiences, and prospects of the International Soil Moisture Network

    NASA Astrophysics Data System (ADS)

    Dorigo, W.; van Oevelen, P. J.; Drusch, M.; Wagner, W.; Scipal, K.; Mecklenburg, S.

    2012-12-01

    In 2009, the International Soil Moisture Network (ISMN; http:www.ipf.tuwien.ac.at) was initiated as a platform to support calibration and validation of soil moisture products from remote sensing and land surface models, and to advance studies on the behavior of soil moisture over space and time. This international initiative is fruit of continuing coordinative efforts of the Global Energy and Water Cycle Experiment (GEWEX) in cooperation with the Group of Earth Observation (GEO) and the Committee on Earth Observation Satellites (CEOS). The decisive financial incentive was given by the European Space Agency (ESA) who considered the establishment of the network critical for optimizing the soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. The ISMN collects and harmonizes ground-based soil moisture data sets from a large variety of individually operating networks and makes them available through a centralized data portal. Meanwhile, almost 6000 soil moisture data sets from over 1300 sites, distributed among 34 networks worldwide, are contained in the database. The steadily increasing number of organizations voluntarily contributing to the ISMN, and the rapidly increasing number of studies based on the network show that the portal has been successful in reaching its primary goal to promote easy data accessibility to a wide variety of users. Recently, several updates of the system were performed to keep up with the increasing data amount and traffic, and to meet the requirements of many advanced users. Many datasets from operational networks (e.g., SCAN, the US Climate Reference Network, COSMOS, and ARM) are now assimilated and processed in the ISMN on a fully automated basis in near-real time. In addition, a new enhanced quality control system is currently being implemented. This presentation gives an overview of these recent developments, presents some examples of important scientific results based on the ISMN, and sketches an outlook for

  14. Wireless Sensor Network for Advanced Energy Management Solutions

    SciTech Connect

    Peter J. Theisen; Bin Lu, Charles J. Luebke

    2009-09-23

    Eaton has developed an advanced energy management solution that has been deployed to several Industries of the Future (IoF) sites. This demonstrated energy savings and reduced unscheduled downtime through an improved means for performing predictive diagnostics and energy efficiency estimation. Eaton has developed a suite of online, continuous, and inferential algorithms that utilize motor current signature analysis (MCSA) and motor power signature analysis (MPSA) techniques to detect and predict the health condition and energy usage condition of motors and their connect loads. Eaton has also developed a hardware and software platform that provided a means to develop and test these advanced algorithms in the field. Results from lab validation and field trials have demonstrated that the developed advanced algorithms are able to detect motor and load inefficiency and performance degradation. Eaton investigated the performance of Wireless Sensor Networks (WSN) within various industrial facilities to understand concerns about topology and environmental conditions that have precluded broad adoption by the industry to date. A Wireless Link Assessment System (WLAS), was used to validate wireless performance under a variety of conditions. Results demonstrated that wireless networks can provide adequate performance in most facilities when properly specified and deployed. Customers from various IoF expressed interest in applying wireless more broadly for selected applications, but continue to prefer utilizing existing, wired field bus networks for most sensor based applications that will tie into their existing Computerized Motor Maintenance Systems (CMMS). As a result, wireless technology was de-emphasized within the project, and a greater focus placed on energy efficiency/predictive diagnostics. Commercially available wireless networks were only utilized in field test sites to facilitate collection of motor wellness information, and no wireless sensor network products were

  15. ADVANCED POWER SYSTEMS ANALYSIS TOOLS

    SciTech Connect

    Robert R. Jensen; Steven A. Benson; Jason D. Laumb

    2001-08-31

    The use of Energy and Environmental Research Center (EERC) modeling tools and improved analytical methods has provided key information in optimizing advanced power system design and operating conditions for efficiency, producing minimal air pollutant emissions and utilizing a wide range of fossil fuel properties. This project was divided into four tasks: the demonstration of the ash transformation model, upgrading spreadsheet tools, enhancements to analytical capabilities using the scanning electron microscopy (SEM), and improvements to the slag viscosity model. The ash transformation model, Atran, was used to predict the size and composition of ash particles, which has a major impact on the fate of the combustion system. To optimize Atran key factors such as mineral fragmentation and coalescence, the heterogeneous and homogeneous interaction of the organically associated elements must be considered as they are applied to the operating conditions. The resulting model's ash composition compares favorably to measured results. Enhancements to existing EERC spreadsheet application included upgrading interactive spreadsheets to calculate the thermodynamic properties for fuels, reactants, products, and steam with Newton Raphson algorithms to perform calculations on mass, energy, and elemental balances, isentropic expansion of steam, and gasifier equilibrium conditions. Derivative calculations can be performed to estimate fuel heating values, adiabatic flame temperatures, emission factors, comparative fuel costs, and per-unit carbon taxes from fuel analyses. Using state-of-the-art computer-controlled scanning electron microscopes and associated microanalysis systems, a method to determine viscosity using the incorporation of grey-scale binning acquired by the SEM image was developed. The image analysis capabilities of a backscattered electron image can be subdivided into various grey-scale ranges that can be analyzed separately. Since the grey scale's intensity is

  16. Advanced Technology Lifecycle Analysis System (ATLAS)

    NASA Technical Reports Server (NTRS)

    O'Neil, Daniel A.; Mankins, John C.

    2004-01-01

    Developing credible mass and cost estimates for space exploration and development architectures require multidisciplinary analysis based on physics calculations, and parametric estimates derived from historical systems. Within the National Aeronautics and Space Administration (NASA), concurrent engineering environment (CEE) activities integrate discipline oriented analysis tools through a computer network and accumulate the results of a multidisciplinary analysis team via a centralized database or spreadsheet Each minute of a design and analysis study within a concurrent engineering environment is expensive due the size of the team and supporting equipment The Advanced Technology Lifecycle Analysis System (ATLAS) reduces the cost of architecture analysis by capturing the knowledge of discipline experts into system oriented spreadsheet models. A framework with a user interface presents a library of system models to an architecture analyst. The analyst selects models of launchers, in-space transportation systems, and excursion vehicles, as well as space and surface infrastructure such as propellant depots, habitats, and solar power satellites. After assembling the architecture from the selected models, the analyst can create a campaign comprised of missions spanning several years. The ATLAS controller passes analyst specified parameters to the models and data among the models. An integrator workbook calls a history based parametric analysis cost model to determine the costs. Also, the integrator estimates the flight rates, launched masses, and architecture benefits over the years of the campaign. An accumulator workbook presents the analytical results in a series of bar graphs. In no way does ATLAS compete with a CEE; instead, ATLAS complements a CEE by ensuring that the time of the experts is well spent Using ATLAS, an architecture analyst can perform technology sensitivity analysis, study many scenarios, and see the impact of design decisions. When the analyst is

  17. 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…

  18. 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.

  19. Advanced Communication and Networking Technologies for Mars Exploration

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul; Hayden, Jeff; Agre, Jonathan R.; Clare, Loren P.; Yan, Tsun-Yee

    2001-01-01

    Next-generation Mars communications networks will provide communications and navigation services to a wide variety of Mars science vehicles including: spacecraft that are arriving at Mars, spacecraft that are entering and descending in the Mars atmosphere, scientific orbiter spacecraft, spacecraft that return Mars samples to Earth, landers, rovers, aerobots, airplanes, and sensing pods. In the current architecture plans, the communication services will be provided using capabilities deployed on the science vehicles as well as dedicated communication satellites that will together make up the Mars network. This network will evolve as additional vehicles arrive, depart or end their useful missions. Cost savings and increased reliability will result from the ability to share communication services between missions. This paper discusses the basic architecture that is needed to support the Mars Communications Network part of NASA's Space Science Enterprise (SSE) communications architecture. The network may use various networking technologies such as those employed in the terrestrial Internet, as well as special purpose deep-space protocols to move data and commands autonomously between vehicles, at disparate Mars vicinity sites (on the surface or in near-Mars space) and between Mars vehicles and earthbound users. The architecture of the spacecraft on-board local communications is being reconsidered in light of these new networking requirements. The trend towards increasingly autonomous operation of the spacecraft is aimed at reducing the dependence on resource scheduling provided by Earth-based operators and increasing system fault tolerance. However, these benefits will result in increased communication and software development requirements. As a result, the envisioned Mars communications infrastructure requires both hardware and protocol technology advancements. This paper will describe a number of the critical technology needs and some of the ongoing research

  20. Design Criteria For Networked Image Analysis System

    NASA Astrophysics Data System (ADS)

    Reader, Cliff; Nitteberg, Alan

    1982-01-01

    Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.

  1. Advanced materials: Information and analysis needs

    SciTech Connect

    Curlee, T.R.; Das, S.; Lee, R.; Trumble, D.

    1990-09-01

    This report presents the findings of a study to identify the types of information and analysis that are needed for advanced materials. The project was sponsored by the US Bureau of Mines (BOM). It includes a conceptual description of information needs for advanced materials and the development and implementation of a questionnaire on the same subject. This report identifies twelve fundamental differences between advanced and traditional materials and discusses the implications of these differences for data and analysis needs. Advanced and traditional materials differ significantly in terms of physical and chemical properties. Advanced material properties can be customized more easily. The production of advanced materials may differ from traditional materials in terms of inputs, the importance of by-products, the importance of different processing steps (especially fabrication), and scale economies. The potential for change in advanced materials characteristics and markets is greater and is derived from the marriage of radically different materials and processes. In addition to the conceptual study, a questionnaire was developed and implemented to assess the opinions of people who are likely users of BOM information on advanced materials. The results of the questionnaire, which was sent to about 1000 people, generally confirm the propositions set forth in the conceptual part of the study. The results also provide data on the categories of advanced materials and the types of information that are of greatest interest to potential users. 32 refs., 1 fig., 12 tabs.

  2. Processors, Pipelines, and Protocols for Advanced Modeling Networks

    NASA Technical Reports Server (NTRS)

    Coughlan, Joseph; Komar, George (Technical Monitor)

    2001-01-01

    Predictive capabilities arise from our understanding of natural processes and our ability to construct models that accurately reproduce these processes. Although our modeling state-of-the-art is primarily limited by existing computational capabilities, other technical areas will soon present obstacles to the development and deployment of future predictive capabilities. Advancement of our modeling capabilities will require not only faster processors, but new processing algorithms, high-speed data pipelines, and a common software engineering framework that allows networking of diverse models that represent the many components of Earth's climate and weather system. Development and integration of these new capabilities will pose serious challenges to the Information Systems (IS) technology community. Designers of future IS infrastructures must deal with issues that include performance, reliability, interoperability, portability of data and software, and ultimately, the full integration of various ES model systems into a unified ES modeling network.

  3. ACTS TDMA network control. [Advanced Communication Technology Satellite

    NASA Technical Reports Server (NTRS)

    Inukai, T.; Campanella, S. J.

    1984-01-01

    This paper presents basic network control concepts for the Advanced Communications Technology Satellite (ACTS) System. Two experimental systems, called the low-burst-rate and high-burst-rate systems, along with ACTS ground system features, are described. The network control issues addressed include frame structures, acquisition and synchronization procedures, coordinated station burst-time plan and satellite-time plan changes, on-board clock control based on ground drift measurements, rain fade control by means of adaptive forward-error-correction (FEC) coding and transmit power augmentation, and reassignment of channel capacities on demand. The NASA ground system, which includes a primary station, diversity station, and master control station, is also described.

  4. Development of precision measurement network of experimental advanced superconducting tokamak

    NASA Astrophysics Data System (ADS)

    Yu, Liandong; Zhao, Huining; Zhang, Wei; Li, Weishi; Deng, Huaxia; Song, Yuntao; Gu, Yongqi

    2014-12-01

    In order to obtain accurate position of the inner key components in the experimental advanced superconducting tokamak (EAST), a combined optical measurement method which is comprised of a laser tracker (LT) and articulated coordinate measuring machine (CMM) has been brought forward. LT, which is an optical measurement instrument and has a large measurement range and high accuracy, is employed for establishing the precision measurement network of EAST, and the articulated CMM is also employed for measuring the inner key components of EAST. The measurement uncertainty analyzed by the Unified Spatial Metrology Network (USMN) is 0.20 mm at a confidence probability of 95.44%. The proposed technology is appropriate for the inspection of the reconstruction of the EAST.

  5. Advanced Mobility Handover for Mobile IPv6 Based Wireless Networks

    PubMed Central

    Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

    2014-01-01

    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches. PMID:25614890

  6. Advanced mobility handover for mobile IPv6 based wireless networks.

    PubMed

    Safa Sadiq, Ali; Fisal, Norsheila Binti; Ghafoor, Kayhan Zrar; Lloret, Jaime

    2014-01-01

    We propose an Advanced Mobility Handover scheme (AMH) in this paper for seamless mobility in MIPv6-based wireless networks. In the proposed scheme, the mobile node utilizes a unique home IPv6 address developed to maintain communication with other corresponding nodes without a care-of-address during the roaming process. The IPv6 address for each MN during the first round of AMH process is uniquely identified by HA using the developed MN-ID field as a global permanent, which is identifying uniquely the IPv6 address of MN. Moreover, a temporary MN-ID is generated by access point each time an MN is associated with a particular AP and temporarily saved in a developed table inside the AP. When employing the AMH scheme, the handover process in the network layer is performed prior to its default time. That is, the mobility handover process in the network layer is tackled by a trigger developed AMH message to the next access point. Thus, a mobile node keeps communicating with the current access point while the network layer handover is executed by the next access point. The mathematical analyses and simulation results show that the proposed scheme performs better as compared with the existing approaches. PMID:25614890

  7. Scaling of data communications for an advanced supercomputer network

    NASA Technical Reports Server (NTRS)

    Levin, E.; Eaton, C. K.; Young, Bruce

    1986-01-01

    The goal of NASA's Numerical Aerodynamic Simulation (NAS) Program is to provide a powerful computational environment for advanced research and development in aeronautics and related disciplines. The present NAS system consists of a Cray 2 supercomputer connected by a data network to a large mass storage system, to sophisticated local graphics workstations and by remote communication to researchers throughout the United States. The program plan is to continue acquiring the most powerful supercomputers as they become available. The implications of a projected 20-fold increase in processing power on the data communications requirements are described.

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

    PubMed

    Rücker, Gerta; Schwarzer, Guido

    2016-03-01

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

  9. Possible contribution of advanced statistical methods (artificial neural networks and linear discriminant analysis) in recognition of patients with suspected atrophic body gastritis

    PubMed Central

    Lahner, Edith; Grossi, Enzo; Intraligi, Marco; Buscema, Massimo; Corleto, Vito D; Fave, Gianfranco Delle; Annibale, Bruno

    2005-01-01

    AIM: To investigating whether ANNs and LDA could recognize patients with ABG in a database, containing only clinical and biochemical variables, of a pool of patients with and without ABG, by selecting the most predictive variables and by reducing input data to the minimum. METHODS: Data was collected from 350 consecutive outpatients (263 with ABG, 87 with non-atrophic gastritis and/or celiac disease [controls]). Structured questionnaires with 22 items (anagraphic, anamnestic, clinical, and biochemical data) were filled out for each patient. All patients underwent gastroscopy with biopsies. ANNs and LDA were applied to recognize patients with ABG. Experiment 1: random selection on 37 variables, experiment 2: optimization process on 30 variables, experiment 3: input data reduction on 8 variables, experiment 4: use of only clinical input data on 5 variables, and experiment 5: use of only serological variables. RESULTS: In experiment 1, overall accuracies of ANNs and LDA were 96.6% and 94.6%, respectively, for predicting patients with ABG. In experiment 2, ANNs and LDA reached an overall accuracy of 98.8% and 96.8%, respectively. In experiment 3, overall accuracy of ANNs was 98.4%. In experiment 4, overall accuracies of ANNs and LDA were, respectively, 91.3% and 88.6%. In experiment 5, overall accuracies of ANNs and LDA were, respectively, 97.7% and 94.5%. CONCLUSION: This preliminary study suggests that advanced statistical methods, not only ANNs, but also LDA, may contribute to better address bioptic sampling during gastroscopy in a subset of patients in whom ABG may be suspected on the basis of aspecific gastrointestinal symptoms or non-digestive disorders. PMID:16270400

  10. Network worlds : from link analysis to virtual places.

    SciTech Connect

    Joslyn, C.

    2002-01-01

    Significant progress is being made in knowledge systems through recent advances in the science of very large networks. Attention is now turning in many quarters to the potential impact on counter-terrorism methods. After reviewing some of these advances, we will discuss the difference between such 'network analytic' approaches, which focus on large, homogeneous graph strucures, and what we are calling 'link analytic' approaches, which focus on somewhat smaller graphs with heterogeneous link types. We use this venue to begin the process of rigorously defining link analysis methods, especially the concept of chaining of views of multidimensional databases. We conclude with some speculation on potential connections to virtual world architectures.

  11. Analysis of complex systems using neural networks

    SciTech Connect

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

    1992-01-01

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

  12. Analysis of complex systems using neural networks

    SciTech Connect

    Uhrig, R.E. |

    1992-12-31

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

  13. Advanced analysis methods in particle physics

    SciTech Connect

    Bhat, Pushpalatha C.; /Fermilab

    2010-10-01

    Each generation of high energy physics experiments is grander in scale than the previous - more powerful, more complex and more demanding in terms of data handling and analysis. The spectacular performance of the Tevatron and the beginning of operations of the Large Hadron Collider, have placed us at the threshold of a new era in particle physics. The discovery of the Higgs boson or another agent of electroweak symmetry breaking and evidence of new physics may be just around the corner. The greatest challenge in these pursuits is to extract the extremely rare signals, if any, from huge backgrounds arising from known physics processes. The use of advanced analysis techniques is crucial in achieving this goal. In this review, I discuss the concepts of optimal analysis, some important advanced analysis methods and a few examples. The judicious use of these advanced methods should enable new discoveries and produce results with better precision, robustness and clarity.

  14. Advanced Power System Analysis Capabilities

    NASA Technical Reports Server (NTRS)

    1997-01-01

    As a continuing effort to assist in the design and characterization of space power systems, the NASA Lewis Research Center's Power and Propulsion Office developed a powerful computerized analysis tool called System Power Analysis for Capability Evaluation (SPACE). This year, SPACE was used extensively in analyzing detailed operational timelines for the International Space Station (ISS) program. SPACE was developed to analyze the performance of space-based photovoltaic power systems such as that being developed for the ISS. It is a highly integrated tool that combines numerous factors in a single analysis, providing a comprehensive assessment of the power system's capability. Factors particularly critical to the ISS include the orientation of the solar arrays toward the Sun and the shadowing of the arrays by other portions of the station.

  15. 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.

  16. Advanced optical network architecture for integrated digital avionics

    NASA Astrophysics Data System (ADS)

    Morgan, D. Reed

    1996-12-01

    For the first time in the history of avionics, the network designer now has a choice in selecting the media that interconnects the sources and sinks of digital data on aircraft. Electrical designs are already giving way to photonics in application areas where the data rate times distance product is large or where special design requirements such as low weight or EMI considerations are critical. Future digital avionic architectures will increasingly favor the use of photonic interconnects as network data rates of one gigabit/second and higher are needed to support real-time operation of high-speed integrated digital processing. As the cost of optical network building blocks is reduced and as temperature-rugged laser sources are matured, metal interconnects will be forced to retreat to applications spanning shorter and shorter distances. Although the trend is already underway, the widespread use of digital optics will first occur at the system level, where gigabit/second, real-time interconnects between sensors, processors, mass memories and displays separated by a least of few meters will be required. The application of photonic interconnects for inter-printed wiring board signalling across the backplane will eventually find application for gigabit/second applications since signal degradation over copper traces occurs before one gigabit/second and 0.5 meters are reached. For the foreseeable future however, metal interconnects will continue to be used to interconnect devices on printed wiring boards since 5 gigabit/second signals can be sent over metal up to around 15 centimeters. Current-day applications of optical interconnects at the system level are described and a projection of how advanced optical interconnect technology will be driven by the use of high speed integrated digital processing on future aircraft is presented. The recommended advanced network for application in the 2010 time frame is a fiber-based system with a signalling speed of around 2

  17. Innovative Networking Concepts Tested on the Advanced Communications Technology Satellite

    NASA Technical Reports Server (NTRS)

    Friedman, Daniel; Gupta, Sonjai; Zhang, Chuanguo; Ephremides, Anthony

    1996-01-01

    This paper describes a program of experiments conducted over the advanced communications technology satellite (ACTS) and the associated TI-VSAT (very small aperture terminal). The experiments were motivated by the commercial potential of low-cost receive only satellite terminals that can operate in a hybrid network environment, and by the desire to demonstrate frame relay technology over satellite networks. The first experiment tested highly adaptive methods of satellite bandwidth allocation in an integrated voice-data service environment. The second involved comparison of forward error correction (FEC) and automatic repeat request (ARQ) methods of error control for satellite communication with emphasis on the advantage that a hybrid architecture provides, especially in the case of multicasts. Finally, the third experiment demonstrated hybrid access to databases and compared the performance of internetworking protocols for interconnecting local area networks (LANs) via satellite. A custom unit termed frame relay access switch (FRACS) was developed by COMSAT Laboratories for these experiments; the preparation and conduct of these experiments involved a total of 20 people from the University of Maryland, the University of Colorado and COMSAT Laboratories, from late 1992 until 1995.

  18. Advanced Signal Analysis for Forensic Applications of Ground Penetrating Radar

    SciTech Connect

    Steven Koppenjan; Matthew Streeton; Hua Lee; Michael Lee; Sashi Ono

    2004-06-01

    Ground penetrating radar (GPR) systems have traditionally been used to image subsurface objects. The main focus of this paper is to evaluate an advanced signal analysis technique. Instead of compiling spatial data for the analysis, this technique conducts object recognition procedures based on spectral statistics. The identification feature of an object type is formed from the training vectors by a singular-value decomposition procedure. To illustrate its capability, this procedure is applied to experimental data and compared to the performance of the neural-network approach.

  19. 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.

  20. Introduction to Network Analysis in Systems Biology

    PubMed Central

    Ma’ayan, Avi

    2011-01-01

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

  1. Investigating Patterns of Interaction in Networked Learning and Computer-Supported Collaborative Learning: A Role for Social Network Analysis

    ERIC Educational Resources Information Center

    de Laat, Maarten; Lally, Vic; Lipponen, Lasse; Simons, Robert-Jan

    2007-01-01

    The focus of this study is to explore the advances that Social Network Analysis (SNA) can bring, in combination with other methods, when studying Networked Learning/Computer-Supported Collaborative Learning (NL/CSCL). We present a general overview of how SNA is applied in NL/CSCL research; we then go on to illustrate how this research method can…

  2. 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.

  3. 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.

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

    PubMed

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

    2016-04-22

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

  5. Advanced Placement: Model Policy Components. Policy Analysis

    ERIC Educational Resources Information Center

    Zinth, Jennifer

    2016-01-01

    Advanced Placement (AP), launched in 1955 by the College Board as a program to offer gifted high school students the opportunity to complete entry-level college coursework, has since expanded to encourage a broader array of students to tackle challenging content. This Education Commission of the State's Policy Analysis identifies key components of…

  6. Proceedings of the Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications

    NASA Technical Reports Server (NTRS)

    Paul, Lori (Editor)

    1991-01-01

    The Workshop on Advanced Network and Technology Concepts for Mobile, Micro, and Personal Communications was held at NASA's JPL Laboratory on 30-31 May 1991. It provided a forum for reviewing the development of advanced network and technology concepts for turn-of-the-century telecommunications. The workshop was organized into three main categories: (1) Satellite-Based Networks (L-band, C-band, Ku-band, and Ka-band); (2) Terrestrial-Based Networks (cellular, CT2, PCN, GSM, and other networks); and (3) Hybrid Satellite/Terrestrial Networks. The proceedings contain presentation papers from each of the above categories.

  7. The Network Protocol Analysis Technique in Snort

    NASA Astrophysics Data System (ADS)

    Wu, Qing-Xiu

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

  8. Analysis and implementation of optoelectronic network routers

    NASA Astrophysics Data System (ADS)

    Raksapatcharawong, Mongkol

    1999-11-01

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

  9. 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.

  10. Ecological network analysis for a virtual water network.

    PubMed

    Fang, Delin; Chen, Bin

    2015-06-01

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

  11. Dynamical robustness analysis of weighted complex networks

    NASA Astrophysics Data System (ADS)

    He, Zhiwei; Liu, Shuai; Zhan, Meng

    2013-09-01

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

  12. Interim Service ISDN Satellite (ISIS) network model for advanced satellite designs and experiments

    NASA Technical Reports Server (NTRS)

    Pepin, Gerard R.; Hager, E. Paul

    1991-01-01

    The Interim Service Integrated Services Digital Network (ISDN) Satellite (ISIS) Network Model for Advanced Satellite Designs and Experiments describes a model suitable for discrete event simulations. A top-down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ISDN modeling abstractions are added to permit the determination and performance for the NASA Satellite Communications Research (SCAR) Program.

  13. Recent advances in morphological cell image analysis.

    PubMed

    Chen, Shengyong; Zhao, Mingzhu; Wu, Guang; Yao, Chunyan; Zhang, Jianwei

    2012-01-01

    This paper summarizes the recent advances in image processing methods for morphological cell analysis. The topic of morphological analysis has received much attention with the increasing demands in both bioinformatics and biomedical applications. Among many factors that affect the diagnosis of a disease, morphological cell analysis and statistics have made great contributions to results and effects for a doctor. Morphological cell analysis finds the cellar shape, cellar regularity, classification, statistics, diagnosis, and so forth. In the last 20 years, about 1000 publications have reported the use of morphological cell analysis in biomedical research. Relevant solutions encompass a rather wide application area, such as cell clumps segmentation, morphological characteristics extraction, 3D reconstruction, abnormal cells identification, and statistical analysis. These reports are summarized in this paper to enable easy referral to suitable methods for practical solutions. Representative contributions and future research trends are also addressed. PMID:22272215

  14. Lightning Radio Source Retrieval Using Advanced Lightning Direction Finder (ALDF) Networks

    NASA Technical Reports Server (NTRS)

    Koshak, William J.; Blakeslee, Richard J.; Bailey, J. C.

    1998-01-01

    A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing and arrival time of lightning radio emissions. Solutions for the plane (i.e., no Earth curvature) are provided that implement all of tile measurements mentioned above. Tests of the retrieval method are provided using computer-simulated data sets. We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. In the absence of measurement errors, quadratic root degeneracy (no source location ambiguity) is shown to exist exactly on the outer sensor baselines for arbitrary non-collinear network geometries. The accuracy of the quadratic planar method is tested with computer generated data sets. The results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 deg. We also note some of the advantages and disadvantages of these methods over the nonlinear method of chi(sup 2) minimization employed by the National Lightning Detection Network (NLDN) and discussed in Cummins et al.(1993, 1995, 1998).

  15. Recent advances on distributed filtering for stochastic systems over sensor networks

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Wang, Zidong; Shen, Bo

    2014-05-01

    Sensor networks comprising of tiny, power-constrained nodes with sensing, computation, and wireless communication capabilities are gaining popularity due to their potential application in a wide variety of environments like monitoring of environmental attributes and various military and civilian applications. Considering the limited power and communication resources of the sensor nodes, the strategy of the distributed information processing is widely exploited. Therefore, it would be interesting to examine how the topology, network-induced phenomena, and power constraints influence the distributed filtering performance and to obtain some suitable schemes in order to solve the addressed distributed filter design problem. In this paper, we aim to survey some recent advances on the distributed filtering and distributed state estimation problems over the sensor networks with various performance requirements and/or randomly occurring network-induced phenomena. First, some practical filter structures are addressed in detail. Then, the developments of the distributed Kalman filtering, distributed state estimation based on the stability or mean-square error analysis, and distributed ? filtering are systematically reviewed. In addition, latest results on the distributed filtering or state estimation over sensor networks are discussed in great detail and some challenges are highlighted. Finally, some concluding remarks are given and some possible future research directions are pointed out.

  16. Advances in European drought research efforts and related research networks

    NASA Astrophysics Data System (ADS)

    Tallaksen, Lena; van Lanen, Henny

    2010-05-01

    catchment structure (i.e. presence of stores) in drought development is still limited. Climate change projections for Europe further indicate that drought is likely to become more frequent and more severe due to warmer northern winters and a warmer and dryer Mediterranean region. This presentation reviews current knowledge on the main climate drivers of drought in Europe, important land-surface feedback processes, drought propagation (meteorological to hydrological droughts), major historical events, spatial and temporal characteristics of drought, and methodologies for monitoring and forecasting. Recent and ongoing European drought research projects and networks are presented, focusing on their role in advancing our knowledge on drought within different research areas and hydroclimatological regions. Finally, some recommendations for further research are given, including the need for access to updated data across national boundaries. A joint interdisciplinary effort is suggested to advance our knowledge through a comprehensive assessment of recent major large-scale droughts in Europe.

  17. NOA: a novel Network Ontology Analysis method

    PubMed Central

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

    2011-01-01

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

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

    PubMed Central

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

    2014-01-01

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

  19. 77 FR 35711 - Strong Cities, Strong Communities National Resource Network Pilot Program Advance Notice and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-06-14

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

  20. Invisible but Essential: The Role of Professional Networks in Promoting Faculty Agency in Career Advancement

    ERIC Educational Resources Information Center

    Niehaus, Elizabeth; O'Meara, KerryAnn

    2015-01-01

    The benefits of professional networks are largely invisible to the people embedded in them (O'Reilly 1991), yet professional networks may provide key benefits for faculty careers. The purpose of the study reported here was to explore the role of professional networks in faculty agency in career advancement, specifically focusing on the overall…

  1. Teaching Advanced Concepts in Computer Networks: VNUML-UM Virtualization Tool

    ERIC Educational Resources Information Center

    Ruiz-Martinez, A.; Pereniguez-Garcia, F.; Marin-Lopez, R.; Ruiz-Martinez, P. M.; Skarmeta-Gomez, A. F.

    2013-01-01

    In the teaching of computer networks the main problem that arises is the high price and limited number of network devices the students can work with in the laboratories. Nowadays, with virtualization we can overcome this limitation. In this paper, we present a methodology that allows students to learn advanced computer network concepts through…

  2. Analysis of neutron noise spectra using neural networks

    SciTech Connect

    Korsah, K. ); Uhrig, R.E. Tennessee Univ., Knoxville, TN )

    1991-01-01

    Neural network architectures based on the back-propagation paradigm have been developed to recognize the features, and detect resonance shifts in, power spectral density (PSD) data. Our goal is to advance the state of the art in the application of noise analysis techniques to monitor nuclear reactor internals. The initial objectives have been to use PSD data, acquired over a period of about 2 years by PSDREC (power spectral density recognition system), to develop neural networks that are able to differentiate between normal neutron power spectral density data and anomalous spectral data, and detect significant shifts in the positions of spectral resonances while reducing the effect of small shifts. Neural network systems referred to in this paper as spectral feature detectors (SFDs) and integral network filters have been developed to meet these objectives. The performance of the SFDs is the subject of this paper. 2 refs., 2 figs.

  3. Lambdastation: a forwarding and admission control service to interface production network facilities with advanced research network paths

    SciTech Connect

    DeMar, Philip; Petravick, Don; /Fermilab

    2004-12-01

    Over the past several years, there has been a great deal of research effort and funding put into the deployment of optical-based, advanced technology wide-area networks. Fermilab and CalTech have initiated a project to enable our production network facilities to exploit these advanced research network facilities. Our objective is to forward designated data transfers across these advanced wide area networks on a per-flow basis, making use our capacious production-use storage systems connected to the local campus network. To accomplish this, we intend to develop a dynamically provisioned forwarding service that would provide alternate path forwarding onto available wide area advanced research networks. The service would dynamically reconfigure forwarding of specific flows within our local production-use network facilities, as well as provide an interface to enable applications to utilize the service. We call this service LambdaStation. If one envisions wide area optical network paths as high bandwidth data railways, then LambdaStation would functionally be the railroad terminal that regulates which flows at the local site get directed onto the high bandwidth data railways. LambdaStation is a DOE-funded SciDac research project in its very early stage of development.

  4. Advanced Fuel Cycle Economic Sensitivity Analysis

    SciTech Connect

    David Shropshire; Kent Williams; J.D. Smith; Brent Boore

    2006-12-01

    A fuel cycle economic analysis was performed on four fuel cycles to provide a baseline for initial cost comparison using the Gen IV Economic Modeling Work Group G4 ECON spreadsheet model, Decision Programming Language software, the 2006 Advanced Fuel Cycle Cost Basis report, industry cost data, international papers, the nuclear power related cost study from MIT, Harvard, and the University of Chicago. The analysis developed and compared the fuel cycle cost component of the total cost of energy for a wide range of fuel cycles including: once through, thermal with fast recycle, continuous fast recycle, and thermal recycle.

  5. Advanced Analysis Methods in High Energy Physics

    SciTech Connect

    Pushpalatha C. Bhat

    2001-10-03

    During the coming decade, high energy physics experiments at the Fermilab Tevatron and around the globe will use very sophisticated equipment to record unprecedented amounts of data in the hope of making major discoveries that may unravel some of Nature's deepest mysteries. The discovery of the Higgs boson and signals of new physics may be around the corner. The use of advanced analysis techniques will be crucial in achieving these goals. The author discusses some of the novel methods of analysis that could prove to be particularly valuable for finding evidence of any new physics, for improving precision measurements and for exploring parameter spaces of theoretical models.

  6. Performance analysis of Integrated Communication and Control System networks

    NASA Technical Reports Server (NTRS)

    Halevi, Y.; Ray, A.

    1990-01-01

    This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

  7. Stochastic flux analysis of chemical reaction networks

    PubMed Central

    2013-01-01

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

  8. Advanced Power Plant Development and Analysis Methodologies

    SciTech Connect

    A.D. Rao; G.S. Samuelsen; F.L. Robson; B. Washom; S.G. Berenyi

    2006-06-30

    Under the sponsorship of the U.S. Department of Energy/National Energy Technology Laboratory, a multi-disciplinary team led by the Advanced Power and Energy Program of the University of California at Irvine is defining the system engineering issues associated with the integration of key components and subsystems into advanced power plant systems with goals of achieving high efficiency and minimized environmental impact while using fossil fuels. These power plant concepts include 'Zero Emission' power plants and the 'FutureGen' H2 co-production facilities. The study is broken down into three phases. Phase 1 of this study consisted of utilizing advanced technologies that are expected to be available in the 'Vision 21' time frame such as mega scale fuel cell based hybrids. Phase 2 includes current state-of-the-art technologies and those expected to be deployed in the nearer term such as advanced gas turbines and high temperature membranes for separating gas species and advanced gasifier concepts. Phase 3 includes identification of gas turbine based cycles and engine configurations suitable to coal-based gasification applications and the conceptualization of the balance of plant technology, heat integration, and the bottoming cycle for analysis in a future study. Also included in Phase 3 is the task of acquiring/providing turbo-machinery in order to gather turbo-charger performance data that may be used to verify simulation models as well as establishing system design constraints. The results of these various investigations will serve as a guide for the U. S. Department of Energy in identifying the research areas and technologies that warrant further support.

  9. Analysis of complex networks using aggressive abstraction.

    SciTech Connect

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

    2008-10-01

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

  10. 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…

  11. Advances in Artificial Neural Networks - Methodological Development and Application

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Artificial neural networks as a major soft-computing technology have been extensively studied and applied during the last three decades. Research on backpropagation training algorithms for multilayer perceptron networks has spurred development of other neural network training algorithms for other ne...

  12. Six Networking Tips to Advance Your Career Goals

    ERIC Educational Resources Information Center

    Jones, Angela

    2013-01-01

    Teachers may wonder why networking is relevant. The point of networking is to cultivate relationships for the exchange of information, services, or resources for employment or business. This may sound cold to those in the educational world, where children and youth are the No. 1 customers, but a network can be a huge support as it pertains to…

  13. Analysis and Testing of Mobile Wireless Networks

    NASA Technical Reports Server (NTRS)

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

    2002-01-01

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

  14. Protein identification by spectral networks analysis.

    PubMed

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

    2007-04-10

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

  15. Extending Stochastic Network Calculus to Loss Analysis

    PubMed Central

    Yu, Li; Zheng, Jun

    2013-01-01

    Loss is an important parameter of Quality of Service (QoS). Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor. PMID:24228019

  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. NEXCADE: perturbation analysis for complex networks.

    PubMed

    Yadav, Gitanjali; Babu, Suresh

    2012-01-01

    Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS) can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html. PMID:22870252

  18. NEXCADE: Perturbation Analysis for Complex Networks

    PubMed Central

    Yadav, Gitanjali; Babu, Suresh

    2012-01-01

    Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the ‘robust, yet fragile’ nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS) can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html. PMID:22870252

  19. 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.

  20. 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

  1. Social network analysis for program implementation.

    PubMed

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

    2015-01-01

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

  2. Network analysis reveals potential markers for pediatric adrenocortical carcinoma

    PubMed Central

    Kulshrestha, Anurag; Suman, Shikha; Ranjan, Rakesh

    2016-01-01

    Pediatric adrenocortical carcinoma (ACC) is a rare malignancy with a poor outcome. Molecular mechanisms of pediatric ACC oncogenesis and advancement are not well understood. Accurate and timely diagnosis of the disease requires identification of new markers for pediatric ACC. Differentially expressed genes (DEGs) were identified from the gene expression profile of pediatric ACC and obtained from Gene Expression Omnibus. Gene Ontology functional and pathway enrichment analysis was implemented to recognize the functions of DEGs. A protein–protein interaction (PPI) and gene–gene functional interaction (GGI) network of DEGs was constructed. Hub gene detection and enrichment analysis of functional modules were performed. Furthermore, a gene regulatory network incorporating DEGs–microRNAs–transcription factors was constructed and analyzed. A total of 431 DEGs including 228 upregulated and 203 downregulated DEGs were screened. These genes were largely involved in cell cycle, steroid biosynthesis, and p53 signaling pathways. Upregulated genes, CDK1, CCNB1, CDC20, and BUB1B, were identified as the common hubs of PPI and GGI networks. All the four common hub genes were also part of modules of the PPI network. Moreover, all the four genes were also present in the largest module of GGI network. A gene regulatory network consisting of 82 microRNAs and 100 transcription factors was also constructed. CDK1, CCNB1, CDC20, and BUB1B may serve as potential biomarker of pediatric ACC and as potential targets for therapeutic approach, although experimental studies are required to authenticate our findings. PMID:27555782

  3. Recent advances in flow injection analysis.

    PubMed

    Trojanowicz, Marek; Kołacińska, Kamila

    2016-04-01

    A dynamic development of methodologies of analytical flow injection measurements during four decades since their invention has reinforced the solid position of flow analysis in the arsenal of techniques and instrumentation of contemporary chemical analysis. With the number of published scientific papers exceeding 20 000, and advanced instrumentation available for environmental, food, and pharmaceutical analysis, flow analysis is well established as an extremely vital field of modern flow chemistry, which is developed simultaneously with methods of chemical synthesis carried out under flow conditions. This review work is based on almost 300 original papers published mostly in the last decade, with special emphasis put on presenting novel achievements from the most recent 2-3 years in order to indicate current development trends of this methodology. Besides the evolution of the design of whole measuring systems, and including especially new applications of various detections methods, several aspects of implications of progress in nanotechnology, and miniaturization of measuring systems for application in different field of modern chemical analysis are also discussed. PMID:26906258

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

    NASA Astrophysics Data System (ADS)

    Hong, Sungryong; Dey, Arjun

    2015-06-01

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

  5. Full Service ISDN Satellite (FSIS) network model for advanced ISDN satellite design and experiments

    NASA Technical Reports Server (NTRS)

    Pepin, Gerard R.

    1992-01-01

    The Full Service Integrated Services Digital Network (FSIS) network model for advanced satellite designs describes a model suitable for discrete event simulations. A top down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ACTS and the Interim Service ISDN Satellite (ISIS) perform ISDN protocol analyses and switching decisions in the terrestrial domain, whereas FSIS makes all its analyses and decisions on-board the ISDN satellite.

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

    NASA Astrophysics Data System (ADS)

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

    2008-02-01

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

  7. Network Anomaly Detection Based on Wavelet Analysis

    NASA Astrophysics Data System (ADS)

    Lu, Wei; Ghorbani, Ali A.

    2008-12-01

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

  8. Advanced Satellite Research Project: SCAR Research Database. Bibliographic analysis

    NASA Technical Reports Server (NTRS)

    Pelton, Joseph N.

    1991-01-01

    The literature search was provided to locate and analyze the most recent literature that was relevant to the research. This was done by cross-relating books, articles, monographs, and journals that relate to the following topics: (1) Experimental Systems - Advanced Communications Technology Satellite (ACTS), and (2) Integrated System Digital Network (ISDN) and Advance Communication Techniques (ISDN and satellites, ISDN standards, broadband ISDN, flame relay and switching, computer networks and satellites, satellite orbits and technology, satellite transmission quality, and network configuration). Bibliographic essay on literature citations and articles reviewed during the literature search task is provided.

  9. Advanced Algorithms for Local Routing Strategy on Complex Networks.

    PubMed

    Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

    2016-01-01

    Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70-90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

  10. Advanced Algorithms for Local Routing Strategy on Complex Networks

    PubMed Central

    Lin, Benchuan; Chen, Bokui; Gao, Yachun; Tse, Chi K.; Dong, Chuanfei; Miao, Lixin; Wang, Binghong

    2016-01-01

    Despite the significant improvement on network performance provided by global routing strategies, their applications are still limited to small-scale networks, due to the need for acquiring global information of the network which grows and changes rapidly with time. Local routing strategies, however, need much less local information, though their transmission efficiency and network capacity are much lower than that of global routing strategies. In view of this, three algorithms are proposed and a thorough investigation is conducted in this paper. These algorithms include a node duplication avoidance algorithm, a next-nearest-neighbor algorithm and a restrictive queue length algorithm. After applying them to typical local routing strategies, the critical generation rate of information packets Rc increases by over ten-fold and the average transmission time 〈T〉 decreases by 70–90 percent, both of which are key physical quantities to assess the efficiency of routing strategies on complex networks. More importantly, in comparison with global routing strategies, the improved local routing strategies can yield better network performance under certain circumstances. This is a revolutionary leap for communication networks, because local routing strategy enjoys great superiority over global routing strategy not only in terms of the reduction of computational expense, but also in terms of the flexibility of implementation, especially for large-scale networks. PMID:27434502

  11. Social Networks and Career Advancement of People with Disabilities

    ERIC Educational Resources Information Center

    Kulkarni, Mukta

    2012-01-01

    Although organizational social networks are known to influence career mobility, the specific direction of this influence is different for diverse employee groups. Diversity in organizational network research has been operationalized on various dimensions such as race and ethnicity, age, religion, education, occupation, and gender. Missing in this…

  12. Advancing Behavior Analysis in Zoos and Aquariums.

    PubMed

    Maple, Terry L; Segura, Valerie D

    2015-05-01

    Zoos, aquariums, and other captive animal facilities offer promising opportunities to advance the science and practice of behavior analysis. Zoos and aquariums are necessarily concerned with the health and well-being of their charges and are held to a high standard by their supporters (visitors, members, and donors), organized critics, and the media. Zoos and aquariums offer unique venues for teaching and research and a locus for expanding the footprint of behavior analysis. In North America, Europe, and the UK, formal agreements between zoos, aquariums, and university graduate departments have been operating successfully for decades. To expand on this model, it will be necessary to help zoo and aquarium managers throughout the world to recognize the value of behavior analysis in the delivery of essential animal health and welfare services. Academic institutions, administrators, and invested faculty should consider the utility of training students to meet the growing needs of applied behavior analysis in zoos and aquariums and other animal facilities such as primate research centers, sanctuaries, and rescue centers. PMID:27540508

  13. Cross-Disciplinary Detection and Analysis of Network Motifs

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2015-01-01

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

  15. 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.

  16. Medical image analysis with artificial neural networks.

    PubMed

    Jiang, J; Trundle, P; Ren, J

    2010-12-01

    Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. PMID:20713305

  17. NASTRAN flutter analysis of advanced turbopropellers

    NASA Technical Reports Server (NTRS)

    Elchuri, V.; Smith, G. C. C.

    1982-01-01

    An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs in NASTRAN was modified and applied to investigate the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) variable sweep. The two dimensional subsonic cascade unsteady aerodynamic theory was applied in a strip theory manner with appropriate modifications for the sweep effects. Each strip is associated with a chord selected normal to any spanwise reference curve such as the blade leading edge. The stability of three operating conditions of a 10-bladed propeller is analyzed. Each of these operating conditions is iterated once to determine the flutter boundary. A 5-bladed propeller is also analyzed at one operating condition to investigate stability. Analytical results obtained are in very good agreement with those from wind tunnel tests.

  18. Advanced development in chemical analysis of Cordyceps.

    PubMed

    Zhao, J; Xie, J; Wang, L Y; Li, S P

    2014-01-01

    Cordyceps sinensis, also called DongChongXiaCao (winter worm summer grass) in Chinese, is a well-known and valued traditional Chinese medicine. In 2006, we wrote a review for discussing the markers and analytical methods in quality control of Cordyceps (J. Pharm. Biomed. Anal. 41 (2006) 1571-1584). Since then this review has been cited by others for more than 60 times, which suggested that scientists have great interest in this special herbal material. Actually, the number of publications related to Cordyceps after 2006 is about 2-fold of that in two decades before 2006 according to the data from Web of Science. Therefore, it is necessary to review and discuss the advanced development in chemical analysis of Cordyceps since then. PMID:23688494

  19. Security Aspects of Smart Cards vs. Embedded Security in Machine-to-Machine (M2M) Advanced Mobile Network Applications

    NASA Astrophysics Data System (ADS)

    Meyerstein, Mike; Cha, Inhyok; Shah, Yogendra

    The Third Generation Partnership Project (3GPP) standardisation group currently discusses advanced applications of mobile networks such as Machine-to-Machine (M2M) communication. Several security issues arise in these contexts which warrant a fresh look at mobile networks’ security foundations, resting on smart cards. This paper contributes a security/efficiency analysis to this discussion and highlights the role of trusted platform technology to approach these issues.

  20. Logical Modeling and Dynamical Analysis of Cellular Networks

    PubMed Central

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

    2016-01-01

    The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle. PMID:27303434

  1. Identification of Neurodegenerative Factors Using Translatome-Regulatory Network Analysis

    PubMed Central

    Brichta, Lars; Shin, William; Jackson-Lewis, Vernice; Blesa, Javier; Yap, Ee-Lynn; Walker, Zachary; Zhang, Jack; Roussarie, Jean-Pierre; Alvarez, Mariano J.; Califano, Andrea; Przedborski, Serge; Greengard, Paul

    2016-01-01

    For degenerative disorders of the central nervous system, the major obstacle to therapeutic advancement has been the challenge of identifying the key molecular mechanisms underlying neuronal loss. We developed a combinatorial approach including translational profiling and brain regulatory network analysis to search for key determinants of neuronal survival or death. Following the generation of transgenic mice for cell type-specific profiling of midbrain dopaminergic neurons, we established and compared translatome libraries reflecting the molecular signature of these cells at baseline or under degenerative stress. Analysis of these libraries by interrogating a context-specific brain regulatory network led to the identification of a repertoire of intrinsic upstream regulators that drive the dopaminergic stress response. The altered activity of these regulators was not associated with changes in their expression levels. This strategy can be generalized for the elucidation of novel molecular determinants involved in the degeneration of other classes of neurons. PMID:26214373

  2. Advances Made in the Next Generation of Satellite Networks

    NASA Technical Reports Server (NTRS)

    Bhasin, Kul B.

    1999-01-01

    Because of the unique networking characteristics of communications satellites, global satellite networks are moving to the forefront in enhancing national and global information infrastructures. Simultaneously, broadband data services, which are emerging as the major market driver for future satellite and terrestrial networks, are being widely acknowledged as the foundation for an efficient global information infrastructure. In the past 2 years, various task forces and working groups around the globe have identified pivotal topics and key issues to address if we are to realize such networks in a timely fashion. In response, industry, government, and academia undertook efforts to address these topics and issues. A workshop was organized to provide a forum to assess the current state-of-the-art, identify key issues, and highlight the emerging trends in the next-generation architectures, data protocol development, communication interoperability, and applications. The Satellite Networks: Architectures, Applications, and Technologies Workshop was hosted by the Space Communication Program at the NASA Lewis Research Center in Cleveland, Ohio. Nearly 300 executives and technical experts from academia, industry, and government, representing the United States and eight other countries, attended the event (June 2 to 4, 1998). The program included seven panels and invited sessions and nine breakout sessions in which 42 speakers presented on technical topics. The proceedings covers a wide range of topics: access technology and protocols, architectures and network simulations, asynchronous transfer mode (ATM) over satellite networks, Internet over satellite networks, interoperability experiments and applications, multicasting, NASA interoperability experiment programs, NASA mission applications, and Transmission Control Protocol/Internet Protocol (TCP/IP) over satellite: issues, relevance, and experience.

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

    PubMed Central

    2011-01-01

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

  4. The Quake-Catcher Network: A Community-Led, Strong-Motion Network with Implications for Earthquake Advanced Alert

    NASA Astrophysics Data System (ADS)

    Cochran, E. S.; Lawrence, J. F.; Christensen, C. M.; Jakka, R. S.; Chung, A. I.

    2009-12-01

    The goal of the Quake-Catcher Network (QCN) is to dramatically increase the number of strong-motion observations by exploiting recent advances in sensing technologies and cyberinfrastructure. Micro-Electro-Mechanical Systems (MEMS) triaxial accelerometers are very low cost (50-100), interface to any desktop computer via USB cable, and provide high-quality acceleration data. Preliminary shake table tests show the MEMS accelerometers can record high-fidelity seismic data and provide linear phase and amplitude response over a wide frequency range. Volunteer computing provides a mechanism to expand strong-motion seismology with minimal infrastructure costs, while promoting community participation in science. Volunteer computing also allows for rapid transfer of metadata, such as that used to rapidly determine the magnitude and location of an earthquake, from participating stations. QCN began distributing sensors and software to K-12 schools and the general public in April 2008 and has grown to roughly 1000 stations. Initial analysis shows metadata are received within 1-14 seconds from the observation of a trigger; the larger data latencies are correlated with greater server-station distances. Currently, we are testing a series of triggering algorithms to maximize the number of earthquakes captured while minimizing false triggers. We are also testing algorithms to automatically detect P- and S-wave arrivals in real time. Trigger times, wave amplitude, and station information are currently uploaded to the server for each trigger. Future work will identify additional metadata useful for quickly determining earthquake location and magnitude. The increased strong-motion observations made possible by QCN will greatly augment the capability of seismic networks to quickly estimate the location and magnitude of an earthquake for advanced alert to the public. In addition, the dense waveform observations will provide improved source imaging of a rupture in near-real-time. These

  5. NAPS: Network Analysis of Protein Structures.

    PubMed

    Chakrabarty, Broto; Parekh, Nita

    2016-07-01

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

  6. Network analysis of eight industrial symbiosis systems

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

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

    PubMed

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

    2015-01-01

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

  8. 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

  9. Network analysis of an online community

    NASA Astrophysics Data System (ADS)

    Han, Sangman; Kim, Beom Jun

    2008-10-01

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

  10. Advancing Reversible Shape Memory by Tuning Network Architecture

    NASA Astrophysics Data System (ADS)

    Li, Qiaoxi; Zhou, Jing; Vatankhah Varnosfaderani, Mohammad; Nykypanchuk, Dmytro; Gang, Oleg; Sheiko, Sergei; University of north carolina at chapel hill Collaboration; Brookhaven National Lab-CFN Collaboration

    Recently, reversible shape memory (RSM) has been realized in conventional semi-crystalline elastomers without applying any external force and synthetic programming. The mechanism is ascribed to counteraction between thermodynamically driven relaxation of a strained polymer network and kinetically preferred self-seeding recrystallization of constrained network strands. In order to maximize RSM's performance in terms of (i) range of reversible strain, (ii) rate of strain recovery, and (iii) relaxation time of reversibility, we have designed a systematic series of networks with different topologies and crosslinking densities, including purposely introduced dangling chains and irregular meshes. Within a broad range of crosslink density ca. 50-1000 mol/m3, we have demonstrated that the RSM's properties improve significantly with increasing crosslink density, regardless of network topology. Actually, one of the most irregular networks with densest crosslinking allowed achieving up to 80% of the programmed strain being fully reversible, fast recovery rate up to 0.05 K-1, and less than 15% decrease of reversibility after hours of annealing at partial melt state. With this understanding and optimization of RSM, we pursue an idea of shape control through self-assembly of shape-memory particles. For this purpose, 3D printing has been employed to prepare large assemblies of particles possessing specific shapes and morphologies.

  11. High-speed parallel-processing networks for advanced architectures

    SciTech Connect

    Morgan, D.R.

    1988-06-01

    This paper describes various parallel-processing architecture networks that are candidates for eventual airborne use. An attempt at projecting which type of network is suitable or optimum for specific metafunction or stand-alone applications is made. However, specific algorithms will need to be developed and bench marks executed before firm conclusions can be drawn. Also, a conceptual projection of how these processors can be built in small, flyable units through the use of wafer-scale integration is offered. The use of the PAVE PILLAR system architecture to provide system level support for these tightly coupled networks is described. The author concludes that: (1) extremely high processing speeds implemented in flyable hardware is possible through parallel-processing networks if development programs are pursued; (2) dramatic speed enhancements through parallel processing requires an excellent match between the algorithm and computer-network architecture; (3) matching several high speed parallel oriented algorithms across the aircraft system to a limited set of hardware modules may be the most cost-effective approach to achieving speed enhancements; and (4) software-development tools and improved operating systems will need to be developed to support efficient parallel-processor use.

  12. Developing an intelligence analysis process through social network analysis

    NASA Astrophysics Data System (ADS)

    Waskiewicz, Todd; LaMonica, Peter

    2008-04-01

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

  13. A Flexible Reservation Algorithm for Advance Network Provisioning

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2010-04-12

    Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnet's OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.

  14. Differential Network Analysis in Human Cancer Research

    PubMed Central

    Gill, Ryan; Datta, Somnath; Datta, Susmita

    2016-01-01

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

  15. 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

  16. 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.

  17. Advanced Coal Wind Hybrid: Economic Analysis

    SciTech Connect

    Phadke, Amol; Goldman, Charles; Larson, Doug; Carr, Tom; Rath, Larry; Balash, Peter; Yih-Huei, Wan

    2008-11-28

    Growing concern over climate change is prompting new thinking about the technologies used to generate electricity. In the future, it is possible that new government policies on greenhouse gas emissions may favor electric generation technology options that release zero or low levels of carbon emissions. The Western U.S. has abundant wind and coal resources. In a world with carbon constraints, the future of coal for new electrical generation is likely to depend on the development and successful application of new clean coal technologies with near zero carbon emissions. This scoping study explores the economic and technical feasibility of combining wind farms with advanced coal generation facilities and operating them as a single generation complex in the Western US. The key questions examined are whether an advanced coal-wind hybrid (ACWH) facility provides sufficient advantages through improvements to the utilization of transmission lines and the capability to firm up variable wind generation for delivery to load centers to compete effectively with other supply-side alternatives in terms of project economics and emissions footprint. The study was conducted by an Analysis Team that consists of staff from the Lawrence Berkeley National Laboratory (LBNL), National Energy Technology Laboratory (NETL), National Renewable Energy Laboratory (NREL), and Western Interstate Energy Board (WIEB). We conducted a screening level analysis of the economic competitiveness and technical feasibility of ACWH generation options located in Wyoming that would supply electricity to load centers in California, Arizona or Nevada. Figure ES-1 is a simple stylized representation of the configuration of the ACWH options. The ACWH consists of a 3,000 MW coal gasification combined cycle power plant equipped with carbon capture and sequestration (G+CC+CCS plant), a fuel production or syngas storage facility, and a 1,500 MW wind plant. The ACWH project is connected to load centers by a 3,000 MW

  18. Wireless Sensors and Networks for Advanced Energy Management

    SciTech Connect

    Hardy, J.E.

    2005-05-06

    Numerous national studies and working groups have identified low-cost, very low-power wireless sensors and networks as a critical enabling technology for increasing energy efficiency, reducing waste, and optimizing processes. Research areas for developing such sensor and network platforms include microsensor arrays, ultra-low power electronics and signal conditioning, data/control transceivers, and robust wireless networks. A review of some of the research in the following areas will be discussed: (1) Low-cost, flexible multi-sensor array platforms (CO{sub 2}, NO{sub x}, CO, humidity, NH{sub 3}, O{sub 2}, occupancy, etc.) that enable energy and emission reductions in applications such as buildings and manufacturing; (2) Modeling investments (energy usage and savings to drive capital investment decisions) and estimated uptime improvements through pervasive gathering of equipment and process health data and its effects on energy; (3) Robust, self-configuring wireless sensor networks for energy management; and (4) Quality-of-service for secure and reliable data transmission from widely distributed sensors. Wireless communications is poised to support technical innovations in the industrial community, with widespread use of wireless sensors forecasted to improve manufacturing production and energy efficiency and reduce emissions. Progress being made in wireless system components, as described in this paper, is helping bring these projected improvements to reality.

  19. Internet2: Building and Deploying Advanced, Networked Applications.

    ERIC Educational Resources Information Center

    Hanss, Ted

    1997-01-01

    Internet2, a consortium effort of over 100 universities, is investing in upgrading campus and national computer network platforms for such applications as digital libraries, collaboration environments, tele-medicine, and distance-independent instruction. The project is described, issues the project intends to address are detailed, and ways in…

  20. A Survey of Geosensor Networks: Advances in Dynamic Environmental Monitoring

    PubMed Central

    Nittel, Silvia

    2009-01-01

    In the recent decade, several technology trends have influenced the field of geosciences in significant ways. The first trend is the more readily available technology of ubiquitous wireless communication networks and progress in the development of low-power, short-range radio-based communication networks, the miniaturization of computing and storage platforms as well as the development of novel microsensors and sensor materials. All three trends have changed the type of dynamic environmental phenomena that can be detected, monitored and reacted to. Another important aspect is the real-time data delivery of novel platforms today. In this paper, I will survey the field of geosensor networks, and mainly focus on the technology of small-scale geosensor networks, example applications and their feasibility and lessons learnt as well as the current research questions posed by using this technology today. Furthermore, my objective is to investigate how this technology can be embedded in the current landscape of intelligent sensor platforms in the geosciences and identify its place and purpose. PMID:22346721

  1. Distributed networks enable advances in US space weather operations

    NASA Astrophysics Data System (ADS)

    Tobiska, W. Kent; Bouwer, S. Dave

    2011-06-01

    Space weather, the shorter-term variable impact of the Sun’s photons, solar wind particles, and interplanetary magnetic field upon the Earth’s environment, adversely affects our technological systems. These technological systems, including their space component, are increasingly being seen as a way to help solve 21st Century problems such as climate change, energy access, fresh water availability, and transportation coordination. Thus, the effects of space weather on space systems and assets must be mitigated and operational space weather using automated distributed networks has emerged as a common operations methodology. The evolution of space weather operations is described and the description of distributed network architectures is provided, including their use of tiers, data objects, redundancy, and time domain definitions. There are several existing distributed networks now providing space weather information and the lessons learned in developing those networks are discussed along with the details of examples for the Solar Irradiance Platform (SIP), Communication Alert and Prediction System (CAPS), GEO Alert and Prediction System (GAPS), LEO Alert and Prediction System (LAPS), Radiation Alert and Prediction System (RAPS), and Magnetosphere Alert and Prediction System (MAPS).

  2. Systems analysis of biological networks in skeletal muscle function

    PubMed Central

    Smith, Lucas R.; Meyer, Gretchen; Lieber, Richard L.

    2014-01-01

    Skeletal muscle function depends on the efficient coordination among subcellular systems. These systems are composed of proteins encoded by a subset of genes, all of which are tightly regulated. In the cases where regulation is altered because of disease or injury, dysfunction occurs. To enable objective analysis of muscle gene expression profiles, we have defined nine biological networks whose coordination is critical to muscle function. We begin by describing the expression of proteins necessary for optimal neuromuscular junction function that results in the muscle cell action potential. That action potential is transmitted to proteins involved in excitation–contraction coupling enabling Ca2+ release. Ca2+ then activates contractile proteins supporting actin and myosin cross-bridge cycling. Force generated by cross-bridges is transmitted via cytoskeletal proteins through the sarcolemma and out to critical proteins that support the muscle extracellular matrix. Muscle contraction is fueled through many proteins that regulate energy metabolism. Inflammation is a common response to injury that can result in alteration of many pathways within muscle. Muscle also has multiple pathways that regulate size through atrophy or hypertrophy. Finally, the isoforms associated with fast muscle fibers and their corresponding isoforms in slow muscle fibers are delineated. These nine networks represent important biological systems that affect skeletal muscle function. Combining high-throughput systems analysis with advanced networking software will allow researchers to use these networks to objectively study skeletal muscle systems. PMID:23188744

  3. Network analysis of genes and their association with diseases.

    PubMed

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

    2016-09-15

    A plethora of network-based approaches within the Systems Biology universe have been applied, to date, to investigate the underlying molecular mechanisms of various human diseases. In the present study, we perform a bipartite, topological and clustering graph analysis in order to gain a better understanding of the relationships between human genetic diseases and the relationships between the genes that are implicated in them. For this purpose, disease-disease and gene-gene networks were constructed from combined gene-disease association networks. The latter, were created by collecting and integrating data from three diverse resources, each one with different content covering from rare monogenic disorders to common complex diseases. This data pluralism enabled us to uncover important associations between diseases with unrelated phenotypic manifestations but with common genetic origin. For our analysis, the topological attributes and the functional implications of the individual networks were taken into account and are shortly discussed. We believe that some observations of this study could advance our understanding regarding the etiology of a disease with distinct pathological manifestations, and simultaneously provide the springboard for the development of preventive and therapeutic strategies and its underlying genetic mechanisms. PMID:27265032

  4. Systems analysis of biological networks in skeletal muscle function.

    PubMed

    Smith, Lucas R; Meyer, Gretchen; Lieber, Richard L

    2013-01-01

    Skeletal muscle function depends on the efficient coordination among subcellular systems. These systems are composed of proteins encoded by a subset of genes, all of which are tightly regulated. In the cases where regulation is altered because of disease or injury, dysfunction occurs. To enable objective analysis of muscle gene expression profiles, we have defined nine biological networks whose coordination is critical to muscle function. We begin by describing the expression of proteins necessary for optimal neuromuscular junction function that results in the muscle cell action potential. That action potential is transmitted to proteins involved in excitation-contraction coupling enabling Ca(2+) release. Ca(2+) then activates contractile proteins supporting actin and myosin cross-bridge cycling. Force generated by cross-bridges is transmitted via cytoskeletal proteins through the sarcolemma and out to critical proteins that support the muscle extracellular matrix. Muscle contraction is fueled through many proteins that regulate energy metabolism. Inflammation is a common response to injury that can result in alteration of many pathways within muscle. Muscle also has multiple pathways that regulate size through atrophy or hypertrophy. Finally, the isoforms associated with fast muscle fibers and their corresponding isoforms in slow muscle fibers are delineated. These nine networks represent important biological systems that affect skeletal muscle function. Combining high-throughput systems analysis with advanced networking software will allow researchers to use these networks to objectively study skeletal muscle systems. PMID:23188744

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

    SciTech Connect

    Pakzad, S. . Dept. of Electrical Engineering)

    1989-08-01

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

  6. Mapping Creativity: Creativity Measurements Network Analysis

    ERIC Educational Resources Information Center

    Pinheiro, Igor Reszka; Cruz, Roberto Moraes

    2014-01-01

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

  7. Nonlinear Time Series Analysis via Neural Networks

    NASA Astrophysics Data System (ADS)

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

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

  8. EFL Writers' Social Networks: Impact on Advanced Academic Literacy Development

    ERIC Educational Resources Information Center

    Ferenz, Orna

    2005-01-01

    For non-native English writers, second language (L2) advanced academic literacy encompasses knowledge of the rhetorical, linguistic, social and cultural features of academic discourse as well as knowledge of English as used by their academic disciplines. Literacy is acquired through a socialization process embedded in social practice, patterned by…

  9. Diversity Performance Analysis on Multiple HAP Networks.

    PubMed

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

    2015-01-01

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

  10. Analysis of Social Networks by Tensor Decomposition

    NASA Astrophysics Data System (ADS)

    Sizov, Sergej; Staab, Steffen; Franz, Thomas

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

  11. Diversity Performance Analysis on Multiple HAP Networks

    PubMed 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

  12. Vulnerability analysis methods for road networks

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    PubMed Central

    Koschützki, Dirk; Schreiber, Falk

    2008-01-01

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

  14. Parametric cost analysis for advanced energy concepts

    SciTech Connect

    Not Available

    1983-10-01

    This report presents results of an exploratory study to develop parametric cost estimating relationships for advanced fossil-fuel energy systems. The first of two tasks was to develop a standard Cost Chart of Accounts to serve as a basic organizing framework for energy systems cost analysis. The second task included development of selected parametric cost estimating relationships (CERs) for individual elements (or subsystems) of a fossil fuel plant, nominally for the Solvent-Refined Coal (SRC) process. Parametric CERs are presented for the following elements: coal preparation, coal slurry preparation, dissolver (reactor); gasification; oxygen production; acid gas/CO/sub 2/ removal; shift conversion; cryogenic hydrogen recovery; and sulfur removal. While the nominal focus of the study was on the SRC process, each of these elements is found in other fossil fuel processes. Thus, the results of this effort have broader potential application. However, it should also be noted that the CERs presented in this report are based upon a limited data base. Thus, they are applicable over a limited range of values (of the independent variables) and for a limited set of specific technologies (e.g., the gasifier CER is for the multi-train, Koppers-Totzek process). Additional work is required to extend the range of these CERs. 16 figures, 13 tables.

  15. Pathway and network analysis of cancer genomes.

    PubMed

    2015-07-01

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

  16. Pathway and Network Analysis of Cancer Genomes

    PubMed Central

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

    2016-01-01

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

  17. RCytoscape: tools for exploratory network analysis

    PubMed Central

    2013-01-01

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

  18. 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

  19. Advanced information processing system: Authentication protocols for network communication

    NASA Technical Reports Server (NTRS)

    Harper, Richard E.; Adams, Stuart J.; Babikyan, Carol A.; Butler, Bryan P.; Clark, Anne L.; Lala, Jaynarayan H.

    1994-01-01

    In safety critical I/O and intercomputer communication networks, reliable message transmission is an important concern. Difficulties of communication and fault identification in networks arise primarily because the sender of a transmission cannot be identified with certainty, an intermediate node can corrupt a message without certainty of detection, and a babbling node cannot be identified and silenced without lengthy diagnosis and reconfiguration . Authentication protocols use digital signature techniques to verify the authenticity of messages with high probability. Such protocols appear to provide an efficient solution to many of these problems. The objective of this program is to develop, demonstrate, and evaluate intercomputer communication architectures which employ authentication. As a context for the evaluation, the authentication protocol-based communication concept was demonstrated under this program by hosting a real-time flight critical guidance, navigation and control algorithm on a distributed, heterogeneous, mixed redundancy system of workstations and embedded fault-tolerant computers.

  20. Advanced obstacle avoidance for a laser based wheelchair using optimised Bayesian neural networks.

    PubMed

    Trieu, Hoang T; Nguyen, Hung T; Willey, Keith

    2008-01-01

    In this paper we present an advanced method of obstacle avoidance for a laser based intelligent wheelchair using optimized Bayesian neural networks. Three neural networks are designed for three separate sub-tasks: passing through a door way, corridor and wall following and general obstacle avoidance. The accurate usable accessible space is determined by including the actual wheelchair dimensions in a real-time map used as inputs to each networks. Data acquisitions are performed separately to collect the patterns required for specified sub-tasks. Bayesian frame work is used to determine the optimal neural network structure in each case. Then these networks are trained under the supervision of Bayesian rule. Experiment results showed that compare to the VFH algorithm our neural networks navigated a smoother path following a near optimum trajectory. PMID:19163454

  1. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V.; Marwan, Norbert; Dijkstra, Henk A.; Kurths, Jürgen

    2015-11-01

    We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology.

  2. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package.

    PubMed

    Donges, Jonathan F; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik V; Marwan, Norbert; Dijkstra, Henk A; Kurths, Jürgen

    2015-11-01

    We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. PMID:26627561

  3. 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…

  4. Advanced Materials and Solids Analysis Research Core (AMSARC)

    EPA Science Inventory

    The Advanced Materials and Solids Analysis Research Core (AMSARC), centered at the U.S. Environmental Protection Agency's (EPA) Andrew W. Breidenbach Environmental Research Center in Cincinnati, Ohio, is the foundation for the Agency's solids and surfaces analysis capabilities. ...

  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. Transportability in Network Meta-analysis.

    PubMed

    Kabali, Conrad; Ghazipura, Marya

    2016-07-01

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

  7. Network design for heavy rainfall analysis

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  8. Micro-macro analysis of complex networks.

    PubMed

    Marchiori, Massimo; Possamai, Lino

    2015-01-01

    Complex systems have attracted considerable interest because of their wide range of applications, and are often studied via a "classic" approach: study a specific system, find a complex network behind it, and analyze the corresponding properties. This simple methodology has produced a great deal of interesting results, but relies on an often implicit underlying assumption: the level of detail on which the system is observed. However, in many situations, physical or abstract, the level of detail can be one out of many, and might also depend on intrinsic limitations in viewing the data with a different level of abstraction or precision. So, a fundamental question arises: do properties of a network depend on its level of observability, or are they invariant? If there is a dependence, then an apparently correct network modeling could in fact just be a bad approximation of the true behavior of a complex system. In order to answer this question, we propose a novel micro-macro analysis of complex systems that quantitatively describes how the structure of complex networks varies as a function of the detail level. To this extent, we have developed a new telescopic algorithm that abstracts from the local properties of a system and reconstructs the original structure according to a fuzziness level. This way we can study what happens when passing from a fine level of detail ("micro") to a different scale level ("macro"), and analyze the corresponding behavior in this transition, obtaining a deeper spectrum analysis. The obtained results show that many important properties are not universally invariant with respect to the level of detail, but instead strongly depend on the specific level on which a network is observed. Therefore, caution should be taken in every situation where a complex network is considered, if its context allows for different levels of observability. PMID:25635812

  9. 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

  10. Analysis of Cascading Failure in Gene Networks

    PubMed Central

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

    2012-01-01

    It is an important subject to research the functional mechanism of cancer-related genes make in formation and development of cancers. The modern methodology of data analysis plays a very important role for deducing the relationship between cancers and cancer-related genes and analyzing functional mechanism of genome. In this research, we construct mutual information networks using gene expression profiles of glioblast and renal in normal condition and cancer conditions. We investigate the relationship between structure and robustness in gene networks of the two tissues using a cascading failure model based on betweenness centrality. Define some important parameters such as the percentage of failure nodes of the network, the average size-ratio of cascading failure, and the cumulative probability of size-ratio of cascading failure to measure the robustness of the networks. By comparing control group and experiment groups, we find that the networks of experiment groups are more robust than that of control group. The gene that can cause large scale failure is called structural key gene. Some of them have been confirmed to be closely related to the formation and development of glioma and renal cancer respectively. Most of them are predicted to play important roles during the formation of glioma and renal cancer, maybe the oncogenes, suppressor genes, and other cancer candidate genes in the glioma and renal cancer cells. However, these studies provide little information about the detailed roles of identified cancer genes. PMID:23248647

  11. 13C NMR Metabolomics: INADEQUATE Network Analysis

    PubMed Central

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

    2015-01-01

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

  12. Advances on tensor network theory: symmetries, fermions, entanglement, and holography

    NASA Astrophysics Data System (ADS)

    Orús, Román

    2014-11-01

    This is a short review on selected theory developments on tensor network (TN) states for strongly correlated systems. Specifically, we briefly review the effect of symmetries in TN states, fermionic TNs, the calculation of entanglement Hamiltonians from projected entangled pair states (PEPS), and the relation between the multi-scale entanglement renormalization ansatz (MERA) and the AdS/CFT or gauge/gravity duality. We stress the role played by entanglement in the emergence of several physical properties and objects through the TN language. Some recent results along these lines are also discussed.

  13. Visual Analysis of Complex Networks and Community Structure

    NASA Astrophysics Data System (ADS)

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

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  15. 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

  16. Advances in materials and current collecting networks for AMTEC electrodes

    NASA Technical Reports Server (NTRS)

    Ryan, M. A.; Jeffries-Nakamura, B.; Williams, R. M.; Underwood, M. L.; O'Connor, D.; Kikkert, S.

    1992-01-01

    Electrode materials for the Alkali Metal Thermal to Electric Converter (AMTEC) play a significant role in the efficiency of the device. RhW and PtW alloys have been studied to determine the best performing material. While RhW electrodes typically have power densities somewhat lower than PtW electrodes, PtW performance is strongly influenced by the Pt/W ratio. The best performing Pt/W ratio is about 3.4. RhW electrodes sinter more slowly than PtW and are predicted to have operating lifetimes up to 40 years; PtW electrodes are predicted to have lifetimes up to 7 years. Interaction with the current collection network can significantly decrease lifetime by inducing metal migration and segregation and by accelerating the sintering rate.

  17. Neural network setpoint control of an advanced test reactor experiment loop simulation

    SciTech Connect

    Cordes, G.A.; Bryan, S.R.; Powell, R.H.; Chick, D.R.

    1990-09-01

    This report describes the design, implementation, and application of artificial neural networks to achieve temperature and flow rate control for a simulation of a typical experiment loop in the Advanced Test Reactor (ATR) located at the Idaho National Engineering Laboratory (INEL). The goal of the project was to research multivariate, nonlinear control using neural networks. A loop simulation code was adapted for the project and used to create a training set and test the neural network controller for comparison with the existing loop controllers. The results for three neural network designs are documented and compared with existing loop controller action. The neural network was shown to be as accurate at loop control as the classical controllers in the operating region represented by the training set. 9 refs., 28 figs., 2 tabs.

  18. 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…

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

    NASA Astrophysics Data System (ADS)

    Cruz, Rene L.

    1991-01-01

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

  20. The Southeast Consortium for Advanced Network Technologies Education: 1997 to the Present. Jones County Junior College.

    ERIC Educational Resources Information Center

    Cotten, Catherine Perry

    The Southeast Consortium for Advanced Network Technologies Education (SCANTE) is a partnership between two-year colleges, four-year colleges and universities, middle/secondary schools, and the business community in Mississippi and elsewhere. SCANTE goals include: (1) to identify and evaluate trends, applications, innovations, and curricula in the…

  1. Unique Systems Analysis Task 7, Advanced Subsonic Technologies Evaluation Analysis

    NASA Technical Reports Server (NTRS)

    Eisenberg, Joseph D. (Technical Monitor); Bettner, J. L.; Stratton, S.

    2004-01-01

    To retain a preeminent U.S. position in the aircraft industry, aircraft passenger mile costs must be reduced while at the same time, meeting anticipated more stringent environmental regulations. A significant portion of these improvements will come from the propulsion system. A technology evaluation and system analysis was accomplished under this task, including areas such as aerodynamics and materials and improved methods for obtaining low noise and emissions. Previous subsonic evaluation analyses have identified key technologies in selected components for propulsion systems for year 2015 and beyond. Based on the current economic and competitive environment, it is clear that studies with nearer turn focus that have a direct impact on the propulsion industry s next generation product are required. This study will emphasize the year 2005 entry into service time period. The objective of this study was to determine which technologies and materials offer the greatest opportunities for improving propulsion systems. The goals are twofold. The first goal is to determine an acceptable compromise between the thermodynamic operating conditions for A) best performance, and B) acceptable noise and chemical emissions. The second goal is the evaluation of performance, weight and cost of advanced materials and concepts on the direct operating cost of an advanced regional transport of comparable technology level.

  2. 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).

  3. 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.

  4. Network Enrichment Analysis in Complex Experiments*

    PubMed Central

    Shojaie, Ali; Michailidis, George

    2010-01-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-02-01

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

  7. Exploratory Analysis of Biological Networks through Visualization, Clustering, and Functional Annotation in Cytoscape.

    PubMed

    Baryshnikova, Anastasia

    2016-01-01

    Biological networks define how genes, proteins, and other cellular components interact with one another to carry out specific functions, providing a scaffold for understanding cellular organization. Although in-depth network analysis requires advanced mathematical and computational knowledge, a preliminary visual exploration of biological networks is accessible to anyone with basic computer skills. Visualization of biological networks is used primarily to examine network topology, identify functional modules, and predict gene functions based on gene connectivity within the network. Networks are excellent at providing a bird's-eye view of data sets and have the power of illustrating complex ideas in simple and intuitive terms. In addition, they enable exploratory analysis and generation of new hypotheses, which can then be tested using rigorous statistical and experimental tools. This protocol describes a simple procedure for visualizing a biological network using the genetic interaction similarity network for Saccharomyces cerevisiae as an example. The visualization procedure described here relies on the open-source network visualization software Cytoscape and includes detailed instructions on formatting and loading the data, clustering networks, and overlaying functional annotations. PMID:26988373

  8. Pathway and Network Analysis in Proteomics

    PubMed Central

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

    2014-01-01

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

  9. 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.

  10. Network-based modular latent structure analysis

    PubMed Central

    2014-01-01

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

  11. Pathway and network analysis in proteomics.

    PubMed

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

    2014-12-01

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

  12. The Tuition Advance Fund: An Analysis Prepared for Boston University.

    ERIC Educational Resources Information Center

    Botsford, Keith

    Three models for anlayzing the Tuition Advance Fund (TAF) are examined. The three models are: projections by the Institute for Demographic and Economic Studies (IDES), projections by Data Resources, Inc. (DRI), and the Tuition Advance Fund Simulation (TAFSIM) models from Boston University. Analysis of the TAF is based on enrollment, price, and…

  13. A Meta-Analysis of Advance-Organizer Studies.

    ERIC Educational Resources Information Center

    Stone, Carol Leth

    Long term studies of advance organizers (AO) were analyzed with Glass's meta-analysis technique. AO's were defined as bridges from reader's previous knowledge to what is to be learned. The results were compared with predictions from Ausubel's model of assimilative learning. The results of the study indicated that advance organizers were associated…

  14. Advanced Fingerprint Analysis Project Fingerprint Constituents

    SciTech Connect

    GM Mong; CE Petersen; TRW Clauss

    1999-10-29

    The work described in this report was focused on generating fundamental data on fingerprint components which will be used to develop advanced forensic techniques to enhance fluorescent detection, and visualization of latent fingerprints. Chemical components of sweat gland secretions are well documented in the medical literature and many chemical techniques are available to develop latent prints, but there have been no systematic forensic studies of fingerprint sweat components or of the chemical and physical changes these substances undergo over time.

  15. Advanced nuclear rocket engine mission analysis

    SciTech Connect

    Ramsthaler, J.; Farbman, G.; Sulmeisters, T.; Buden, D.; Harris, P.

    1987-12-01

    The use of a derivative of the NERVA engine developed from 1955 to 1973 was evluated for potential application to Air Force orbital transfer and maneuvering missions in the time period 1995 to 2020. The NERVA stge was found to have lower life cycle costs (LCC) than an advanced chemical stage for performing low earth orbit (LEO) to geosynchronous orbit (GEO0 missions at any level of activity greater than three missions per year. It had lower life cycle costs than a high performance nuclear electric engine at any level of LEO to GEO mission activity. An examination of all unmanned orbital transfer and maneuvering missions from the Space Transportation Architecture study (STAS 111-3) indicated a LCC advantage for the NERVA stage over the advanced chemical stage of fifteen million dollars. The cost advanced accured from both the orbital transfer and maneuvering missions. Parametric analyses showed that the specific impulse of the NERVA stage and the cost of delivering material to low earth orbit were the most significant factors in the LCC advantage over the chemical stage. Lower development costs and a higher thrust gave the NERVA engine an LCC advantage over the nuclear electric stage. An examination of technical data from the Rover/NERVA program indicated that development of the NERVA stage has a low technical risk, and the potential for high reliability and safe operation. The data indicated the NERVA engine had a great flexibility which would permit a single stage to perform all Air Force missions.

  16. Advanced Modeling, Simulation and Analysis (AMSA) Capability Roadmap Progress Review

    NASA Technical Reports Server (NTRS)

    Antonsson, Erik; Gombosi, Tamas

    2005-01-01

    Contents include the following: NASA capability roadmap activity. Advanced modeling, simulation, and analysis overview. Scientific modeling and simulation. Operations modeling. Multi-special sensing (UV-gamma). System integration. M and S Environments and Infrastructure.

  17. Using Social Network Analysis to Predict Early Collaboration within Health Advocacy Coalitions

    ERIC Educational Resources Information Center

    Honeycutt, Todd C.; Strong, Debra A.

    2012-01-01

    Within coalitions of consumer advocates formed to advance health insurance coverage expansions, engaging in united advocacy activities soon after formation might be an important precursor to attaining coalition effectiveness in shaping policy. In this article, the authors apply social network analysis (SNA) to examine how organizational…

  18. Sensitivity analysis of artificial neural network (ANN) brightness temperature predictions over snow-covered regions in North America using the Advanced Microwave Sounding Radiometer (AMSR-E) from 2002 to 2011

    NASA Astrophysics Data System (ADS)

    Xue, Y.; Forman, B. A.

    2013-12-01

    Snow is a significant contributor to the earth's hydrologic cycle, energy cycle, and climate system. Further, up to 80% of freshwater supply in the western United States originates as snow (and ice). Characterization of the mass of snow, or snow water equivalent (SWE), across regional and continental scales has commonly been conducted using satellite-based passive microwave (PMW) brightness temperatures (Tb) within a SWE retrieval algorithm. However, SWE retrievals often suffer from deficiencies related to deep snow, wet snow, snow evolution, snow aging, overlying vegetation, surface and internal ice lenses, depth hoar, and sub-grid scale lakes. As an alternative to SWE retrievals, this study explores the potential for using PMW Tb and machine learning within a data assimilation framework. An artificial neural network (ANN) is presented for eventual use as an observation operator to map the land surface model states into Tb space. This study explores the sensitivity of an ANN as a computationally efficient measurement model operator for the prediction of PMW Tb across North America. The analysis employs normalized sensitivity coefficients and a one-at-a-time approach such that each of the 11 different inputs could be examined separately in order to quantify the impact of perturbations to each input on the multi-frequency, multi-polarization Tb output from the ANN. Spatiotemporal variability in the Tb predictions across regional spatial scales and seasonal timescales is investigated from 2002 to 2011. Preliminary results suggest ANN-based Tb predictions are sensitive to certain snow states, such as SWE, snow density, and snow temperature in non-vegetated or sparsely vegetated regions. Further, sensitivity of ANN prediction of ΔTb=Tb, 18v*-Tb, 36v* to changes in SWE suggest the likelihood for success when the ANN is eventually implemented into a data assimilation framework. Despite the promise in these initial results, challenges remain at enhancing ANN sensitivity

  19. Feasibility of a Networked Air Traffic Infrastructure Validation Environment for Advanced NextGen Concepts

    NASA Technical Reports Server (NTRS)

    McCormack, Michael J.; Gibson, Alec K.; Dennis, Noah E.; Underwood, Matthew C.; Miller,Lana B.; Ballin, Mark G.

    2013-01-01

    Abstract-Next Generation Air Transportation System (NextGen) applications reliant upon aircraft data links such as Automatic Dependent Surveillance-Broadcast (ADS-B) offer a sweeping modernization of the National Airspace System (NAS), but the aviation stakeholder community has not yet established a positive business case for equipage and message content standards remain in flux. It is necessary to transition promising Air Traffic Management (ATM) Concepts of Operations (ConOps) from simulation environments to full-scale flight tests in order to validate user benefits and solidify message standards. However, flight tests are prohibitively expensive and message standards for Commercial-off-the-Shelf (COTS) systems cannot support many advanced ConOps. It is therefore proposed to simulate future aircraft surveillance and communications equipage and employ an existing commercial data link to exchange data during dedicated flight tests. This capability, referred to as the Networked Air Traffic Infrastructure Validation Environment (NATIVE), would emulate aircraft data links such as ADS-B using in-flight Internet and easily-installed test equipment. By utilizing low-cost equipment that is easy to install and certify for testing, advanced ATM ConOps can be validated, message content standards can be solidified, and new standards can be established through full-scale flight trials without necessary or expensive equipage or extensive flight test preparation. This paper presents results of a feasibility study of the NATIVE concept. To determine requirements, six NATIVE design configurations were developed for two NASA ConOps that rely on ADS-B. The performance characteristics of three existing in-flight Internet services were investigated to determine whether performance is adequate to support the concept. Next, a study of requisite hardware and software was conducted to examine whether and how the NATIVE concept might be realized. Finally, to determine a business case

  20. NetworkAnalyst for statistical, visual and network-based meta-analysis of gene expression data.

    PubMed

    Xia, Jianguo; Gill, Erin E; Hancock, Robert E W

    2015-06-01

    Meta-analysis of gene expression data sets is increasingly performed to help identify robust molecular signatures and to gain insights into underlying biological processes. The complicated nature of such analyses requires both advanced statistics and innovative visualization strategies to support efficient data comparison, interpretation and hypothesis generation. NetworkAnalyst (http://www.networkanalyst.ca) is a comprehensive web-based tool designed to allow bench researchers to perform various common and complex meta-analyses of gene expression data via an intuitive web interface. By coupling well-established statistical procedures with state-of-the-art data visualization techniques, NetworkAnalyst allows researchers to easily navigate large complex gene expression data sets to determine important features, patterns, functions and connections, thus leading to the generation of new biological hypotheses. This protocol provides a step-wise description of how to effectively use NetworkAnalyst to perform network analysis and visualization from gene lists; to perform meta-analysis on gene expression data while taking into account multiple metadata parameters; and, finally, to perform a meta-analysis of multiple gene expression data sets. NetworkAnalyst is designed to be accessible to biologists rather than to specialist bioinformaticians. The complete protocol can be executed in ∼1.5 h. Compared with other similar web-based tools, NetworkAnalyst offers a unique visual analytics experience that enables data analysis within the context of protein-protein interaction networks, heatmaps or chord diagrams. All of these analysis methods provide the user with supporting statistical and functional evidence. PMID:25950236

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

    PubMed Central

    2012-01-01

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

  2. Robustness analysis of biochemical network models.

    PubMed

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

    2006-05-01

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

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

    PubMed

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

    2014-12-01

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

  4. Artificial neural networks and Abelian harmonic analysis

    NASA Astrophysics Data System (ADS)

    Rodriguez, Domingo; Pertuz-Campo, Jairo

    1991-12-01

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

  5. 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

  6. Advanced surface design for logistics analysis

    NASA Astrophysics Data System (ADS)

    Brown, Tim R.; Hansen, Scott D.

    The development of anthropometric arm/hand and tool models and their manipulation in a large system model for maintenance simulation are discussed. The use of Advanced Surface Design and s-fig technology in anthropometrics, and three-dimensional graphics simulation tools, are found to achieve a good balance between model manipulation speed and model accuracy. The present second generation models are shown to be twice as fast to manipulate as the first generation b-surf models, to be easier to manipulate into various configurations, and to more closely approximate human contours.

  7. Advanced tracking systems design and analysis

    NASA Technical Reports Server (NTRS)

    Potash, R.; Floyd, L.; Jacobsen, A.; Cunningham, K.; Kapoor, A.; Kwadrat, C.; Radel, J.; Mccarthy, J.

    1989-01-01

    The results of an assessment of several types of high-accuracy tracking systems proposed to track the spacecraft in the National Aeronautics and Space Administration (NASA) Advanced Tracking and Data Relay Satellite System (ATDRSS) are summarized. Tracking systems based on the use of interferometry and ranging are investigated. For each system, the top-level system design and operations concept are provided. A comparative system assessment is presented in terms of orbit determination performance, ATDRSS impacts, life-cycle cost, and technological risk.

  8. Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan; Heitzig, Jobst; Beronov, Boyan; Wiedermann, Marc; Runge, Jakob; Feng, Qing Yi; Tupikina, Liubov; Stolbova, Veronika; Donner, Reik; Marwan, Norbert; Dijkstra, Henk; Kurths, Jürgen

    2016-04-01

    We introduce the pyunicorn (Pythonic unified complex network and recurrence analysis toolbox) open source software package for applying and combining modern methods of data analysis and modeling from complex network theory and nonlinear time series analysis. pyunicorn is a fully object-oriented and easily parallelizable package written in the language Python. It allows for the construction of functional networks such as climate networks in climatology or functional brain networks in neuroscience representing the structure of statistical interrelationships in large data sets of time series and, subsequently, investigating this structure using advanced methods of complex network theory such as measures and models for spatial networks, networks of interacting networks, node-weighted statistics, or network surrogates. Additionally, pyunicorn provides insights into the nonlinear dynamics of complex systems as recorded in uni- and multivariate time series from a non-traditional perspective by means of recurrence quantification analysis, recurrence networks, visibility graphs, and construction of surrogate time series. The range of possible applications of the library is outlined, drawing on several examples mainly from the field of climatology. pyunicorn is available online at https://github.com/pik-copan/pyunicorn. Reference: J.F. Donges, J. Heitzig, B. Beronov, M. Wiedermann, J. Runge, Q.-Y. Feng, L. Tupikina, V. Stolbova, R.V. Donner, N. Marwan, H.A. Dijkstra, and J. Kurths, Unified functional network and nonlinear time series analysis for complex systems science: The pyunicorn package, Chaos 25, 113101 (2015), DOI: 10.1063/1.4934554, Preprint: arxiv.org:1507.01571 [physics.data-an].

  9. An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives

    PubMed Central

    Moreland-Russell, Sarah; Carothers, Bobbi J.

    2015-01-01

    This study examines smokefree policy networks in two cities—Kansas City and St. Louis, Missouri—one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers. PMID:26371022

  10. An Examination of Two Policy Networks Involved in Advancing Smokefree Policy Initiatives.

    PubMed

    Moreland-Russell, Sarah; Carothers, Bobbi J

    2015-09-01

    This study examines smokefree policy networks in two cities—Kansas City and St. Louis, Missouri—one that was successful in achieving widespread policy success, and one that was not. Descriptive social network analyses and visual network mapping were used to compare importance and contact relationships among actors involved in the smokefree policy initiatives. In Kansas City, where policy adoption was achieved, there was a higher level of connectivity among members, with network members being in contact with an average of more than five people, compared to just over two people for the St. Louis network. For both cities, despite being recognized as important, politicians were in contact with the fewest number of people. Results highlight the critical need to actively engage a variety of stakeholders when attempting city wide public health policy change. As evident by the success in smokefree policy adoption throughout Kansas City compared to St. Louis, closer linkages and continued communication among stakeholders including the media, coalitions, public health agencies, policymakers, and other partners are essential if we are to advance and broaden the impact of public health policy. Results indicate that the presence of champions, or those that play leadership roles in actively promoting policy by linking individuals and organizations, play an important role in advancing public health policy. Those working in public health should examine their level of engagement with the policy process and implement strategies for improving that engagement through relationship building and ongoing interactions with a variety of stakeholders, including policymakers. PMID:26371022

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

    PubMed Central

    Ma'ayan, A.

    2009-01-01

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

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

    PubMed

    Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie

    2015-06-01

    End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital. PMID:24644162

  13. Underwater acoustic wireless sensor networks: advances and future trends in physical, MAC and routing layers.

    PubMed

    Climent, Salvador; Sanchez, Antonio; Capella, Juan Vicente; Meratnia, Nirvana; Serrano, Juan Jose

    2014-01-01

    This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols. PMID:24399155

  14. Underwater Acoustic Wireless Sensor Networks: Advances and Future Trends in Physical, MAC and Routing Layers

    PubMed Central

    Climent, Salvador; Sanchez, Antonio; Capella, Juan Vicente; Meratnia, Nirvana; Serrano, Juan Jose

    2014-01-01

    This survey aims to provide a comprehensive overview of the current research on underwater wireless sensor networks, focusing on the lower layers of the communication stack, and envisions future trends and challenges. It analyzes the current state-of-the-art on the physical, medium access control and routing layers. It summarizes their security threads and surveys the currently proposed studies. Current envisioned niches for further advances in underwater networks research range from efficient, low-power algorithms and modulations to intelligent, energy-aware routing and medium access control protocols. PMID:24399155

  15. Advanced Learning Technologies and Learning Networks and Their Impact on Future Aerospace Workforce

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    This document contains the proceedings of the training workshop on Advanced Learning Technologies and Learning Networks and their impact on Future Aerospace Workforce. The workshop was held at the Peninsula Workforce Development Center, Hampton, Virginia, April 2 3, 2003. The workshop was jointly sponsored by Old Dominion University and NASA. Workshop attendees came from NASA, other government agencies, industry, and universities. The objectives of the workshop were to: 1) provide broad overviews of the diverse activities related to advanced learning technologies and learning environments, and 2) identify future directions for research that have high potential for aerospace workforce development. Eighteen half-hour overviewtype presentations were made at the workshop.

  16. Multistage neural network model for dynamic scene analysis

    SciTech Connect

    Ajjimarangsee, P.

    1989-01-01

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

  17. Recent Advances in Anthocyanin Analysis and Characterization

    PubMed Central

    Welch, Cara R.; Wu, Qingli; Simon, James E.

    2009-01-01

    Anthocyanins are a class of polyphenols responsible for the orange, red, purple and blue colors of many fruits, vegetables, grains, flowers and other plants. Consumption of anthocyanins has been linked as protective agents against many chronic diseases and possesses strong antioxidant properties leading to a variety of health benefits. In this review, we examine the advances in the chemical profiling of natural anthocyanins in plant and biological matrices using various chromatographic separations (HPLC and CE) coupled with different detection systems (UV, MS and NMR). An overview of anthocyanin chemistry, prevalence in plants, biosynthesis and metabolism, bioactivities and health properties, sample preparation and phytochemical investigations are discussed while the major focus examines the comparative advantages and disadvantages of each analytical technique. PMID:19946465

  18. Using Social Network Analysis for Spam Detection

    NASA Astrophysics Data System (ADS)

    Debarr, Dave; Wechsler, Harry

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

  19. 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)…

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

    PubMed

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

    2014-07-01

    Biological network analysis is a powerful approach to gain systems-level understanding of patterns of gene expression in different cell types, disease states and other biological/experimental conditions. Three consecutive steps are required--identification of genes or proteins of interest, network construction and network analysis and visualization. To date, researchers have to learn to use a combination of several tools to accomplish this task. In addition, interactive visualization of large networks has been primarily restricted to locally installed programs. To address these challenges, we have developed NetworkAnalyst, taking advantage of state-of-the-art web technologies, to enable high performance network analysis with rich user experience. NetworkAnalyst integrates all three steps and presents the results via a powerful online network visualization framework. Users can upload gene or protein lists, single or multiple gene expression datasets to perform comprehensive gene annotation and differential expression analysis. Significant genes are mapped to our manually curated protein-protein interaction database to construct relevant networks. The results are presented through standard web browsers for network analysis and interactive exploration. NetworkAnalyst supports common functions for network topology and module analyses. Users can easily search, zoom and highlight nodes or modules, as well as perform functional enrichment analysis on these selections. The networks can be customized with different layouts, colors or node sizes, and exported as PNG, PDF or GraphML files. Comprehensive FAQs, tutorials and context-based tips and instructions are provided. NetworkAnalyst currently supports protein-protein interaction network analysis for human and mouse and is freely available at http://www.networkanalyst.ca. PMID:24861621

  1. 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

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

    PubMed Central

    Wiggins, Benjamin L.; Goodreau, Steven M.

    2014-01-01

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

  3. 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.

  4. Analysis of an advanced technology subsonic turbofan incorporating revolutionary materials

    NASA Technical Reports Server (NTRS)

    Knip, Gerald, Jr.

    1987-01-01

    Successful implementation of revolutionary composite materials in an advanced turbofan offers the possibility of further improvements in engine performance and thrust-to-weight ratio relative to current metallic materials. The present analysis determines the approximate engine cycle and configuration for an early 21st century subsonic turbofan incorporating all composite materials. The advanced engine is evaluated relative to a current technology baseline engine in terms of its potential fuel savings for an intercontinental quadjet having a design range of 5500 nmi and a payload of 500 passengers. The resultant near optimum, uncooled, two-spool, advanced engine has an overall pressure ratio of 87, a bypass ratio of 18, a geared fan, and a turbine rotor inlet temperature of 3085 R. Improvements result in a 33-percent fuel saving for the specified misssion. Various advanced composite materials are used throughout the engine. For example, advanced polymer composite materials are used for the fan and the low pressure compressor (LPC).

  5. 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

  6. A flexible state-space approach for the modeling of metabolic networks II: advanced interrogation of hybridoma metabolism.

    PubMed

    Baughman, Adam C; Sharfstein, Susan T; Martin, Lealon L

    2011-03-01

    Having previously introduced the mathematical framework of topological metabolic analysis (TMA) - a novel optimization-based technique for modeling metabolic networks of arbitrary size and complexity - we demonstrate how TMA facilitates unique methods of metabolic interrogation. With the aid of several hybridoma metabolic investigations as case-studies (Bonarius et al., 1995, 1996, 2001), we first establish that the TMA framework identifies biologically important aspects of the metabolic network under investigation. We also show that the use of a structured weighting approach within our objective provides a substantial modeling benefit over an unstructured, uniform, weighting approach. We then illustrate the strength of TAM as an advanced interrogation technique, first by using TMA to prove the existence of (and to quantitatively describe) multiple topologically distinct configurations of a metabolic network that each optimally model a given set of experimental observations. We further show that such alternate topologies are indistinguishable using existing stoichiometric modeling techniques, and we explain the biological significance of the topological variables appearing within our model. By leveraging the manner in which TMA implements metabolite inputs and outputs, we also show that metabolites whose possible metabolic fates are inadequately described by a given network reconstruction can be quickly identified. Lastly, we show how the use of the TMA aggregate objective function (AOF) permits the identification of modeling solutions that can simultaneously consider experimental observations, underlying biological motivations, or even purely engineering- or design-based goals. PMID:21163360

  7. Analysis of quantum network coding for realistic repeater networks

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  8. Multiple quantitative trait analysis using bayesian networks.

    PubMed

    Scutari, Marco; Howell, Phil; Balding, David J; Mackay, Ian

    2014-09-01

    Models for genome-wide prediction and association studies usually target a single phenotypic trait. However, in animal and plant genetics it is common to record information on multiple phenotypes for each individual that will be genotyped. Modeling traits individually disregards the fact that they are most likely associated due to pleiotropy and shared biological basis, thus providing only a partial, confounded view of genetic effects and phenotypic interactions. In this article we use data from a Multiparent Advanced Generation Inter-Cross (MAGIC) winter wheat population to explore Bayesian networks as a convenient and interpretable framework for the simultaneous modeling of multiple quantitative traits. We show that they are equivalent to multivariate genetic best linear unbiased prediction (GBLUP) and that they are competitive with single-trait elastic net and single-trait GBLUP in predictive performance. Finally, we discuss their relationship with other additive-effects models and their advantages in inference and interpretation. MAGIC populations provide an ideal setting for this kind of investigation because the very low population structure and large sample size result in predictive models with good power and limited confounding due to relatedness. PMID:25236454

  9. Advanced reliability method for fatigue analysis

    NASA Technical Reports Server (NTRS)

    Wu, Y.-T.; Wirsching, P. H.

    1984-01-01

    When design factors are considered as random variables and the failure condition cannot be expressed by a closed form algebraic inequality, computations of risk (or probability of failure) may become extremely difficult or very inefficient. This study suggests using a simple and easily constructed second degree polynomial to approximate the complicated limit state in the neighborhood of the design point; a computer analysis relates the design variables at selected points. Then a fast probability integration technique (i.e., the Rackwitz-Fiessler algorithm) can be used to estimate risk. The capability of the proposed method is demonstrated in an example of a low cycle fatigue problem for which a computer analysis is required to perform local strain analysis to relate the design variables. A comparison of the performance of this method is made with a far more costly Monte Carlo solution. Agreement of the proposed method with Monte Carlo is considered to be good.

  10. 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.

  11. 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.

  12. 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.

  13. Modeling and analysis of advanced binary cycles

    SciTech Connect

    Gawlik, K.

    1997-12-31

    A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.

  14. 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.

  15. 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

  16. Quantitative methods for ecological network analysis.

    PubMed

    Ulanowicz, Robert E

    2004-12-01

    The analysis of networks of ecological trophic transfers is a useful complement to simulation modeling in the quest for understanding whole-ecosystem dynamics. Trophic networks can be studied in quantitative and systematic fashion at several levels. Indirect relationships between any two individual taxa in an ecosystem, which often differ in either nature or magnitude from their direct influences, can be assayed using techniques from linear algebra. The same mathematics can also be employed to ascertain where along the trophic continuum any individual taxon is operating, or to map the web of connections into a virtual linear chain that summarizes trophodynamic performance by the system. Backtracking algorithms with pruning have been written which identify pathways for the recycle of materials and energy within the system. The pattern of such cycling often reveals modes of control or types of functions exhibited by various groups of taxa. The performance of the system as a whole at processing material and energy can be quantified using information theory. In particular, the complexity of process interactions can be parsed into separate terms that distinguish organized, efficient performance from the capacity for further development and recovery from disturbance. Finally, the sensitivities of the information-theoretic system indices appear to identify the dynamical bottlenecks in ecosystem functioning. PMID:15556474

  17. 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…

  18. 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…

  19. 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.

  20. Progress in Advanced Spectral Analysis of Radioxenon

    SciTech Connect

    Haas, Derek A.; Schrom, Brian T.; Cooper, Matthew W.; Ely, James H.; Flory, Adam E.; Hayes, James C.; Heimbigner, Tom R.; McIntyre, Justin I.; Saunders, Danielle L.; Suckow, Thomas J.

    2010-09-21

    Improvements to a Java based software package developed at Pacific Northwest National Laboratory (PNNL) for display and analysis of radioxenon spectra acquired by the International Monitoring System (IMS) are described here. The current version of the Radioxenon JavaViewer implements the region of interest (ROI) method for analysis of beta-gamma coincidence data. Upgrades to the Radioxenon JavaViewer will include routines to analyze high-purity germanium detector (HPGe) data, Standard Spectrum Method to analyze beta-gamma coincidence data and calibration routines to characterize beta-gamma coincidence detectors. These upgrades are currently under development; the status and initial results will be presented. Implementation of these routines into the JavaViewer and subsequent release is planned for FY 2011-2012.

  1. Recent advances in statistical energy analysis

    NASA Technical Reports Server (NTRS)

    Heron, K. H.

    1992-01-01

    Statistical Energy Analysis (SEA) has traditionally been developed using modal summation and averaging approach, and has led to the need for many restrictive SEA assumptions. The assumption of 'weak coupling' is particularly unacceptable when attempts are made to apply SEA to structural coupling. It is now believed that this assumption is more a function of the modal formulation rather than a necessary formulation of SEA. The present analysis ignores this restriction and describes a wave approach to the calculation of plate-plate coupling loss factors. Predictions based on this method are compared with results obtained from experiments using point excitation on one side of an irregular six-sided box structure. Conclusions show that the use and calculation of infinite transmission coefficients is the way forward for the development of a purely predictive SEA code.

  2. Advancing Usability Evaluation through Human Reliability Analysis

    SciTech Connect

    Ronald L. Boring; David I. Gertman

    2005-07-01

    This paper introduces a novel augmentation to the current heuristic usability evaluation methodology. The SPAR-H human reliability analysis method was developed for categorizing human performance in nuclear power plants. Despite the specialized use of SPAR-H for safety critical scenarios, the method also holds promise for use in commercial off-the-shelf software usability evaluations. The SPAR-H method shares task analysis underpinnings with human-computer interaction, and it can be easily adapted to incorporate usability heuristics as performance shaping factors. By assigning probabilistic modifiers to heuristics, it is possible to arrive at the usability error probability (UEP). This UEP is not a literal probability of error but nonetheless provides a quantitative basis to heuristic evaluation. When combined with a consequence matrix for usability errors, this method affords ready prioritization of usability issues.

  3. Advanced Techniques for Root Cause Analysis

    Energy Science and Technology Software Center (ESTSC)

    2000-09-19

    Five items make up this package, or can be used individually. The Chronological Safety Management Template utilizes a linear adaptation of the Integrated Safety Management System laid out in the form of a template that greatly enhances the ability of the analyst to perform the first step of any investigation which is to gather all pertinent facts and identify causal factors. The Problem Analysis Tree is a simple three (3) level problem analysis tree whichmore » is easier for organizations outside of WSRC to use. Another part is the Systemic Root Cause Tree. One of the most basic and unique features of Expanded Root Cause Analysis is the Systemic Root Cause portion of the Expanded Root Cause Pyramid. The Systemic Root Causes are even more basic than the Programmatic Root Causes and represent Root Causes that cut across multiple (if not all) programs in an organization. the Systemic Root Cause portion contains 51 causes embedded at the bottom level of a three level Systemic Root Cause Tree that is divided into logical, organizationally based categorie to assist the analyst. The Computer Aided Root Cause Analysis that allows the analyst at each level of the Pyramid to a) obtain a brief description of the cause that is being considered, b) record a decision that the item is applicable, c) proceed to the next level of the Pyramid to see only those items at the next level of the tree that are relevant to the particular cause that has been chosen, and d) at the end of the process automatically print out a summary report of the incident, the causal factors as they relate to the safety management system, the probable causes, apparent causes, Programmatic Root Causes and Systemic Root Causes for each causal factor and the associated corrective action.« less

  4. Advanced CMOS Radiation Effects Testing Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, Jonathan Allen; Marshall, Paul W.; Rodbell, Kenneth P.; Gordon, Michael S.; LaBel, Kenneth A.; Schwank, James R.; Dodds, Nathaniel A.; Castaneda, Carlos M.; Berg, Melanie D.; Kim, Hak S.; Phan, Anthony M.; Seidleck, Christina M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  5. Advanced CMOS Radiation Effects Testing and Analysis

    NASA Technical Reports Server (NTRS)

    Pellish, J. A.; Marshall, P. W.; Rodbell, K. P.; Gordon, M. S.; LaBel, K. A.; Schwank, J. R.; Dodds, N. A.; Castaneda, C. M.; Berg, M. D.; Kim, H. S.; Phan, A. M.; Seidleck, C. M.

    2014-01-01

    Presentation at the annual NASA Electronic Parts and Packaging (NEPP) Program Electronic Technology Workshop (ETW). The material includes an update of progress in this NEPP task area over the past year, which includes testing, evaluation, and analysis of radiation effects data on the IBM 32 nm silicon-on-insulator (SOI) complementary metal oxide semiconductor (CMOS) process. The testing was conducted using test vehicles supplied by directly by IBM.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. LambdaStation: Exploiting Advance Networks In Data Intensive High Energy Physics Applications

    SciTech Connect

    Harvey B. Newman

    2009-09-11

    Lambda Station software implements selective, dynamic, secure path control between local storage & analysis facilities, and high bandwidth, wide-area networks (WANs). It is intended to facilitate use of desirable, alternate wide area network paths which may only be intermittently available, or subject to policies that restrict usage to specified traffic. Lambda Station clients gain awareness of potential alternate network paths via Clarens-based web services, including path characteristics such as bandwidth and availability. If alternate path setup is requested and granted, Lambda Station will configure the local network infrastructure to properly forward designated data flows via the alternate path. A fully functional implementation of Lambda Station, capable of dynamic alternate WAN path setup and teardown, has been successfully developed. A limited Lambda Station-awareness capability within the Storage Resource Manager (SRM) product has been developed. Lambda Station has been successfully tested in a number of venues, including Super Computing 2008. LambdaStation software, developed by the Fermilab team, enables dynamic allocation of alternate network paths for high impact traffic and to forward designated flows across LAN. It negotiates with reservation and provisioning systems of WAN control planes, be it based on SONET channels, demand tunnels, or dynamic circuit networks. It creates End-To-End circuit between single hosts, computer farms or networks with predictable performance characteristics, preserving QoS if supported in LAN and WAN and tied security policy allowing only specific traffic to be forwarded or received through created path. Lambda Station project also explores Network Awareness capabilities.

  12. Associated neural network independent component analysis structure

    NASA Astrophysics Data System (ADS)

    Kim, Keehoon; Kostrzweski, Andrew

    2006-05-01

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

  13. 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."

  14. Advances in Analysis of Longitudinal Data

    PubMed Central

    Gibbons, Robert D.; Hedeker, Donald; DuToit, Stephen

    2010-01-01

    In this review, we explore recent developments in the area of linear and nonlinear generalized mixed-effects regression models and various alternatives, including generalized estimating equations for analysis of longitudinal data. Methods are described for continuous and normally distributed as well as categorical (binary, ordinal, nominal) and count (Poisson) variables. Extensions of the model to three and four levels of clustering, multivariate outcomes, and incorporation of design weights are also described. Linear and nonlinear models are illustrated using an example involving a study of the relationship between mood and smoking. PMID:20192796

  15. 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).

  16. Advanced Orion Optimized Laser System Analysis

    NASA Technical Reports Server (NTRS)

    1996-01-01

    Contractor shall perform a complete analysis of the potential of the solid state laser in the very long pulse mode (100 ns pulse width, 10-30 hz rep-rate) and in the very short pulse mode (100 ps pulse width 10-30 hz rep rate) concentrating on the operation of the device in the 'hot-rod' mode, where no active cooling the laser operation is attempted. Contractor's calculations shall be made of the phase aberrations which develop during the repped-pulse train, and the results shall feed into the adaptive optics analyses. The contractor shall devise solutions to work around ORION track issues. A final report shall be furnished to the MSFC COTR including all calculations and analysis of estimates of bulk phase and intensity aberration distribution in the laser output beam as a function of time during the repped-pulse train for both wave forms (high-energy/long-pulse, as well as low-energy/short-pulse). Recommendations shall be made for mitigating the aberrations by laser re-design and/or changes in operating parameters of optical pump sources and/or designs.

  17. Analysis of epileptic seizures with complex network.

    PubMed

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

    2014-01-01

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

  18. Basic parameter estimation of binary neutron star systems by the advanced LIGO/Vigro network

    SciTech Connect

    Rodriguez, Carl L.; Farr, Benjamin; Raymond, Vivien; Farr, Will M.; Littenberg, Tyson B.; Fazi, Diego; Kalogera, Vicky

    2014-04-01

    Within the next five years, it is expected that the Advanced LIGO/Virgo network will have reached a sensitivity sufficient to enable the routine detection of gravitational waves. Beyond the initial detection, the scientific promise of these instruments relies on the effectiveness of our physical parameter estimation capabilities. A major part of this effort has been toward the detection and characterization of gravitational waves from compact binary coalescence, e.g., the coalescence of binary neutron stars. While several previous studies have investigated the accuracy of parameter estimation with advanced detectors, the majority have relied on approximation techniques such as the Fisher Matrix which are insensitive to the non-Gaussian nature of the gravitational wave posterior distribution function. Here we report average statistical uncertainties that will be achievable for strong detection candidates (S/N = 20) over a comprehensive sample of source parameters. We use the Markov Chain Monte Carlo based parameter estimation software developed by the LIGO/Virgo Collaboration with the goal of updating the previously quoted Fisher Matrix bounds. We find the recovery of the individual masses to be fractionally within 9% (15%) at the 68% (95%) credible intervals for equal-mass systems, and within 1.9% (3.7%) for unequal-mass systems. We also find that the Advanced LIGO/Virgo network will constrain the locations of binary neutron star mergers to a median uncertainty of 5.1 deg{sup 2} (13.5 deg{sup 2}) on the sky. This region is improved to 2.3 deg{sup 2} (6 deg{sup 2}) with the addition of the proposed LIGO India detector to the network. We also report the average uncertainties on the luminosity distances and orbital inclinations of strong detections that can be achieved by different network configurations.

  19. CoIN: a network analysis for document triage.

    PubMed

    Hsu, Yi-Yu; Kao, Hung-Yu

    2013-01-01

    In recent years, there was a rapid increase in the number of medical articles. The number of articles in PubMed has increased exponentially. Thus, the workload for biocurators has also increased exponentially. Under these circumstances, a system that can automatically determine in advance which article has a higher priority for curation can effectively reduce the workload of biocurators. Determining how to effectively find the articles required by biocurators has become an important task. In the triage task of BioCreative 2012, we proposed the Co-occurrence Interaction Nexus (CoIN) for learning and exploring relations in articles. We constructed a co-occurrence analysis system, which is applicable to PubMed articles and suitable for gene, chemical and disease queries. CoIN uses co-occurrence features and their network centralities to assess the influence of curatable articles from the Comparative Toxicogenomics Database. The experimental results show that our network-based approach combined with co-occurrence features can effectively classify curatable and non-curatable articles. CoIN also allows biocurators to survey the ranking lists for specific queries without reviewing meaningless information. At BioCreative 2012, CoIN achieved a 0.778 mean average precision in the triage task, thus finishing in second place out of all participants. Database URL: http://ikmbio.csie.ncku.edu.tw/coin/home.php. PMID:24218542

  20. Advanced Communication Technology Satellite (ACTS) Very Small Aperture Terminal (VSAT) Network Control Performance

    NASA Technical Reports Server (NTRS)

    Coney, T. A.

    1996-01-01

    This paper discusses the performance of the network control function for the Advanced Communications Technology Satellite (ACTS) very small aperture terminal (VSAT) full mesh network. This includes control of all operational activities such as acquisition, synchronization, timing and rain fade compensation as well as control of all communications activities such as on-demand integrated services (voice, video, and date) connects and disconnects Operations control is provided by an in-band orderwire carried in the baseboard processor (BBP) control burst, the orderwire burst, the reference burst, and the uplink traffic burst. Communication services are provided by demand assigned multiple access (DAMA) protocols. The ACTS implementation of DAMA protocols ensures both on-demand and integrated voice, video and data services. Communications services control is also provided by the in-band orderwire but uses only the reference burst and the uplink traffic burst. The performance of the ACTS network control functions have been successfully tested during on-orbit checkout and in various VSAT networks in day to day operations. This paper discusses the network operations and services control performance.

  1. Value analysis for advanced technology products

    NASA Astrophysics Data System (ADS)

    Soulliere, Mark

    2011-03-01

    Technology by itself can be wondrous, but buyers of technology factor in the price they have to pay along with performance in their decisions. As a result, the ``best'' technology may not always win in the marketplace when ``good enough'' can be had at a lower price. Technology vendors often set pricing by ``cost plus margin,'' or by competitors' offerings. What if the product is new (or has yet to be invented)? Value pricing is a methodology to price products based on the value generated (e.g. money saved) by using one product vs. the next best technical alternative. Value analysis can often clarify what product attributes generate the most value. It can also assist in identifying market forces outside of the control of the technology vendor that also influence pricing. These principles are illustrated with examples.

  2. Advanced stability analysis for laminar flow control

    NASA Technical Reports Server (NTRS)

    Orszag, S. A.

    1981-01-01

    Five classes of problems are addressed: (1) the extension of the SALLY stability analysis code to the full eighth order compressible stability equations for three dimensional boundary layer; (2) a comparison of methods for prediction of transition using SALLY for incompressible flows; (3) a study of instability and transition in rotating disk flows in which the effects of Coriolis forces and streamline curvature are included; (4) a new linear three dimensional instability mechanism that predicts Reynolds numbers for transition to turbulence in planar shear flows in good agreement with experiment; and (5) a study of the stability of finite amplitude disturbances in axisymmetric pipe flow showing the stability of this flow to all nonlinear axisymmetric disturbances.

  3. Performance analysis of advanced spacecraft TPS

    NASA Technical Reports Server (NTRS)

    Pitts, William C.

    1987-01-01

    The analysis on the feasibility for using metal hydrides in the thermal protection system of cryogenic tanks in space was based on the heat capacity of ice as the phase change material (PCM). It was found that with ice the thermal protection system weight could be reduced by, at most, about 20 percent over an all LI-900 insulation. For this concept to be viable, a metal hydride with considerably more capacity than water would be required. None were found. Special metal hydrides were developed for hydrogen fuel storage applications and it may be possible to do so for the current application. Until this appears promising further effort on this feasibility study does not seem warranted.

  4. 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

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

    PubMed

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

    2015-08-01

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

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

    NASA Astrophysics Data System (ADS)

    Nadarajah, Nishaanthan; Nirmalathas, Ampalavanapillai

    2008-03-01

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

  7. A New Approach in Advance Network Reservation and Provisioning for High-Performance Scientific Data Transfers

    SciTech Connect

    Balman, Mehmet; Chaniotakis, Evangelos; Shoshani, Arie; Sim, Alex

    2010-01-28

    Scientific applications already generate many terabytes and even petabytes of data from supercomputer runs and large-scale experiments. The need for transferring data chunks of ever-increasing sizes through the network shows no sign of abating. Hence, we need high-bandwidth high speed networks such as ESnet (Energy Sciences Network). Network reservation systems, i.e. ESnet's OSCARS (On-demand Secure Circuits and Advance Reservation System) establish guaranteed bandwidth of secure virtual circuits at a certain time, for a certain bandwidth and length of time. OSCARS checks network availability and capacity for the specified period of time, and allocates requested bandwidth for that user if it is available. If the requested reservation cannot be granted, no further suggestion is returned back to the user. Further, there is no possibility from the users view-point to make an optimal choice. We report a new algorithm, where the user specifies the total volume that needs to be transferred, a maximum bandwidth that he/she can use, and a desired time period within which the transfer should be done. The algorithm can find alternate allocation possibilities, including earliest time for completion, or shortest transfer duration - leaving the choice to the user. We present a novel approach for path finding in time-dependent networks, and a new polynomial algorithm to find possible reservation options according to given constraints. We have implemented our algorithm for testing and incorporation into a future version of ESnet?s OSCARS. Our approach provides a basis for provisioning end-to-end high performance data transfers over storage and network resources.

  8. Advanced analysis techniques for uranium assay

    SciTech Connect

    Geist, W. H.; Ensslin, Norbert; Carrillo, L. A.; Beard, C. A.

    2001-01-01

    Uranium has a negligible passive neutron emission rate making its assay practicable only with an active interrogation method. The active interrogation uses external neutron sources to induce fission events in the uranium in order to determine the mass. This technique requires careful calibration with standards that are representative of the items to be assayed. The samples to be measured are not always well represented by the available standards which often leads to large biases. A technique of active multiplicity counting is being developed to reduce some of these assay difficulties. Active multiplicity counting uses the measured doubles and triples count rates to determine the neutron multiplication (f4) and the product of the source-sample coupling ( C ) and the 235U mass (m). Since the 35U mass always appears in the multiplicity equations as the product of Cm, the coupling needs to be determined before the mass can be known. A relationship has been developed that relates the coupling to the neutron multiplication. The relationship is based on both an analytical derivation and also on empirical observations. To determine a scaling constant present in this relationship, known standards must be used. Evaluation of experimental data revealed an improvement over the traditional calibration curve analysis method of fitting the doubles count rate to the 235Um ass. Active multiplicity assay appears to relax the requirement that the calibration standards and unknown items have the same chemical form and geometry.

  9. Multispectral laser imaging for advanced food analysis

    NASA Astrophysics Data System (ADS)

    Senni, L.; Burrascano, P.; Ricci, M.

    2016-07-01

    A hardware-software apparatus for food inspection capable of realizing multispectral NIR laser imaging at four different wavelengths is herein discussed. The system was designed to operate in a through-transmission configuration to detect the presence of unwanted foreign bodies inside samples, whether packed or unpacked. A modified Lock-In technique was employed to counterbalance the significant signal intensity attenuation due to transmission across the sample and to extract the multispectral information more efficiently. The NIR laser wavelengths used to acquire the multispectral images can be varied to deal with different materials and to focus on specific aspects. In the present work the wavelengths were selected after a preliminary analysis to enhance the image contrast between foreign bodies and food in the sample, thus identifying the location and nature of the defects. Experimental results obtained from several specimens, with and without packaging, are presented and the multispectral image processing as well as the achievable spatial resolution of the system are discussed.

  10. Advances in carbonate exploration and reservoir analysis

    USGS Publications Warehouse

    Garland, J.; Neilson, J.; Laubach, S.E.; Whidden, Katherine J.

    2012-01-01

    The development of innovative techniques and concepts, and the emergence of new plays in carbonate rocks are creating a resurgence of oil and gas discoveries worldwide. The maturity of a basin and the application of exploration concepts have a fundamental influence on exploration strategies. Exploration success often occurs in underexplored basins by applying existing established geological concepts. This approach is commonly undertaken when new basins ‘open up’ owing to previous political upheavals. The strategy of using new techniques in a proven mature area is particularly appropriate when dealing with unconventional resources (heavy oil, bitumen, stranded gas), while the application of new play concepts (such as lacustrine carbonates) to new areas (i.e. ultra-deep South Atlantic basins) epitomizes frontier exploration. Many low-matrix-porosity hydrocarbon reservoirs are productive because permeability is controlled by fractures and faults. Understanding basic fracture properties is critical in reducing geological risk and therefore reducing well costs and increasing well recovery. The advent of resource plays in carbonate rocks, and the long-standing recognition of naturally fractured carbonate reservoirs means that new fracture and fault analysis and prediction techniques and concepts are essential.

  11. 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.

  12. Dynamic network analysis of protein interactions

    NASA Astrophysics Data System (ADS)

    Almaas, Eivind; Deri, Joya

    2007-03-01

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

  13. Multilayer Kohonen network and its separability analysis

    NASA Astrophysics Data System (ADS)

    Liu, Chao-yuan; Li, Jie-Gu

    1995-04-01

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

  14. Advanced computational tools for 3-D seismic analysis

    SciTech Connect

    Barhen, J.; Glover, C.W.; Protopopescu, V.A.

    1996-06-01

    The global objective of this effort is to develop advanced computational tools for 3-D seismic analysis, and test the products using a model dataset developed under the joint aegis of the United States` Society of Exploration Geophysicists (SEG) and the European Association of Exploration Geophysicists (EAEG). The goal is to enhance the value to the oil industry of the SEG/EAEG modeling project, carried out with US Department of Energy (DOE) funding in FY` 93-95. The primary objective of the ORNL Center for Engineering Systems Advanced Research (CESAR) is to spearhead the computational innovations techniques that would enable a revolutionary advance in 3-D seismic analysis. The CESAR effort is carried out in collaboration with world-class domain experts from leading universities, and in close coordination with other national laboratories and oil industry partners.

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

    NASA Astrophysics Data System (ADS)

    Ercan, Alper

    2016-03-01

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

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

    PubMed

    Farine, Damien R; Whitehead, Hal

    2015-09-01

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

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

    PubMed

    Pradhan, M; Provan, G; Henrion, M

    1994-01-01

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

  18. Network congestion analysis of gravity generated models

    NASA Astrophysics Data System (ADS)

    Maniadakis, Dimitris; Varoutas, Dimitris

    2014-07-01

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

  19. METHODS ADVANCEMENT FOR MILK ANALYSIS: THE MAMA STUDY

    EPA Science Inventory

    The Methods Advancement for Milk Analysis (MAMA) study was designed by US EPA and CDC investigators to provide data to support the technological and study design needs of the proposed National Children=s Study (NCS). The NCS is a multi-Agency-sponsored study, authorized under the...

  20. Polybrominated Diphenyl Ethers in Dryer Lint: An Advanced Analysis Laboratory

    ERIC Educational Resources Information Center

    Thompson, Robert Q.

    2008-01-01

    An advanced analytical chemistry laboratory experiment is described that involves environmental analysis and gas chromatography-mass spectrometry. Students analyze lint from clothes dryers for traces of flame retardant chemicals, polybrominated diphenylethers (PBDEs), compounds receiving much attention recently. In a typical experiment, ng/g…

  1. A Meta-Analysis of Advanced Organizer Studies.

    ERIC Educational Resources Information Center

    Stone, Carol Leth

    1983-01-01

    Twenty-nine reports yielding 112 studies were analyzed with Glass's meta-analysis technique, and results were compared with predictions from Ausubel's model of assimilative learning. Overall, advance organizers were shown to be associated with increased learning and retention of material to be learned. (Author)

  2. Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis

    ERIC Educational Resources Information Center

    Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.

    2006-01-01

    Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…

  3. NASTRAN documentation for flutter analysis of advanced turbopropellers

    NASA Technical Reports Server (NTRS)

    Elchuri, V.; Gallo, A. M.; Skalski, S. C.

    1982-01-01

    An existing capability developed to conduct modal flutter analysis of tuned bladed-shrouded discs was modified to facilitate investigation of the subsonic unstalled flutter characteristics of advanced turbopropellers. The modifications pertain to the inclusion of oscillatory modal aerodynamic loads of blades with large (backward and forward) varying sweep.

  4. Networked sensors for the future force (NSFF) advanced technology demonstration (ATD) communications systems

    NASA Astrophysics Data System (ADS)

    Nemeroff, Jay; DiPierro, Stefano

    2005-05-01

    The U.S. Army"s Future Combat Systems (FCS) and Future Force Warrior (FFW) will rely on the use of unattended, tactical sensors to detect and identify enemy targets in order to avoid enemy fires and enable precise networked fire to survive on the future battlefield with less armor protection. Successful implementation of these critical sensor fields requires the development of a specialized communications network infrastructure needed to disseminate sensor data to provide relevant, timely and accurate situational awareness information to the tactical common operating picture. The sensor network communications must support both static deployed and mobile ground and air robotic sensor arrays with robust, secure, stealthy, and jam resistant links. It is envisioned that tactical sensor networks can be deployed in a two tiered communications architecture that includes a lower sensor sub-layer consisting of acoustic, magnetic, Chemical/Biological and seismic detectors and an upper sub-layer consisting of infrared or visual imaging cameras. The upper sub-layer can be cued by the lower sub-layer and provides a seamless gateway link to higher echelon backbone tactical networks. The NSFF Advanced Technology Demonstration (ATD) communications effort focuses on providing Future Force systems such as the FCS and the Future Force Warrior with critical situational awareness data needed for survivability. The communications systems supporting this functionality must be designed such that unattended ground sensor data can flow seamlessly from the lowest unattended tactical sensor echelons into the Army"s tactical backbone networks while also allowing the "fusing" of the data with other intelligence information for correlation within a tactical command and control node. NSFF is realizing this capability by using advanced communications technologies developed under the Soldier Level Integrated Communications Environment (SLICE) Soldier Radio Waveform (SRW) project. These technologies

  5. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, T. H. H.

    1985-01-01

    Advanced stress analysis methods applicable to turbine engine structures are investigated. Constructions of special elements which containing traction-free circular boundaries are investigated. New versions of mixed variational principle and version of hybrid stress elements are formulated. A method is established for suppression of kinematic deformation modes. semiLoof plate and shell elements are constructed by assumed stress hybrid method. An elastic-plastic analysis is conducted by viscoplasticity theory using the mechanical subelement model.

  6. Recent Advances in Multidisciplinary Analysis and Optimization, part 3

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: aircraft design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  7. Recent Advances in Multidisciplinary Analysis and Optimization, part 1

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  8. Recent Advances in Multidisciplinary Analysis and Optimization, part 2

    NASA Technical Reports Server (NTRS)

    Barthelemy, Jean-Francois M. (Editor)

    1989-01-01

    This three-part document contains a collection of technical papers presented at the Second NASA/Air Force Symposium on Recent Advances in Multidisciplinary Analysis and Optimization, held September 28-30, 1988 in Hampton, Virginia. The topics covered include: helicopter design, aeroelastic tailoring, control of aeroelastic structures, dynamics and control of flexible structures, structural design, design of large engineering systems, application of artificial intelligence, shape optimization, software development and implementation, and sensitivity analysis.

  9. 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.

  10. Public transport networks: empirical analysis and modeling

    NASA Astrophysics Data System (ADS)

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

    2009-03-01

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

  11. Battery-free Wireless Sensor Network For Advanced Fossil-Fuel Based Power Generation

    SciTech Connect

    Yi Jia

    2011-02-28

    This report summarizes technical progress achieved during the project supported by the Department of Energy under Award Number DE-FG26-07NT4306. The aim of the project was to conduct basic research into battery-free wireless sensing mechanism in order to develop novel wireless sensors and sensor network for physical and chemical parameter monitoring in a harsh environment. Passive wireless sensing platform and five wireless sensors including temperature sensor, pressure sensor, humidity sensor, crack sensor and networked sensors developed and demonstrated in our laboratory setup have achieved the objective for the monitoring of various physical and chemical parameters in a harsh environment through remote power and wireless sensor communication, which is critical to intelligent control of advanced power generation system. This report is organized by the sensors developed as detailed in each progress report.

  12. Advanced computing

    NASA Technical Reports Server (NTRS)

    1991-01-01

    Advanced concepts in hardware, software and algorithms are being pursued for application in next generation space computers and for ground based analysis of space data. The research program focuses on massively parallel computation and neural networks, as well as optical processing and optical networking which are discussed under photonics. Also included are theoretical programs in neural and nonlinear science, and device development for magnetic and ferroelectric memories.

  13. 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.

  14. Analysis of IMS spectra using neural networks

    SciTech Connect

    Bell, S.E.

    1992-09-01

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

  15. Analysis of IMS spectra using neural networks

    SciTech Connect

    Bell, S.E.

    1992-01-01

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

  16. Ad Hoc Networks: Headline 2000 Communications Analysis

    NASA Astrophysics Data System (ADS)

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

    2002-06-01

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

  17. Resource Allocation and Power Management Schemes in an LTE-Advanced Femtocell Network

    NASA Astrophysics Data System (ADS)

    Lee, Byung-Bog; Yu, Jae-Hak; Lee, In-Hwan; Pyo, Cheol-Sig; Kim, Se-Jin

    In this letter, we introduce two different resource allocation and Tx power management schemes, called resource control and fixed power (RCFP) and fixed resource and power control (FRPC), in an LTE-Advanced femtocell network. We analyze and compare the two schemes in terms of the system throughput for downlink and energy consumption of home evolved NodeB (HeNB) Tx power according to the number of HeNBs and home user equipment (HUE)'s user traffic density (C). The simulation results show that the FRPC scheme has better performance in terms of system throughput for macro user equipments (MUEs) and energy consumption in low C.

  18. 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.

  19. The performance analysis of linux networking - packet receiving

    SciTech Connect

    Wu, Wenji; Crawford, Matt; Bowden, Mark; /Fermilab

    2006-11-01

    The computing models for High-Energy Physics experiments are becoming ever more globally distributed and grid-based, both for technical reasons (e.g., to place computational and data resources near each other and the demand) and for strategic reasons (e.g., to leverage equipment investments). To support such computing models, the network and end systems, computing and storage, face unprecedented challenges. One of the biggest challenges is to transfer scientific data sets--now in the multi-petabyte (10{sup 15} bytes) range and expected to grow to exabytes within a decade--reliably and efficiently among facilities and computation centers scattered around the world. Both the network and end systems should be able to provide the capabilities to support high bandwidth, sustained, end-to-end data transmission. Recent trends in technology are showing that although the raw transmission speeds used in networks are increasing rapidly, the rate of advancement of microprocessor technology has slowed down. Therefore, network protocol-processing overheads have risen sharply in comparison with the time spent in packet transmission, resulting in degraded throughput for networked applications. More and more, it is the network end system, instead of the network, that is responsible for degraded performance of network applications. In this paper, the Linux system's packet receive process is studied from NIC to application. We develop a mathematical model to characterize the Linux packet receiving process. Key factors that affect Linux systems network performance are analyzed.

  20. Isolation and analysis of ginseng: advances and challenges

    PubMed Central

    Wang, Chong-Zhi

    2011-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products in the world. Because of its complex constituents, multidisciplinary techniques are needed to validate the analytical methods that support ginseng’s use worldwide. In the past decade, rapid development of technology has advanced many aspects of ginseng research. The aim of this review is to illustrate the recent advances in the isolation and analysis of ginseng, and to highlight their new applications and challenges. Emphasis is placed on recent trends and emerging techniques. The current article reviews the literature between January 2000 and September 2010. PMID:21258738

  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 Central

    Stam, Cornelis J; Reijneveld, Jaap C

    2007-01-01

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

  3. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-08-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  4. Issues affecting advanced passive light-water reactor safety analysis

    SciTech Connect

    Beelman, R.J.; Fletcher, C.D.; Modro, S.M.

    1992-01-01

    Next generation commercial reactor designs emphasize enhanced safety through improved safety system reliability and performance by means of system simplification and reliance on immutable natural forces for system operation. Simulating the performance of these safety systems will be central to analytical safety evaluation of advanced passive reactor designs. Yet the characteristically small driving forces of these safety systems pose challenging computational problems to current thermal-hydraulic systems analysis codes. Additionally, the safety systems generally interact closely with one another, requiring accurate, integrated simulation of the nuclear steam supply system, engineered safeguards and containment. Furthermore, numerical safety analysis of these advanced passive reactor designs wig necessitate simulation of long-duration, slowly-developing transients compared with current reactor designs. The composite effects of small computational inaccuracies on induced system interactions and perturbations over long periods may well lead to predicted results which are significantly different than would otherwise be expected or might actually occur. Comparisons between the engineered safety features of competing US advanced light water reactor designs and analogous present day reactor designs are examined relative to the adequacy of existing thermal-hydraulic safety codes in predicting the mechanisms of passive safety. Areas where existing codes might require modification, extension or assessment relative to passive safety designs are identified. Conclusions concerning the applicability of these codes to advanced passive light water reactor safety analysis are presented.

  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. PMID:26529706

  6. 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

  7. Advanced Post-Irradiation Examination Capabilities Alternatives Analysis Report

    SciTech Connect

    Jeff Bryan; Bill Landman; Porter Hill

    2012-12-01

    An alternatives analysis was performed for the Advanced Post-Irradiation Capabilities (APIEC) project in accordance with the U.S. Department of Energy (DOE) Order DOE O 413.3B, “Program and Project Management for the Acquisition of Capital Assets”. The Alternatives Analysis considered six major alternatives: ? No Action ? Modify Existing DOE Facilities – capabilities distributed among multiple locations ? Modify Existing DOE Facilities – capabilities consolidated at a few locations ? Construct New Facility ? Commercial Partnership ? International Partnerships Based on the alternatives analysis documented herein, it is recommended to DOE that the advanced post-irradiation examination capabilities be provided by a new facility constructed at the Materials and Fuels Complex at the Idaho National Laboratory.

  8. Analysis of Photonic Networks for a Chip Multiprocessor Using Scientific Applications

    SciTech Connect

    Kamil, Shoaib A; Hendry, Gilbert; Biberman, Aleksandr; Chan, Johnnie; Lee, Benjamin G.; Mohiyuddin, Marghoob; Jain, Ankit; Bergman, Keren; Carloni, Luca; Kubiatowicz, John; Oliker, Leonid; Shalf, John

    2009-01-31

    As multiprocessors scale to unprecedented numbers of cores in order to sustain performance growth, it is vital that these gains are not nullified by high energy consumption from inter-core communication. With recent advances in 3D Integration CMOS technology, the possibility for realizing hybrid photonic-electronic networks-on-chip warrants investigating real application traces on functionally comparable photonic and electronic network designs. We present a comparative analysis using both synthetic benchmarks as well as real applications, run through detailed cycle accurate models implemented under the OMNeT++ discrete event simulation environment. Results show that when utilizing standard process-to-processor mapping methods, this hybrid network can achieve 75X improvement in energy efficiency for synthetic benchmarks and up to 37X improvement for real scientific applications, defined as network performance per energy spent, over an electronic mesh for large messages across a variety of communication patterns.

  9. The Lockheed Martin Network: An Intranet Analysis.

    ERIC Educational Resources Information Center

    Okey, Robert M.

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

  10. Longitudinal Network Analysis Using Multidimensional Scaling.

    ERIC Educational Resources Information Center

    Barnett, George A.; Palmer, Mark T.

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

  11. Comparative network analysis via differential graphlet communities

    PubMed Central

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

    2015-01-01

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

  12. 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.

  13. Facilitating career advancement for women in the Geosciences through the Earth Science Women's Network (ESWN)

    NASA Astrophysics Data System (ADS)

    Hastings, M. G.; Kontak, R.; Holloway, T.; Kogan, M.; Laursen, S. L.; Marin-Spiotta, E.; Steiner, A. L.; Wiedinmyer, C.

    2011-12-01

    The Earth Science Women's Network (ESWN) is a network of women geoscientists, many of who are in the early stages of their careers. The mission of ESWN is to promote career development, build community, provide informal mentoring and support, and facilitate professional collaborations, all towards making women successful in their scientific careers. ESWN currently connects over 1000 women across the globe, and includes graduate students, postdoctoral associates, faculty from a diversity of colleges and universities, program managers, and government, non-government and industry researchers. ESWN facilitates communication between its members via an email listserv and in-person networking events, and also provides resources to the broader community through the public Earth Science Jobs Listserv that hosts over 1800 subscribers. With funding from a NSF ADVANCE PAID grant, our primary goals include growing our membership to serve a wider section of the geosciences community, designing and administering career development workshops, promoting professional networking at major scientific conferences, and developing web resources to build connections, collaborations, and peer mentoring for and among women in the Earth Sciences. Recognizing that women in particular face a number of direct and indirect biases while navigating their careers, we aim to provide a range of opportunities for professional development that emphasize different skills at different stages of career. For example, ESWN-hosted mini-workshops at national scientific conferences have targeted skill building for early career researchers (e.g., postdocs, tenure-track faculty), with a recent focus on raising extramural research funding and best practices for publishing in the geosciences literature. More concentrated, multi-day professional development workshops are offered annually with varying themes such as Defining Your Research Identity and Building Leadership Skills for Success in Scientific Organizations

  14. Building a Governance Strategy for CER: The Patient Outcomes Research to Advance Learning (PORTAL) Network Experience

    PubMed Central

    Paolino, Andrea R.; McGlynn, Elizabeth A.; Lieu, Tracy; Nelson, Andrew F.; Prausnitz, Stephanie; Horberg, Michael A.; Arterburn, David E.; Gould, Michael K.; Laws, Reesa L.; Steiner, John F.

    2016-01-01

    Introduction: The Patient Outcomes Research to Advance Learning (PORTAL) Network was established with funding from the Patient-Centered Outcomes Research Institute (PCORI) in 2014. The PORTAL team adapted governance structures and processes from past research network collaborations. We will review and outline the structures and processes of the PORTAL governance approach and describe how proactively focusing on priority areas helped us to facilitate an ambitious research agenda. Background: For years a variety of funders have supported large-scale infrastructure grants to promote the use of clinical datasets to answer important comparative effectiveness research (CER) questions. These awards have provided the impetus for health care systems to join forces in creating clinical data research networks. Often, these scientific networks do not develop governance processes proactively or systematically, and address issues only as problems arise. Even if network leaders and collaborators foresee the need to develop governance approaches, they may underestimate the time and effort required to develop sound processes. The resulting delays can impede research progress. Innovation: Because the PORTAL sites had built trust and a foundation of collaboration by participating with one another in past research networks, essential elements of effective governance such as guiding principles, decision making processes, project governance, data governance, and stakeholders in governance were familiar to PORTAL investigators. This trust and familiarity enabled the network to rapidly prioritize areas that required sound governance approaches: responding to new research opportunities, creating a culture of trust and collaboration, conducting individual studies, within the broader network, assigning responsibility and credit to scientific investigators, sharing data while protecting privacy/security, and allocating resources. The PORTAL Governance Document, complete with a Toolkit of

  15. Latest developments in advanced network management and cross-sharing of next-generation flux stations

    NASA Astrophysics Data System (ADS)

    Burba, George; Johnson, Dave; Velgersdyk, Michael; Begashaw, Israel; Allyn, Douglas

    2016-04-01

    In recent years, spatial and temporal flux data coverage improved significantly and on multiple scales, from a single station to continental networks, due to standardization, automation, and management of the data collection, and better handling of the extensive amounts of generated data. However, operating budgets for flux research items, such as labor, travel, and hardware, are becoming more difficult to acquire and sustain. With more stations and networks, larger data flows from each station, and smaller operating budgets, modern tools are required to effectively and efficiently handle the entire process, including sharing data among collaborative groups. On one hand, such tools can maximize time dedicated to publications answering research questions, and minimize time and expenses spent on data acquisition, processing, quality control and overall station management. On the other hand, cross-sharing the stations with external collaborators may help leverage available funding, and promote data analyses and publications. A new low-cost, advanced system, FluxSuite, utilizes a combination of hardware, software and web-services to address these specific demands. It automates key stages of flux workflow, minimizes day-to-day site management, and modernizes the handling of data flows: (i) The system can be easily incorporated into a new flux station, or as un upgrade to many presently operating flux stations, via weatherized remotely-accessible microcomputer, SmartFlux 2, with fully digital inputs (ii) Each next-generation station will measure all parameters needed for flux computations in a digital and PTP time-synchronized mode, accepting digital signals from a number of anemometers and data loggers (iii) The field microcomputer will calculate final fully-processed flux rates in real time, including computation-intensive Fourier transforms, spectra, co-spectra, multiple rotations, stationarity, footprint, etc. (iv) Final fluxes, radiation, weather and soil data will

  16. "ATLAS" Advanced Technology Life-cycle Analysis System

    NASA Technical Reports Server (NTRS)

    Lollar, Louis F.; Mankins, John C.; ONeil, Daniel A.

    2004-01-01

    Making good decisions concerning research and development portfolios-and concerning the best systems concepts to pursue - as early as possible in the life cycle of advanced technologies is a key goal of R&D management This goal depends upon the effective integration of information from a wide variety of sources as well as focused, high-level analyses intended to inform such decisions Life-cycle Analysis System (ATLAS) methodology and tool kit. ATLAS encompasses a wide range of methods and tools. A key foundation for ATLAS is the NASA-created Technology Readiness. The toolkit is largely spreadsheet based (as of August 2003). This product is being funded by the Human and Robotics The presentation provides a summary of the Advanced Technology Level (TRL) systems Technology Program Office, Office of Exploration Systems, NASA Headquarters, Washington D.C. and is being integrated by Dan O Neil of the Advanced Projects Office, NASA/MSFC, Huntsville, AL

  17. Develop Advanced Nonlinear Signal Analysis Topographical Mapping System

    NASA Technical Reports Server (NTRS)

    Jong, Jen-Yi

    1997-01-01

    During the development of the SSME, a hierarchy of advanced signal analysis techniques for mechanical signature analysis has been developed by NASA and AI Signal Research Inc. (ASRI) to improve the safety and reliability for Space Shuttle operations. These techniques can process and identify intelligent information hidden in a measured signal which is often unidentifiable using conventional signal analysis methods. Currently, due to the highly interactive processing requirements and the volume of dynamic data involved, detailed diagnostic analysis is being performed manually which requires immense man-hours with extensive human interface. To overcome this manual process, NASA implemented this program to develop an Advanced nonlinear signal Analysis Topographical Mapping System (ATMS) to provide automatic/unsupervised engine diagnostic capabilities. The ATMS will utilize a rule-based Clips expert system to supervise a hierarchy of diagnostic signature analysis techniques in the Advanced Signal Analysis Library (ASAL). ASAL will perform automatic signal processing, archiving, and anomaly detection/identification tasks in order to provide an intelligent and fully automated engine diagnostic capability. The ATMS has been successfully developed under this contract. In summary, the program objectives to design, develop, test and conduct performance evaluation for an automated engine diagnostic system have been successfully achieved. Software implementation of the entire ATMS system on MSFC's OISPS computer has been completed. The significance of the ATMS developed under this program is attributed to the fully automated coherence analysis capability for anomaly detection and identification which can greatly enhance the power and reliability of engine diagnostic evaluation. The results have demonstrated that ATMS can significantly save time and man-hours in performing engine test/flight data analysis and performance evaluation of large volumes of dynamic test data.

  18. Presurgical epileptogenic network analysis: A way to enhance epilepsy surgery outcome.

    PubMed

    Dixit, Aparna Banerjee; Banerjee, Jyotirmoy; Tripathi, Manjari; Chandra, P Sarat

    2015-01-01

    Accurate localization of the "epileptogenic zone (EZ)" is an important issue in epilepsy surgery. The EZ is not discrete and focal; in fact, the epileptogenic networks can spread ictal activity to different regions of the brain. Changes in network characteristics and functional connectivity are shown to be associated with epilepsy. Seizures are thought to represent a hyper-synchronous state and presumable changes in synchronization between different brain regions underlie the mechanisms of seizure spread. Although presurgical evaluation of the epileptogenic network analysis can be carried out using existing investigative techniques like electroencephalogram (EEG), video-EEG, magnetic resonance imaging, single-photon emission computed tomography, and magnetoencephalography, advanced imaging techniques such as optical intrinsic spectroscopy, auto-fluorescence imaging, voltage sensitive dye imaging, and calcium imaging have the advantage of better spatiotemporal resolution over a large area of cortex. Understanding the wide-scale dynamic networks by analyzing the changes in the synchronization patterns using advanced imaging techniques will be instrumental in the presurgical analysis of the epileptogenic network and better localization of the EZs in the future. PMID:26448235

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

    DOE Data Explorer

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

    2014-08-01

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

  20. Experimental demonstration of large capacity WSDM optical access network with multicore fibers and advanced modulation formats.

    PubMed

    Li, Borui; Feng, Zhenhua; Tang, Ming; Xu, Zhilin; Fu, Songnian; Wu, Qiong; Deng, Lei; Tong, Weijun; Liu, Shuang; Shum, Perry Ping

    2015-05-01

    Towards the next generation optical access network supporting large capacity data transmission to enormous number of users covering a wider area, we proposed a hybrid wavelength-space division multiplexing (WSDM) optical access network architecture utilizing multicore fibers with advanced modulation formats. As a proof of concept, we experimentally demonstrated a WSDM optical access network with duplex transmission using our developed and fabricated multicore (7-core) fibers with 58.7km distance. As a cost-effective modulation scheme for access network, the optical OFDM-QPSK signal has been intensity modulated on the downstream transmission in the optical line terminal (OLT) and it was directly detected in the optical network unit (ONU) after MCF transmission. 10 wavelengths with 25GHz channel spacing from an optical comb generator are employed and each wavelength is loaded with 5Gb/s OFDM-QPSK signal. After amplification, power splitting, and fan-in multiplexer, 10-wavelength downstream signal was injected into six outer layer cores simultaneously and the aggregation downstream capacity reaches 300 Gb/s. -16 dBm sensitivity has been achieved for 3.8 × 10-3 bit error ratio (BER) with 7% Forward Error Correction (FEC) limit for all wavelengths in every core. Upstream signal from ONU side has also been generated and the bidirectional transmission in the same core causes negligible performance degradation to the downstream signal. As a universal platform for wired/wireless data access, our proposed architecture provides additional dimension for high speed mobile signal transmission and we hence demonstrated an upstream delivery of 20Gb/s per wavelength with QPSK modulation formats using the inner core of MCF emulating a mobile backhaul service. The IQ modulated data was coherently detected in the OLT side. -19 dBm sensitivity has been achieved under the FEC limit and more than 18 dB power budget is guaranteed. PMID:25969194

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

    ERIC Educational Resources Information Center

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

    2011-01-01

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

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

    ERIC Educational Resources Information Center

    Toikkanen, Tarmo; Lipponen, Lasse

    2011-01-01

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

  3. 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

  4. Use of Network Analysis to Establish Neurosurgical Parameters in Gliomas and Epilepsy

    PubMed Central

    MAESAWA, Satoshi; BAGARINAO, Epifanio; FUJII, Masazumi; FUTAMURA, Miyako; WAKABAYASHI, Toshihiko

    2016-01-01

    Cutting-edge neuroimaging technologies can facilitate preoperative evaluation in various neurosurgical settings. Surgery for gliomas and epilepsy requires precise localization for resection due to the need to preserve (or perhaps improve) higher cognitive functions. Accordingly, a hodological approach should be taken that considers subcortical networks as well as cortical functions within various functional domains. Resting state functional magnetic resonance imaging (fMRI) has the potential to provide new insights that are valuable for this approach. In this review, we describe recent developments in network analysis using resting state fMRI related to factors in glioma and epilepsy surgery: the identification of functionally dominant areas, evaluation of cognitive function by alteration of resting state networks (RSNs), glioma grading, and epileptic focus detection. One particular challenge that is close to realization is using fMRI for the identification of sensorimotor- and language-dominant areas during a task-free resting state. Various RSNs representative of the default mode network demonstrated at least some alterations in both patient groups, which correlated with behavioral changes including cognition, memory, and attention, and the development of psychosis. Still challenging is the detection of epileptic foci and propagation pathways when using only network analysis with resting state fMRI; however, a combined method with simultaneous electroencephalography has produced promising results. Consequently, network analysis is expected to continue to advance as neuroimaging technology improves in the next decade, and preoperative evaluation for neurosurgical parameters through these techniques should improve parallel with them. PMID:26923836

  5. Use of Network Analysis to Establish Neurosurgical Parameters in Gliomas and Epilepsy.

    PubMed

    Maesawa, Satoshi; Bagarinao, Epifanio; Fujii, Masazumi; Futamura, Miyako; Wakabayashi, Toshihiko

    2016-01-01

    Cutting-edge neuroimaging technologies can facilitate preoperative evaluation in various neurosurgical settings. Surgery for gliomas and epilepsy requires precise localization for resection due to the need to preserve (or perhaps improve) higher cognitive functions. Accordingly, a hodological approach should be taken that considers subcortical networks as well as cortical functions within various functional domains. Resting state functional magnetic resonance imaging (fMRI) has the potential to provide new insights that are valuable for this approach. In this review, we describe recent developments in network analysis using resting state fMRI related to factors in glioma and epilepsy surgery: the identification of functionally dominant areas, evaluation of cognitive function by alteration of resting state networks (RSNs), glioma grading, and epileptic focus detection. One particular challenge that is close to realization is using fMRI for the identification of sensorimotor- and language-dominant areas during a task-free resting state. Various RSNs representative of the default mode network demonstrated at least some alterations in both patient groups, which correlated with behavioral changes including cognition, memory, and attention, and the development of psychosis. Still challenging is the detection of epileptic foci and propagation pathways when using only network analysis with resting state fMRI; however, a combined method with simultaneous electroencephalography has produced promising results. Consequently, network analysis is expected to continue to advance as neuroimaging technology improves in the next decade, and preoperative evaluation for neurosurgical parameters through these techniques should improve parallel with them. PMID:26923836

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. A NEW METABOLOMICS ANALYSIS TECHNIQUE: STEADY-STATE METABOLIC NETWORK DYNAMICS ANALYSIS

    PubMed Central

    CAKMAK, ALI; QI, XINJIAN; CICEK, A. ERCUMENT; BEDERMAN, ILYA; HENDERSON, LEIGH; DRUMM, MITCHELL; OZSOYOGLU, GULTEKIN

    2014-01-01

    With the recent advances in experimental technologies, such as gas chromatography and mass spectrometry, the number of metabolites that can be measured in biofluids of individuals has markedly increased. Given a set of such measurements, a very common task encountered by biologists is to identify the metabolic mechanisms that lead to changes in the concentrations of given metabolites and interpret the metabolic consequences of the observed changes in terms of physiological problems, nutritional deficiencies, or diseases. In this paper, we present the steady-state metabolic network dynamics analysis (SMDA) approach in detail, together with its application in a cystic fibrosis study. We also present a computational performance evaluation of the SMDA tool against a mammalian metabolic network database. The query output space of the SMDA tool is exponentially large in the number of reactions of the network. However, (i) larger numbers of observations exponentially reduce the output size, and (ii) exploratory search and browsing of the query output space is provided to allow users to search for what they are looking for. PMID:22809304

  11. The Electrophysiological MEMS Device with Micro Channel Array for Cellular Network Analysis

    NASA Astrophysics Data System (ADS)

    Tonomura, Wataru; Kurashima, Toshiaki; Takayama, Yuzo; Moriguchi, Hiroyuki; Jimbo, Yasuhiko; Konishi, Satoshi

    This paper describes a new type of MCA (Micro Channel Array) for simultaneous multipoint measurement of cellular network. Presented MCA employing the measurement principles of the patch-clamp technique is designed for advanced neural network analysis which has been studied by co-authors using 64ch MEA (Micro Electrode Arrays) system. First of all, sucking and clamping of cells through channels of developed MCA is expected to improve electrophysiological signal detections. Electrophysiological sensing electrodes integrated around individual channels of MCA by using MEMS (Micro Electro Mechanical System) technologies are electrically isolated for simultaneous multipoint measurement. In this study, we tested the developed MCA using the non-cultured rat's cerebral cortical slice and the hippocampal neurons. We could measure the spontaneous action potential of the slice simultaneously at multiple points and culture the neurons on developed MCA. Herein, we describe the experimental results together with the design and fabrication of the electrophysiological MEMS device with MCA for cellular network analysis.

  12. 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

  13. Multiobjective blockmodeling for social network analysis.

    PubMed

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

    2013-07-01

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

  14. The prediction of the building precision in the Laser Engineered Net Shaping process using advanced networks

    NASA Astrophysics Data System (ADS)

    Lu, Z. L.; Li, D. C.; Lu, B. H.; Zhang, A. F.; Zhu, G. X.; Pi, G.

    2010-05-01

    Laser Engineered Net Shaping (LENS) is an advanced manufacturing technology, but it is difficult to control the depositing height (DH) of the prototype because there are many technology parameters influencing the forming process. The effect of main parameters (laser power, scanning speed and powder feeding rate) on the DH of single track is firstly analyzed, and then it shows that there is the complex nonlinear intrinsic relationship between them. In order to predict the DH, the back propagation (BP) based network improved with Adaptive learning rate and Momentum coefficient (AM) algorithm, and the least square support vector machine (LS-SVM) network are both adopted. The mapping relationship between above parameters and the DH is constructed according to training samples collected by LENS experiments, and then their generalization ability, function-approximating ability and real-time are contrastively investigated. The results show that although the predicted result by the BP-AM approximates the experimental result, above performance index of the LS-SVM are better than those of the BP-AM. Finally, high-definition thin-walled parts of AISI316L are successfully fabricated. Hence, the LS-SVM network is more suitable for the prediction of the DH.

  15. Advances in Mid-Infrared Spectroscopy for Chemical Analysis.

    PubMed

    Haas, Julian; Mizaikoff, Boris

    2016-06-12

    Infrared spectroscopy in the 3-20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review. PMID:27070183

  16. Advances in Mid-Infrared Spectroscopy for Chemical Analysis

    NASA Astrophysics Data System (ADS)

    Haas, Julian; Mizaikoff, Boris

    2016-06-01

    Infrared spectroscopy in the 3–20 μm spectral window has evolved from a routine laboratory technique into a state-of-the-art spectroscopy and sensing tool by benefitting from recent progress in increasingly sophisticated spectra acquisition techniques and advanced materials for generating, guiding, and detecting mid-infrared (MIR) radiation. Today, MIR spectroscopy provides molecular information with trace to ultratrace sensitivity, fast data acquisition rates, and high spectral resolution catering to demanding applications in bioanalytics, for example, and to improved routine analysis. In addition to advances in miniaturized device technology without sacrificing analytical performance, selected innovative applications for MIR spectroscopy ranging from process analysis to biotechnology and medical diagnostics are highlighted in this review.

  17. Analysis and design of advanced composite bounded joints

    NASA Technical Reports Server (NTRS)

    Hart-Smith, L. J.

    1974-01-01

    Advances in the analysis of adhesive-bonded joints are presented with particular emphasis on advanced composite structures. The joints analyzed are of double-lap, single-lap, scarf, stepped-lap and tapered-lap configurations. Tensile, compressive, and in-plane shear loads are covered. In addition to the usual geometric variables, the theory accounts for the strength increases attributable to adhesive plasticity (in terms of the elastic-plastic adhesive model) and the joint strength reductions imposed by imbalances between the adherends. The solutions are largely closed-form analytical results, employing iterative solutions on a digital computer for the more complicated joint configurations. In assessing the joint efficiency, three potential failure modes are considered. These are adherend failure outside the joint, adhesive failure in shear, and adherend interlaminar tension failure (or adhesive failure in peel). Each mode is governed by a distinct mathematical analysis and each prevails throughout different ranges of geometric sizes and proportions.

  18. Network traffic analysis using dispersion patterns

    Energy Science and Technology Software Center (ESTSC)

    2010-03-15

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

  19. 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…

  20. 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…

  1. 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…

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

    ERIC Educational Resources Information Center

    Doerfel, Marya L.; Barnett, George A.

    1999-01-01

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

  3. Evaluating network models: A likelihood analysis

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

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

  4. The Evolution of Technology in the Deep Space Network: A History of the Advanced Systems Program

    NASA Technical Reports Server (NTRS)

    Layland, J. W.; Rauch, L. L.

    1994-01-01

    The Deep Space Network (DSN) of 1995 might be described as the evolutionary result of 45 years of deep space communication and navigation, together with the synergistic activities of radio science and radar and radio astronomy. But the evolution of the DSN did not just happen - it was carefully planned and created. The evolution of the DSN has been an ongoing engineering activity, and engineering is a process of problem solving under constraints, one of which is technology. In turn, technology is the knowledge base providing the capability and experience for practical application of various areas of science, when needed. The best engineering solutions result from optimization under the fewest constraints, and if technology needs are well anticipated (ready when needed), then the most effective engineering solution is possible. Throughout the history of the DSN it has been the goal and function of DSN advanced technology development (designated the DSN Advanced Systems Program from 1963 through 1994) to supply the technology needs of the DSN when needed, and thus to minimize this constraint on DSN engineering. Technology often takes considerable time to develop, and when that happens, it is important to have anticipated engineering needs; at times, this anticipation has been by as much as 15 years. Also, on a number of occasions, mission malfunctions or emergencies have resulted in unplanned needs for technology that has, in fact, been available from the reservoir of advanced technology provided by the DSN Advanced Systems Program. Sometimes, even DSN engineering personnel fail to realize that the organization of JPL permits an overlap of DSN advanced technology activities with subsequent engineering activities. This can result in the flow of advanced technology into DSN engineering in a natural and sometimes almost unnoticed way. In the following pages, we will explore some of the many contributions of the DSN Advanced Systems Program that were provided to DSN

  5. 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

  6. Advanced gamma ray balloon experiment ground checkout and data analysis

    NASA Technical Reports Server (NTRS)

    Blackstone, M.

    1976-01-01

    A software programming package to be used in the ground checkout and handling of data from the advanced gamma ray balloon experiment is described. The Operator's Manual permits someone unfamiliar with the inner workings of the software system (called LEO) to operate on the experimental data as it comes from the Pulse Code Modulation interface, converting it to a form for later analysis, and monitoring the program of an experiment. A Programmer's Manual is included.

  7. [Advances in independent component analysis and its application].

    PubMed

    Chen, Huafu; Yao, Dezhong

    2003-06-01

    The independent component analysis (ICA) is a new technique in statistical signal processing, which decomposes mixed signals into statistical independent components. The reported applications in biomedical and radar signal have demonstrated its good prospect in various blind signal separation. In this paper, the progress of ICA in such as its principle, algorithm and application and advance direction of ICA in future is reviewed. The aim is to promote the research in theory and application in the future. PMID:12856621

  8. Advanced superposition methods for high speed turbopump vibration analysis

    NASA Technical Reports Server (NTRS)

    Nielson, C. E.; Campany, A. D.

    1981-01-01

    The small, high pressure Mark 48 liquid hydrogen turbopump was analyzed and dynamically tested to determine the cause of high speed vibration at an operating speed of 92,400 rpm. This approaches the design point operating speed of 95,000 rpm. The initial dynamic analysis in the design stage and subsequent further analysis of the rotor only dynamics failed to predict the vibration characteristics found during testing. An advanced procedure for dynamics analysis was used in this investigation. The procedure involves developing accurate dynamic models of the rotor assembly and casing assembly by finite element analysis. The dynamically instrumented assemblies are independently rap tested to verify the analytical models. The verified models are then combined by modal superposition techniques to develop a completed turbopump model where dynamic characteristics are determined. The results of the dynamic testing and analysis obtained are presented and methods of moving the high speed vibration characteristics to speeds above the operating range are recommended. Recommendations for use of these advanced dynamic analysis procedures during initial design phases are given.

  9. Advanced image analysis for the preservation of cultural heritage

    NASA Astrophysics Data System (ADS)

    France, Fenella G.; Christens-Barry, William; Toth, Michael B.; Boydston, Kenneth

    2010-02-01

    The Library of Congress' Preservation Research and Testing Division has established an advanced preservation studies scientific program for research and analysis of the diverse range of cultural heritage objects in its collection. Using this system, the Library is currently developing specialized integrated research methodologies for extending preservation analytical capacities through non-destructive hyperspectral imaging of cultural objects. The research program has revealed key information to support preservation specialists, scholars and other institutions. The approach requires close and ongoing collaboration between a range of scientific and cultural heritage personnel - imaging and preservation scientists, art historians, curators, conservators and technology analysts. A research project of the Pierre L'Enfant Plan of Washington DC, 1791 had been undertaken to implement and advance the image analysis capabilities of the imaging system. Innovative imaging options and analysis techniques allow greater processing and analysis capacities to establish the imaging technique as the first initial non-invasive analysis and documentation step in all cultural heritage analyses. Mapping spectral responses, organic and inorganic data, topography semi-microscopic imaging, and creating full spectrum images have greatly extended this capacity from a simple image capture technique. Linking hyperspectral data with other non-destructive analyses has further enhanced the research potential of this image analysis technique.

  10. The European VLF/LF Radio Network: Advances and Recent Results

    NASA Astrophysics Data System (ADS)

    Biagi, Pier Francesco; Maggipinto, Tommaso; Schiavulli, Luigi; Ligonzo, Teresa; Ermini, Anita; Martinelli, Giovanni; Moldovan, Iren; Silva, Hugo; Bezzeghoud, Mourad; Contadakis, Michael; Arabelos, Dimitrios; Frantzis, Xenofhon; Katzis, Konstantinos; Buyuksarac, Aydin; D'Amico, Sebastiano

    2013-04-01

    Since 2009 a network of VLF (20-60 kHz) and LF (150-300 kHz) radio receivers has been put into operation in Europe in order to study earthquakes precursors. At the moment the network consists of ten receivers three of which are located in Italy, two in Greece and one in Portugal, Romania, Malta, Cyprus and Turkey. The data (sampling rate of 1min) are downloaded automatically at the end of each day and are collected at the Department of Physics of the University of Bari (Italy) that is the central node of the network. A detailed study of the radio data collected in the radio network from July 2009 to September 2011 was performed, using different methods of analysis. In total 27 cases suitable for analyzing were found and successes, i.e. radio anomalies preceding the subsequent earthquake (Mw ≥ 5.0) and clearly related to the event, were obtained in 70% of the cases; but increasing the value of the Mw threshold for the earthquakes this percentage seems to increase. Among the different methods of analysis the Wavelet spectra appear to be the most sensitive ones. At the moment a system able to apply on the radio data the Wavelet analysis automatically at the end of each day is being developed. On May 20, 2012 an earthquake with Mw=6.1 occurred in north Italy (Emilia region); the epicenter is located inside the "sensitive" area of the network. The results obtained in such occasion are presented.

  11. 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.

  12. 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).

  13. [Advanced data analysis and visualization for clinical laboratory].

    PubMed

    Inada, Masanori; Yoneyama, Akiko

    2011-01-01

    This paper describes visualization techniques that help identify hidden structures in clinical laboratory data. The visualization of data is helpful for a rapid and better understanding of the characteristics of data sets. Various charts help the user identify trends in data. Scatter plots help prevent misinterpretations due to invalid data by identifying outliers. The representation of experimental data in figures is always useful for communicating results to others. Currently, flexible methods such as smoothing methods and latent structure analysis are available owing to the presence of advanced hardware and software. Principle component analysis, which is a well-known technique used to reduce multidimensional data sets, can be carried out on a personal computer. These methods could lead to advanced visualization with regard to exploratory data analysis. In this paper, we present 3 examples in order to introduce advanced data analysis. In the first example, a smoothing spline was fitted to a time-series from the control chart which is not in a state of statistical control. The trend line was clearly extracted from the daily measurements of the control samples. In the second example, principal component analysis was used to identify a new diagnostic indicator for Graves' disease. The multi-dimensional data obtained from patients were reduced to lower dimensions, and the principle components thus obtained summarized the variation in the data set. In the final example, a latent structure analysis for a Gaussian mixture model was used to draw complex density functions suitable for actual laboratory data. As a result, 5 clusters were extracted. The mixed density function of these clusters represented the data distribution graphically. The methods used in the above examples make the creation of complicated models for clinical laboratories more simple and flexible. PMID:21404582

  14. Linking Advanced Visualization and MATLAB for the Analysis of 3D Gene Expression Data

    SciTech Connect

    Ruebel, Oliver; Keranen, Soile V.E.; Biggin, Mark; Knowles, David W.; Weber, Gunther H.; Hagen, Hans; Hamann, Bernd; Bethel, E. Wes

    2011-03-30

    Three-dimensional gene expression PointCloud data generated by the Berkeley Drosophila Transcription Network Project (BDTNP) provides quantitative information about the spatial and temporal expression of genes in early Drosophila embryos at cellular resolution. The BDTNP team visualizes and analyzes Point-Cloud data using the software application PointCloudXplore (PCX). To maximize the impact of novel, complex data sets, such as PointClouds, the data needs to be accessible to biologists and comprehensible to developers of analysis functions. We address this challenge by linking PCX and Matlab via a dedicated interface, thereby providing biologists seamless access to advanced data analysis functions and giving bioinformatics researchers the opportunity to integrate their analysis directly into the visualization application. To demonstrate the usefulness of this approach, we computationally model parts of the expression pattern of the gene even skipped using a genetic algorithm implemented in Matlab and integrated into PCX via our Matlab interface.

  15. Advanced stress analysis methods applicable to turbine engine structures

    NASA Technical Reports Server (NTRS)

    Pian, Theodore H. H.

    1991-01-01

    The following tasks on the study of advanced stress analysis methods applicable to turbine engine structures are described: (1) constructions of special elements which contain traction-free circular boundaries; (2) formulation of new version of mixed variational principles and new version of hybrid stress elements; (3) establishment of methods for suppression of kinematic deformation modes; (4) construction of semiLoof plate and shell elements by assumed stress hybrid method; and (5) elastic-plastic analysis by viscoplasticity theory using the mechanical subelement model.

  16. Advances in Computational Stability Analysis of Composite Aerospace Structures

    SciTech Connect

    Degenhardt, R.; Araujo, F. C. de

    2010-09-30

    European aircraft industry demands for reduced development and operating costs. Structural weight reduction by exploitation of structural reserves in composite aerospace structures contributes to this aim, however, it requires accurate and experimentally validated stability analysis of real structures under realistic loading conditions. This paper presents different advances from the area of computational stability analysis of composite aerospace structures which contribute to that field. For stringer stiffened panels main results of the finished EU project COCOMAT are given. It investigated the exploitation of reserves in primary fibre composite fuselage structures through an accurate and reliable simulation of postbuckling and collapse. For unstiffened cylindrical composite shells a proposal for a new design method is presented.

  17. Advanced Models for Aeroelastic Analysis of Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Keith, Theo G., Jr.; Mahajan, Aparajit

    1996-01-01

    This report describes an integrated, multidisciplinary simulation capability for aeroelastic analysis and optimization of advanced propulsion systems. This research is intended to improve engine development, acquisition, and maintenance costs. One of the proposed simulations is aeroelasticity of blades, cowls, and struts in an ultra-high bypass fan. These ducted fans are expected to have significant performance, fuel, and noise improvements over existing engines. An interface program was written to use modal information from COBSTAN and NASTRAN blade models in aeroelastic analysis with a single rotation ducted fan aerodynamic code.

  18. 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.

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

    PubMed

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

    2015-01-01

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

  20. 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

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

    PubMed

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

    2015-01-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures. PMID:26634293

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

    PubMed Central

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

    2015-01-01

    Understanding the mechanisms that reduce the many degrees of freedom in the musculoskeletal system remains an outstanding challenge. Muscle synergies reduce the dimensionality and hence simplify the control problem. How this is achieved is not yet known. Here we use network theory to assess the coordination between multiple muscles and to elucidate the neural implementation of muscle synergies. We performed connectivity analysis of surface EMG from ten leg muscles to extract the muscle networks while human participants were standing upright in four different conditions. We observed widespread connectivity between muscles at multiple distinct frequency bands. The network topology differed significantly between frequencies and between conditions. These findings demonstrate how muscle networks can be used to investigate the neural circuitry of motor coordination. The presence of disparate muscle networks across frequencies suggests that the neuromuscular system is organized into a multiplex network allowing for parallel and hierarchical control structures. PMID:26634293

  3. 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.

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

    PubMed

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

    2010-08-01

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

  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. PMID:25462609

  6. Structural Configuration Systems Analysis for Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Welstead, Jason R.; Quinlan, Jesse R.; Guynn, Mark D.

    2016-01-01

    Structural configuration analysis of an advanced aircraft fuselage concept is investigated. This concept is characterized by a double-bubble section fuselage with rear mounted engines. Based on lessons learned from structural systems analysis of unconventional aircraft, high-fidelity finite-element models (FEM) are developed for evaluating structural performance of three double-bubble section configurations. Structural sizing and stress analysis are applied for design improvement and weight reduction. Among the three double-bubble configurations, the double-D cross-section fuselage design was found to have a relatively lower structural weight. The structural FEM weights of these three double-bubble fuselage section concepts are also compared with several cylindrical fuselage models. Since these fuselage concepts are different in size, shape and material, the fuselage structural FEM weights are normalized by the corresponding passenger floor area for a relative comparison. This structural systems analysis indicates that an advanced composite double-D section fuselage may have a relative structural weight ratio advantage over a conventional aluminum fuselage. Ten commercial and conceptual aircraft fuselage structural weight estimates, which are empirically derived from the corresponding maximum takeoff gross weight, are also presented and compared with the FEM- based estimates for possible correlation. A conceptual full vehicle FEM model with a double-D fuselage is also developed for preliminary structural analysis and weight estimation.

  7. Validation Database Based Thermal Analysis of an Advanced RPS Concept

    NASA Technical Reports Server (NTRS)

    Balint, Tibor S.; Emis, Nickolas D.

    2006-01-01

    Advanced RPS concepts can be conceived, designed and assessed using high-end computational analysis tools. These predictions may provide an initial insight into the potential performance of these models, but verification and validation are necessary and required steps to gain confidence in the numerical analysis results. This paper discusses the findings from a numerical validation exercise for a small advanced RPS concept, based on a thermal analysis methodology developed at JPL and on a validation database obtained from experiments performed at Oregon State University. Both the numerical and experimental configurations utilized a single GPHS module enabled design, resembling a Mod-RTG concept. The analysis focused on operating and environmental conditions during the storage phase only. This validation exercise helped to refine key thermal analysis and modeling parameters, such as heat transfer coefficients, and conductivity and radiation heat transfer values. Improved understanding of the Mod-RTG concept through validation of the thermal model allows for future improvements to this power system concept.

  8. 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

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

    PubMed

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

    2016-01-01

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

  10. 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

  11. Artificial neural networks for small dataset analysis.

    PubMed

    Pasini, Antonello

    2015-05-01

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

  12. Multilayer Network Analysis of Nuclear Reactions.

    PubMed

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

    2016-01-01

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

  13. 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

  14. Artificial neural networks for small dataset analysis

    PubMed Central

    2015-01-01

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

  15. Analysis of remote synchronization in complex networks

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  16. Performance Analysis of IIUM Wireless Campus Network

    NASA Astrophysics Data System (ADS)

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

    2013-12-01

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

  17. Revealing shared and distinct gene network organization in Arabidopsis immune responses by integrative analysis.

    PubMed

    Dong, Xiaobao; Jiang, Zhenhong; Peng, You-Liang; Zhang, Ziding

    2015-03-01

    Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response. PMID:25614062

  18. Revealing Shared and Distinct Gene Network Organization in Arabidopsis Immune Responses by Integrative Analysis1

    PubMed Central

    Dong, Xiaobao; Jiang, Zhenhong; Peng, You-Liang; Zhang, Ziding

    2015-01-01

    Pattern-triggered immunity (PTI) and effector-triggered immunity (ETI) are two main plant immune responses to counter pathogen invasion. Genome-wide gene network organizing principles leading to quantitative differences between PTI and ETI have remained elusive. We combined an advanced machine learning method and modular network analysis to systematically characterize the organizing principles of Arabidopsis (Arabidopsis thaliana) PTI and ETI at three network resolutions. At the single network node/edge level, we ranked genes and gene interactions based on their ability to distinguish immune response from normal growth and successfully identified many immune-related genes associated with PTI and ETI. Topological analysis revealed that the top-ranked gene interactions tend to link network modules. At the subnetwork level, we identified a subnetwork shared by PTI and ETI encompassing 1,159 genes and 1,289 interactions. This subnetwork is enriched in interactions linking network modules and is also a hotspot of attack by pathogen effectors. The subnetwork likely represents a core component in the coordination of multiple biological processes to favor defense over development. Finally, we constructed modular network models for PTI and ETI to explain the quantitative differences in the global network architecture. Our results indicate that the defense modules in ETI are organized into relatively independent structures, explaining the robustness of ETI to genetic mutations and effector attacks. Taken together, the multiscale comparisons of PTI and ETI provide a systems biology perspective on plant immunity and emphasize coordination among network modules to establish a robust immune response. PMID:25614062

  19. 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

  20. Inference, simulation, modeling, and analysis of complex networks, with special emphasis on complex networks in systems biology

    NASA Astrophysics Data System (ADS)

    Christensen, Claire Petra

    Across diverse fields ranging from physics to biology, sociology, and economics, the technological advances of the past decade have engendered an unprecedented explosion of data on highly complex systems with thousands, if not millions of interacting components. These systems exist at many scales of size and complexity, and it is becoming ever-more apparent that they are, in fact, universal, arising in every field of study. Moreover, they share fundamental properties---chief among these, that the individual interactions of their constituent parts may be well-understood, but the characteristic behaviour produced by the confluence of these interactions---by these complex networks---is unpredictable; in a nutshell, the whole is more than the sum of its parts. There is, perhaps, no better illustration of this concept than the discoveries being made regarding complex networks in the biological sciences. In particular, though the sequencing of the human genome in 2003 was a remarkable feat, scientists understand that the "cellular-level blueprints" for the human being are cellular-level parts lists, but they say nothing (explicitly) about cellular-level processes. The challenge of modern molecular biology is to understand these processes in terms of the networks of parts---in terms of the interactions among proteins, enzymes, genes, and metabolites---as it is these processes that ultimately differentiate animate from inanimate, giving rise to life! It is the goal of systems biology---an umbrella field encapsulating everything from molecular biology to epidemiology in social systems---to understand processes in terms of fundamental networks of core biological parts, be they proteins or people. By virtue of the fact that there are literally countless complex systems, not to mention tools and techniques used to infer, simulate, analyze, and model these systems, it is impossible to give a truly comprehensive account of the history and study of complex systems. The author

  1. Advanced hydrogen/oxygen thrust chamber design analysis

    NASA Technical Reports Server (NTRS)

    Shoji, J. M.

    1973-01-01

    The results are reported of the advanced hydrogen/oxygen thrust chamber design analysis program. The primary objectives of this program were to: (1) provide an in-depth analytical investigation to develop thrust chamber cooling and fatigue life limitations of an advanced, high pressure, high performance H2/O2 engine design of 20,000-pounds (88960.0 N) thrust; and (2) integrate the existing heat transfer analysis, thermal fatigue and stress aspects for advanced chambers into a comprehensive computer program. Thrust chamber designs and analyses were performed to evaluate various combustor materials, coolant passage configurations (tubes and channels), and cooling circuits to define the nominal 1900 psia (1.31 x 10 to the 7th power N/sq m) chamber pressure, 300-cycle life thrust chamber. The cycle life capability of the selected configuration was then determined for three duty cycles. Also the influence of cycle life and chamber pressure on thrust chamber design was investigated by varying in cycle life requirements at the nominal chamber pressure and by varying the chamber pressure at the nominal cycle life requirement.

  2. An Advanced Orbiting Systems Approach to Quality of Service in Space-Based Intelligent Communication Networks

    NASA Technical Reports Server (NTRS)

    Riha, Andrew P.

    2005-01-01

    As humans and robotic technologies are deployed in future constellation systems, differing traffic services will arise, e.g., realtime and non-realtime. In order to provide a quality of service framework that would allow humans and robotic technologies to interoperate over a wide and dynamic range of interactions, a method of classifying data as realtime or non-realtime is needed. In our paper, we present an approach that leverages the Consultative Committee for Space Data Systems (CCSDS) Advanced Orbiting Systems (AOS) data link protocol. Specifically, we redefine the AOS Transfer Frame Replay Flag in order to provide an automated store-and-forward approach on a per-service basis for use in the next-generation Interplanetary Network. In addition to addressing the problem of intermittent connectivity and associated services, we propose a follow-on methodology for prioritizing data through further modification of the AOS Transfer Frame.

  3. Perspectives on Advanced Learning Technologies and Learning Networks and Future Aerospace Workforce Environments

    NASA Technical Reports Server (NTRS)

    Noor, Ahmed K. (Compiler)

    2003-01-01

    An overview of the advanced learning technologies is given in this presentation along with a brief description of their impact on future aerospace workforce development. The presentation is divided into five parts (see Figure 1). In the first part, a brief historical account of the evolution of learning technologies is given. The second part describes the current learning activities. The third part describes some of the future aerospace systems, as examples of high-tech engineering systems, and lists their enabling technologies. The fourth part focuses on future aerospace research, learning and design environments. The fifth part lists the objectives of the workshop and some of the sources of information on learning technologies and learning networks.

  4. Advanced high quality aerosol data: novel results from the EUSAAR in situ measurement network

    NASA Astrophysics Data System (ADS)

    Laj, P.; Philippin, S.; Putaud, J.-P.; Wiedensohler, A.; de Leeuw, G.; Fjaeraa, A. M.; Platt, U.; Baltensperger, U.; Fiebig, M.

    2009-04-01

    The EU-funded project EUSAAR (EUropean Supersites for Atmospheric Aerosol Research) aims at integrating measurements of atmospheric aerosol properties from a distributed network of 20 high-quality European ground-based stations. The objective is to ensure harmonization, validation and data diffusion of current measurements of particle optical, physical and chemical properties which are critical parameters for quantifying the key processes and the impact of aerosols on climate and air quality. We will present and discuss the results and highlights of the activities and achievements during the first 3 years of the project during which EUSAAR has contributed to improving the comparability of measurements for data users and to adopting best practices in aerosol monitoring procedures, and has started providing high quality aerosol data much needed in the atmospheric research community from the most advanced monitoring stations currently operational in Europe.

  5. Advanced Main Combustion Chamber structural jacket strength analysis

    NASA Technical Reports Server (NTRS)

    Johnston, L. M.; Perkins, L. A.; Denniston, C. L.; Price, J. M.

    1993-01-01

    The structural analysis of the Advanced Main Combustion Chamber (AMCC) is presented. The AMCC is an advanced fabrication concept of the Space Shuttle Main Engine main combustion chamber (MCC). Reduced cost and fabrication time of up to 75 percent were the goals of the AMCC with cast jacket with vacuum plasma sprayed or platelet liner. Since the cast material for the AMCC is much weaker than the wrought material for the MCC, the AMCC is heavier and strength margins much lower in some areas. Proven hand solutions were used to size the manifolds cutout tee areas for combined pressure and applied loads. Detailed finite element strength analyses were used to size the manifolds, longitudinal ribs, and jacket for combined pressure and applied local loads. The design of the gimbal actuator strut attachment lugs were determined by finite element analyses and hand solutions.

  6. Whole-genome CNV analysis: advances in computational approaches

    PubMed Central

    Pirooznia, Mehdi; Goes, Fernando S.; Zandi, Peter P.

    2015-01-01

    Accumulating evidence indicates that DNA copy number variation (CNV) is likely to make a significant contribution to human diversity and also play an important role in disease susceptibility. Recent advances in genome sequencing technologies have enabled the characterization of a variety of genomic features, including CNVs. This has led to the development of several bioinformatics approaches to detect CNVs from next-generation sequencing data. Here, we review recent advances in CNV detection from whole genome sequencing. We discuss the informatics approaches and current computational tools that have been developed as well as their strengths and limitations. This review will assist researchers and analysts in choosing the most suitable tools for CNV analysis as well as provide suggestions for new directions in future development. PMID:25918519

  7. 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…

  8. 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…

  9. 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…

  10. 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...

  11. 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.

  12. Advanced simulation for analysis of critical infrastructure : abstract cascades, the electric power grid, and Fedwire.

    SciTech Connect

    Glass, Robert John, Jr.; Stamber, Kevin Louis; Beyeler, Walter Eugene

    2004-08-01

    Critical Infrastructures are formed by a large number of components that interact within complex networks. As a rule, infrastructures contain strong feedbacks either explicitly through the action of hardware/software control, or implicitly through the action/reaction of people. Individual infrastructures influence others and grow, adapt, and thus evolve in response to their multifaceted physical, economic, cultural, and political environments. Simply put, critical infrastructures are complex adaptive systems. In the Advanced Modeling and Techniques Investigations (AMTI) subgroup of the National Infrastructure Simulation and Analysis Center (NISAC), we are studying infrastructures as complex adaptive systems. In one of AMTI's efforts, we are focusing on cascading failure as can occur with devastating results within and between infrastructures. Over the past year we have synthesized and extended the large variety of abstract cascade models developed in the field of complexity science and have started to apply them to specific infrastructures that might experience cascading failure. In this report we introduce our comprehensive model, Polynet, which simulates cascading failure over a wide range of network topologies, interaction rules, and adaptive responses as well as multiple interacting and growing networks. We first demonstrate Polynet for the classical Bac, Tang, and Wiesenfeld or BTW sand-pile in several network topologies. We then apply Polynet to two very different critical infrastructures: the high voltage electric power transmission system which relays electricity from generators to groups of distribution-level consumers, and Fedwire which is a Federal Reserve service for sending large-value payments between banks and other large financial institutions. For these two applications, we tailor interaction rules to represent appropriate unit behavior and consider the influence of random transactions within two stylized networks: a regular homogeneous array and a

  13. Investigation on Interference Coordination Employing Almost Blank Subframes in Heterogeneous Networks for LTE-Advanced Downlink

    NASA Astrophysics Data System (ADS)

    Miki, Nobuhiko; Saito, Yuya; Shirakabe, Masashige; Morimoto, Akihito; Abe, Tetsushi

    This paper investigates the application of inter-cell interference coordination (ICIC) in heterogeneous networks for the LTE-Advanced downlink where picocells are overlaid onto macrocells. In LTE-Advanced, in order to perform ICIC, almost blank subframes (ABSs) are employed, where only the cell-specific reference signal (CRS) is transmitted to protect the subframes in the picocells from severe interference from the macrocells. Furthermore, multicast/broadcast over single-frequency network (MBSFN) subframes are employed to reduce the interference of the CRS on the data channel, although the control channel still suffers from interference from the CRS. When the cell range expansion (CRE), which offload the UEs from macrocells to picocells, is used to improve the system performance, the influence from the CRS increases. In order to assess the influence, the required CRE bias to improve the data channel is investigated based on a system-level simulation under various conditions such as the number of picocells, the protected subframe ratio, and the user distribution. The simulation results show that the cell-edge user throughput is improved with the CRE bias of more than 8dB, employing ABSs. Furthermore, simulation results show that one dominant source of interference is observed for the sets of user equipment (UEs) connected to the picocells via CRE with such a bias value. Based on observation, the influence that the CRS has on the control channel, i.e., physical control format indicator channel (PCFICH), and physical downlink control channel (PDCCH) is investigated based on a link-level simulation combined with a system-level simulation. The simulation results show that protecting the PCFICH is very important compared to protecting the PDCCH, since the block error rate (BLER) performance of the PCFICH becomes worse than the required BLER of 10-3 to support various conditions, although the BLER performance of the PDCCH can exceed the required BLER of 10-2 by spanning

  14. The New Algorithm for Symbolic Network Analysis.

    NASA Astrophysics Data System (ADS)

    Chow, John Tsai-Chiang

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

  15. 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.

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

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

    PubMed

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

    2016-07-01

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

  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. Vulnerability analysis for complex networks using aggressive abstraction.

    SciTech Connect

    Colbaugh, Richard; Glass, Kristin L.

    2010-06-01

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

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

    PubMed Central

    2013-01-01

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

  2. Decreased resting-state connections within the visuospatial attention-related network in advanced aging.

    PubMed

    Li, Yujie; Li, Chunlin; Wu, Qiong; Xu, Zhihan; Kurata, Tomoko; Ohno, Seiichiro; Kanazawa, Susumu; Abe, Koji; Wu, Jinglong

    2015-06-15

    Advanced aging is accompanied by a decline in visuospatial attention. Previous neuroimaging and electrophysiological studies have demonstrated dysfunction in specific brain areas related to visuospatial attention. However, it is still unclear how the functional connectivity between brain regions causes the decline of visuospatial attention. Here, we combined task and rest functional magnetic resonance imaging (fMRI) to investigate the age-dependent alterations of resting-state functional connectivity within the task-related network. Twenty-three young subjects and nineteen elderly subjects participated in this study, and a modified Posner paradigm was used to define the region of interest (ROI). Our results showed that a marked reduction in the number of connections occurred with age, but this effect was not uniform throughout the brain: while there was a significant loss of communication in the anterior portion of the brain and between the anterior and posterior cerebral cortices, communication in the posterior portion of the brain was preserved. Moreover, the older adults exhibited weakened resting-state functional connectivity between the supplementary motor area and left anterior insular cortex. These findings suggest that, the disrupted functional connectivity of the brain network for visuospatial attention that occurs during normal aging may underlie the decline in cognitive performance. PMID:25817360

  3. An advanced probabilistic structural analysis method for implicit performance functions

    NASA Technical Reports Server (NTRS)

    Wu, Y.-T.; Millwater, H. R.; Cruse, T. A.

    1989-01-01

    In probabilistic structural analysis, the performance or response functions usually are implicitly defined and must be solved by numerical analysis methods such as finite element methods. In such cases, the most commonly used probabilistic analysis tool is the mean-based, second-moment method which provides only the first two statistical moments. This paper presents a generalized advanced mean value (AMV) method which is capable of establishing the distributions to provide additional information for reliability design. The method requires slightly more computations than the second-moment method but is highly efficient relative to the other alternative methods. In particular, the examples show that the AMV method can be used to solve problems involving non-monotonic functions that result in truncated distributions.

  4. The analysis of protein pharmaceuticals: near future advances.

    PubMed

    Middaugh, C R

    1994-01-01

    The analysis of protein pharmaceuticals currently involves a complex series of chromatographic, electrophoretic, spectroscopic, immunological and biological measurements to unequivocally establish their identity, purity and integrity. In this review, I briefly consider the possibility that at least the functional identity and integrity of a protein drug might be established by either a single analysis involving X-ray diffraction, NMR or mass spectrometry, or by a chromatographically based multi-detector system in which a number of critical parameters are essentially simultaneously determined. The use of a protein standard to obtain comparative measurements and new advances in the technology of each of these methods is emphasized. A current major obstacle to the implementation of these approaches is the frequent microheterogeneity of protein preparations. The evolution of biological assays into measurements examining more defined intracellular signal transduction events or based on novel biosensors as well as the analysis of vaccines is also briefly discussed. PMID:7765931

  5. 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

  6. Mobile Wireless Sensor Networks for Advanced Soil Sensing and Ecosystem Monitoring

    NASA Astrophysics Data System (ADS)

    Mollenhauer, Hannes; Schima, Robert; Remmler, Paul; Mollenhauer, Olaf; Hutschenreuther, Tino; Toepfer, Hannes; Dietrich, Peter; Bumberger, Jan

    2015-04-01

    For an adequate characterization of ecosystems it is necessary to detect individual processes with suitable monitoring strategies and methods. Due to the natural complexity of all environmental compartments, single point or temporally and spatially fixed measurements are mostly insufficient for an adequate representation. The application of mobile wireless sensor networks for soil and atmosphere sensing offers significant benefits, due to the simple adjustment of the sensor distribution, the sensor types and the sample rate (e.g. by using optimization approaches or event triggering modes) to the local test conditions. This can be essential for the monitoring of heterogeneous and dynamic environmental systems and processes. One significant advantage in the application of mobile ad-hoc wireless sensor networks is their self-organizing behavior. Thus, the network autonomously initializes and optimizes itself. Due to the localization via satellite a major reduction in installation and operation costs and time is generated. In addition, single point measurements with a sensor are significantly improved by measuring at several optimized points continuously. Since performing analog and digital signal processing and computation in the sensor nodes close to the sensors a significant reduction of the data to be transmitted can be achieved which leads to a better energy management of nodes. Furthermore, the miniaturization of the nodes and energy harvesting are current topics under investigation. First results of field measurements are given to present the potentials and limitations of this application in environmental science. In particular, collected in-situ data with numerous specific soil and atmosphere parameters per sensor node (more than 25) recorded over several days illustrates the high performance of this system for advanced soil sensing and soil-atmosphere interaction monitoring. Moreover, investigations of biotic and abiotic process interactions and optimization

  7. 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.

  8. Neurocontroller analysis via evolutionary network minimization.

    PubMed

    Ganon, Zohar; Keinan, Alon; Ruppin, Eytan

    2006-01-01

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

  9. Composite Structure Modeling and Analysis of Advanced Aircraft Fuselage Concepts

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Sorokach, Michael R.

    2015-01-01

    NASA Environmentally Responsible Aviation (ERA) project and the Boeing Company are collabrating to advance the unitized damage arresting composite airframe technology with application to the Hybrid-Wing-Body (HWB) aircraft. The testing of a HWB fuselage section with Pultruded Rod Stitched Efficient Unitized Structure (PRSEUS) construction is presently being conducted at NASA Langley. Based on lessons learned from previous HWB structural design studies, improved finite-element models (FEM) of the HWB multi-bay and bulkhead assembly are developed to evaluate the performance of the PRSEUS construction. In order to assess the comparative weight reduction benefits of the PRSEUS technology, conventional cylindrical skin-stringer-frame models of a cylindrical and a double-bubble section fuselage concepts are developed. Stress analysis with design cabin-pressure load and scenario based case studies are conducted for design improvement in each case. Alternate analysis with stitched composite hat-stringers and C-frames are also presented, in addition to the foam-core sandwich frame and pultruded rod-stringer construction. The FEM structural stress, strain and weights are computed and compared for relative weight/strength benefit assessment. The structural analysis and specific weight comparison of these stitched composite advanced aircraft fuselage concepts demonstrated that the pressurized HWB fuselage section assembly can be structurally as efficient as the conventional cylindrical fuselage section with composite stringer-frame and PRSEUS construction, and significantly better than the conventional aluminum construction and the double-bubble section concept.

  10. 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

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

    PubMed

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

    2016-01-01

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

  12. Statistical Models and Methods for Network Meta-Analysis.

    PubMed

    Madden, L V; Piepho, H-P; Paul, P A

    2016-08-01

    Meta-analysis, the methodology for analyzing the results from multiple independent studies, has grown tremendously in popularity over the last four decades. Although most meta-analyses involve a single effect size (summary result, such as a treatment difference) from each study, there are often multiple treatments of interest across the network of studies in the analysis. Multi-treatment (or network) meta-analysis can be used for simultaneously analyzing the results from all the treatments. However, the methodology is considerably more complicated than for the analysis of a single effect size, and there have not been adequate explanations of the approach for agricultural investigations. We review the methods and models for conducting a network meta-analysis based on frequentist statistical principles, and demonstrate the procedures using a published multi-treatment plant pathology data set. A major advantage of network meta-analysis is that correlations of estimated treatment effects are automatically taken into account when an appropriate model is used. Moreover, treatment comparisons may be possible in a network meta-analysis that are not possible in a single study because all treatments of interest may not be included in any given study. We review several models that consider the study effect as either fixed or random, and show how to interpret model-fitting output. We further show how to model the effect of moderator variables (study-level characteristics) on treatment effects, and present one approach to test for the consistency of treatment effects across the network. Online supplemental files give explanations on fitting the network meta-analytical models using SAS. PMID:27111798

  13. Qualitative Analysis of Commercial Social Network Profiles

    NASA Astrophysics Data System (ADS)

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

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

  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. Analysis of Regional GPS Networks in Eastern Ontario

    NASA Astrophysics Data System (ADS)

    Samadi Alinia, H.; Tiampo, K. F.

    2014-12-01

    Although stable, intraplate region of eastern Canada is considered low rate deformation area in the North American plate, the retreat of large ice sheets during deglaciation in the last 20 ka has resulted in horizontal and vertical deformation of the Earth's in eastern Ontario. Present-day glacial isostatic adjustment (GIA) uplift rates approach 10 mm/yr or more at Hudson Bay and decrease with distance southeastward. Current GIA models forecast that the hinge line between uplift to the northwest and subsidence to the southeast lies somewhere near the Saint Lawrence valley in eastern Canada [Tushingham and Peltier, 1991; Peltier, 2002]. Employing continuous Global Positioning System (cGPS) observations and high precision tools for processing and then analyzing each component of derived time series are important tools to monitor the associated regional crustal deformation with good accuracies. Here we describe the analysis of coordinate time series of cGPS stations scattered sparsely throughout southeastern Ontario and between Ottawa and the east coast of Hudson Bay. Here, the two most reliable local networks, each including 4 to 6 reference stations, were selected for analysis. Data for period of approximately five years, 2008-2012.9, was processed with Bernese 5.0 over several campaigns. Individual cGPS coordinate time series were generated for each station and basic parameters, such as mean, variance and repeatability, were estimated. The time series are corrected with respect to the rigid plate motion and seasonal variations and advanced time series analysis techniques, including spectral analysis and principal component analysis were implemented. Post-processing of the time series reproduces the general GIA spatial pattern. Results also show that the vertical velocities of all stations in the solution are consistent with the GIA model uplift rate and are consistent with other cGPS sites in eastern Canada and increases from north of lake of Ontario (approximately

  16. Analysis of opinion spreading in homogeneous networks with signed relationships

    NASA Astrophysics Data System (ADS)

    Fan, Pengyi; Wang, Hui; Li, Pei; Li, Wei; Jiang, Zhihong

    2012-08-01

    Recently, significant attention has been devoted to opinion dynamics in social networks, in which all the relationships between individuals are assumed as positive ones (i.e. friend, altruism or trust). However, many realistic social networks include negative relationships (i.e. enemy or distrust) as well as positive ones. In order to find the dynamical behavior of opinion spreading in signed networks, we propose a model taking into account the impacts of positive and negative relationships. Based on this model, we analyze the dynamical process and provide a detailed mathematical analysis for identifying the threshold of opinion spreading in homogeneous networks with signed relationships. By performing numerical simulations for the threshold in three different signed networks, we find that the theoretical and numerical results are in good agreement, confirming the correctness of our exact solution.

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

    NASA Astrophysics Data System (ADS)

    Matesanz, David; Ortega, Guillermo J.

    2015-10-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2010-04-01

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

  19. Radionuclide migration analysis using a discrete fracture network model

    SciTech Connect

    Ijiri, Y.; Sawada, A.; Webb, E.K.; Watari, S.; Hatanaka, K.; Uchida, M.; Ishiguro, K.; Umeki, H.; Dershowitz, W.S.

    1999-07-01

    This paper describes an approach for assessing the geosphere performance of nuclear waste disposal in fractured rock. In this approach, a three-dimensional heterogeneous channel-network model is constructed using a stochastic discrete fracture network (DFN) code. Radionuclide migration in the channel-network model is solved using the Laplace transform Galerkin finite element method, taking into account advection-dispersion in a fracture network, matrix diffusion, sorption in the rock matrix as well as radioactive chain decay. Preliminary radionuclide migration analysis was performed for fifty realizations of a synthetic block-scale DFN model. The total radionuclide release from all packages in the repository was estimated from the statistics of the results of fifty realizations under the hypothesis of ergodicity. The interpretation of the result of the three-dimensional network model by a combination of simpler one-dimensional parallel plate models is also discussed.

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

    PubMed Central

    2014-01-01

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

  1. Analysis of torsional oscillations using an artificial neural network

    SciTech Connect

    Hsu, Y.Y.; Jeng, L,H. )

    1992-12-01

    In this paper, a novel approach using an artificial neural network (ANN) is proposed for the analysis of torsional oscillations in a power system. In the developed artificial neural network, those system variables such as generator loadings and capacitor compensation ratio which have major impacts on the damping characteristics of torsional oscillatio modes are employed as the inputs. The outputs of the neural net provide the desired eigenvalues for torsional modes. Once the connection weights of the neural network have been learned using a set of training data derived off-line, the neural network can be applied to torsional analysis in real-time situations. To demonstrate the effectiveness of the proposed neural net, torsional analysis is performed on the IEEE First Benchmark Model. It is concluded from the test results that accurate assessment of the torsional mode eigenvalues can be achieved by the neural network in a very efficient manner. Thereofore, the proposed neural network approach can serve as a valuable tool to system operators in conducting SSR analysis in operational planning.

  2. Advanced water window x-ray microscope design and analysis

    NASA Technical Reports Server (NTRS)

    Shealy, D. L.; Wang, C.; Jiang, W.; Lin, J.

    1992-01-01

    The project was focused on the design and analysis of an advanced water window soft-x-ray microscope. The activities were accomplished by completing three tasks contained in the statement of work of this contract. The new results confirm that in order to achieve resolutions greater than three times the wavelength of the incident radiation, it will be necessary to use aspherical mirror surfaces and to use graded multilayer coatings on the secondary (to accommodate the large variations of the angle of incidence over the secondary when operating the microscope at numerical apertures of 0.35 or greater). The results are included in a manuscript which is enclosed in the Appendix.

  3. Advanced Wireless Power Transfer Vehicle and Infrastructure Analysis (Presentation)

    SciTech Connect

    Gonder, J.; Brooker, A.; Burton, E.; Wang, J.; Konan, A.

    2014-06-01

    This presentation discusses current research at NREL on advanced wireless power transfer vehicle and infrastructure analysis. The potential benefits of E-roadway include more electrified driving miles from battery electric vehicles, plug-in hybrid electric vehicles, or even properly equipped hybrid electric vehicles (i.e., more electrified miles could be obtained from a given battery size, or electrified driving miles could be maintained while using smaller and less expensive batteries, thereby increasing cost competitiveness and potential market penetration). The system optimization aspect is key given the potential impact of this technology on the vehicles, the power grid and the road infrastructure.

  4. Advanced Technology Lifecycle Analysis System (ATLAS) Technology Tool Box (TTB)

    NASA Technical Reports Server (NTRS)

    Doyle, Monica; ONeil, Daniel A.; Christensen, Carissa B.

    2005-01-01

    The Advanced Technology Lifecycle Analysis System (ATLAS) is a decision support tool designed to aid program managers and strategic planners in determining how to invest technology research and development dollars. It is an Excel-based modeling package that allows a user to build complex space architectures and evaluate the impact of various technology choices. ATLAS contains system models, cost and operations models, a campaign timeline and a centralized technology database. Technology data for all system models is drawn from a common database, the ATLAS Technology Tool Box (TTB). The TTB provides a comprehensive, architecture-independent technology database that is keyed to current and future timeframes.

  5. Creep analysis of fuel plates for the Advanced Neutron Source

    SciTech Connect

    Swinson, W.F.; Yahr, G.T.

    1994-11-01

    The reactor for the planned Advanced Neutron Source will use closely spaced arrays of fuel plates. The plates are thin and will have a core containing enriched uranium silicide fuel clad in aluminum. The heat load caused by the nuclear reactions within the fuel plates will be removed by flowing high-velocity heavy water through narrow channels between the plates. However, the plates will still be at elevated temperatures while in service, and the potential for excessive plate deformation because of creep must be considered. An analysis to include creep for deformation and stresses because of temperature over a given time span has been performed and is reported herein.

  6. Design, analysis and test verification of advanced encapsulation systems

    NASA Technical Reports Server (NTRS)

    Garcia, A., III

    1982-01-01

    An analytical methodology for advanced encapsulation designs was developed. From these methods design sensitivities are established for the development of photovoltaic module criteria and the definition of needed research tasks. Analytical models were developed to perform optical, thermal, electrical and analyses on candidate encapsulation systems. From these analyses several candidate systems were selected for qualification testing. Additionally, test specimens of various types are constructed and tested to determine the validity of the analysis methodology developed. Identified deficiencies and/or discrepancies between analytical models and relevant test data are corrected. Prediction capability of analytical models is improved. Encapsulation engineering generalities, principles, and design aids for photovoltaic module designers is generated.

  7. Life-cycle cost analysis of advanced design mixer pump

    SciTech Connect

    Hall, M.N., Westinghouse Hanford

    1996-07-23

    This analysis provides cost justification for the Advanced Design Mixer Pump program based on the cost benefit to the Hanford Site of 4 mixer pump systems defined in terms of the life-cycle cost.A computer model is used to estimate the total number of service hours necessary for each mixer pump to operate over the 20-year retrieval sequence period for single-shell tank waste. This study also considered the double-shell tank waste retrieved prior to the single-shell tank waste which is considered the initial retrieval.

  8. Computer modeling for advanced life support system analysis.

    PubMed

    Drysdale, A

    1997-01-01

    This article discusses the equivalent mass approach to advanced life support system analysis, describes a computer model developed to use this approach, and presents early results from modeling the NASA JSC BioPlex. The model is built using an object oriented approach and G2, a commercially available modeling package Cost factor equivalencies are given for the Volosin scenarios. Plant data from NASA KSC and Utah State University (USU) are used, together with configuration data from the BioPlex design effort. Initial results focus on the importance of obtaining high plant productivity with a flight-like configuration. PMID:11540448

  9. ADVISOR: a systems analysis tool for advanced vehicle modeling

    NASA Astrophysics Data System (ADS)

    Markel, T.; Brooker, A.; Hendricks, T.; Johnson, V.; Kelly, K.; Kramer, B.; O'Keefe, M.; Sprik, S.; Wipke, K.

    This paper provides an overview of Advanced Vehicle Simulator (ADVISOR)—the US Department of Energy's (DOE's) ADVISOR written in the MATLAB/Simulink environment and developed by the National Renewable Energy Laboratory. ADVISOR provides the vehicle engineering community with an easy-to-use, flexible, yet robust and supported analysis package for advanced vehicle modeling. It is primarily used to quantify the fuel economy, the performance, and the emissions of vehicles that use alternative technologies including fuel cells, batteries, electric motors, and internal combustion engines in hybrid (i.e. multiple power sources) configurations. It excels at quantifying the relative change that can be expected due to the implementation of technology compared to a baseline scenario. ADVISOR's capabilities and limitations are presented and the power source models that are included in ADVISOR are discussed. Finally, several applications of the tool are presented to highlight ADVISOR's functionality. The content of this paper is based on a presentation made at the 'Development of Advanced Battery Engineering Models' workshop held in Crystal City, Virginia in August 2001.

  10. Abnormal white matter structural networks characterize heroin-dependent individuals: a network analysis.

    PubMed

    Zhang, Ruibin; Jiang, Guihua; Tian, Junzhang; Qiu, Yingwei; Wen, Xue; Zalesky, Andrew; Li, Meng; Ma, Xiaofen; Wang, Junjing; Li, Shumei; Wang, Tianyue; Li, Changhong; Huang, Ruiwang

    2016-05-01

    Neuroimaging studies suggested that drug addiction is linked to abnormal brain functional connectivity. However, little is known about the alteration of brain white matter (WM) connectivity in addictive drug users and nearly no study has been performed to examine the alterations of brain WM connectivity in heroin-dependent individuals (HDIs). Diffusion tensor imaging (DTI) offers a comprehensive technique to map the whole brain WM connectivity in vivo. In this study, we acquired DTI datasets from 20 HDIs and 18 healthy controls and constructed their brain WM structural networks using a deterministic fibre tracking approach. Using graph theoretical analysis, we explored the global and nodal topological parameters of brain network for both groups and adopted a network-based statistic (NBS) approach to assess between-group differences in inter-regional WM connections. Statistical analysis indicated the global efficiency and network strength were significantly increased, but the characteristic path length was significantly decreased in the HDIs compared with the controls. We also found that in the HDIs, the nodal efficiency was significantly increased in the left prefrontal cortex, bilateral orbital frontal cortices and left anterior cingulate gyrus. Moreover, the NBS analysis revealed that in the HDIs, the significant increased connections were located in the paralimbic, orbitofrontal, prefrontal and temporal regions. Our results may reflect the disruption of whole brain WM structural networks in the HDIs. Our findings suggest that mapping brain WM structural network may be helpful for better understanding the neuromechanism of heroin addiction. PMID:25740690

  11. The Problem of Thresholding in Small-World Network Analysis

    PubMed Central

    Langer, Nicolas; Pedroni, Andreas; Jäncke, Lutz

    2013-01-01

    Graph theory deterministically models networks as sets of vertices, which are linked by connections. Such mathematical representation of networks, called graphs are increasingly used in neuroscience to model functional brain networks. It was shown that many forms of structural and functional brain networks have small-world characteristics, thus, constitute networks of dense local and highly effective distal information processing. Motivated by a previous small-world connectivity analysis of resting EEG-data we explored implications of a commonly used analysis approach. This common course of analysis is to compare small-world characteristics between two groups using classical inferential statistics. This however, becomes problematic when using measures of inter-subject correlations, as it is the case in commonly used brain imaging methods such as structural and diffusion tensor imaging with the exception of fibre tracking. Since for each voxel, or region there is only one data point, a measure of connectivity can only be computed for a group. To empirically determine an adequate small-world network threshold and to generate the necessary distribution of measures for classical inferential statistics, samples are generated by thresholding the networks on the group level over a range of thresholds. We believe that there are mainly two problems with this approach. First, the number of thresholded networks is arbitrary. Second, the obtained thresholded networks are not independent samples. Both issues become problematic when using commonly applied parametric statistical tests. Here, we demonstrate potential consequences of the number of thresholds and non-independency of samples in two examples (using artificial data and EEG data). Consequently alternative approaches are presented, which overcome these methodological issues. PMID:23301043

  12. Google matrix analysis of C.elegans neural network

    NASA Astrophysics Data System (ADS)

    Kandiah, V.; Shepelyansky, D. L.

    2014-05-01

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

  13. The Edinburgh human metabolic network reconstruction and its functional analysis

    PubMed Central

    Ma, Hongwu; Sorokin, Anatoly; Mazein, Alexander; Selkov, Alex; Selkov, Evgeni; Demin, Oleg; Goryanin, Igor

    2007-01-01

    A better understanding of human metabolism and its relationship with diseases is an important task in human systems biology studies. In this paper, we present a high-quality human metabolic network manually reconstructed by integrating genome annotation information from different databases and metabolic reaction information from literature. The network contains nearly 3000 metabolic reactions, which were reorganized into about 70 human-specific metabolic pathways according to their functional relationships. By analysis of the functional connectivity of the metabolites in the network, the bow-tie structure, which was found previously by structure analysis, is reconfirmed. Furthermore, the distribution of the disease related genes in the network suggests that the IN (substrates) subset of the bow-tie structure has more flexibility than other parts. PMID:17882155

  14. Topology analysis of social networks extracted from literature.

    PubMed

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

    2015-01-01

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

  15. Graph spectral analysis of protein interaction network evolution.

    PubMed

    Thorne, Thomas; Stumpf, Michael P H

    2012-10-01

    We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a bayesian approach and perform posterior density estimation using an approximate bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more naturally than previously used summary statistics such as the degree distribution. Furthermore, we include the effects of sampling into the analysis, to properly correct for the incompleteness of existing datasets, and have analysed the performance of our method under various degrees of sampling. We consider a number of models focusing not only on the biologically relevant class of duplication models, but also including models of scale-free network growth that have previously been claimed to describe such data. We find a preference for a duplication-divergence with linear preferential attachment model in the majority of the interaction datasets considered. We also illustrate how our method can be used to perform multi-model inference of network parameters to estimate properties of the full network from sampled data. PMID:22552917

  16. 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.

  17. Network generation and analysis of complex biomass conversion systems

    SciTech Connect

    Rangarajan, S.; Kaminski, T.; Van Wyk, E.; Bhan, A.; Daoutidis, P.

    2011-01-01

    A modular computational tool for automated generation and rule-based post-processing of reaction systems in biomass conversion is presented. Cheminformatics and graph theory algorithms are used to generate chemical transformations pertaining to heterogeneous and homogeneous chemistries in the automated rule-based network generator. A domain-specific language provides a user-friendly English-like chemistry specification interface to the network generator. A rule-based pathway analysis module enables the user to extract and query pathways from the reaction network. A demonstration of the features of this tool is presented using Fructose to 5-Hydroxymethylfurfural as a case study.

  18. Advancing interconnect density for spiking neural network hardware implementations using traffic-aware adaptive network-on-chip routers.

    PubMed

    Carrillo, Snaider; Harkin, Jim; McDaid, Liam; Pande, Sandeep; Cawley, Seamus; McGinley, Brian; Morgan, Fearghal

    2012-09-01

    The brain is highly efficient in how it processes information and tolerates faults. Arguably, the basic processing units are neurons and synapses that are interconnected in a complex pattern. Computer scientists and engineers aim to harness this efficiency and build artificial neural systems that can emulate the key information processing principles of the brain. However, existing approaches cannot provide the dense interconnect for the billions of neurons and synapses that are required. Recently a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an efficient, robust computing platform. However, the use of the NoC as an interconnection fabric for large-scale SNNs demands a good trade-off between scalability, throughput, neuron/synapse ratio and power consumption. This paper presents a novel traffic-aware, adaptive NoC router, which forms part of a proposed embedded mixed-signal SNN architecture called EMBRACE (EMulating Biologically-inspiRed ArChitectures in hardwarE). The proposed adaptive NoC router provides the inter-neuron connectivity for EMBRACE, maintaining router communication and avoiding dropped router packets by adapting to router traffic congestion. Results are presented on throughput, power and area performance analysis of the adaptive router using a 90 nm CMOS technology which outperforms existing NoCs in this domain. The adaptive behaviour of the router is also verified on a Stratix II FPGA implementation of a 4 × 2 router array with real-time traffic congestion. The presented results demonstrate the feasibility of using the proposed adaptive NoC router within the EMBRACE architecture to realise large-scale SNNs on embedded hardware. PMID:22561008

  19. Network analysis of EtOH-related candidate genes.

    PubMed

    Guo, An-Yuan; Sun, Jingchun; Jia, Peilin; Zhao, Zhongming

    2010-05-01

    Recently, we collected many large-scale datasets for alcohol dependence and EtOH response in five organisms and deposited them in our EtOH-related gene resource database (ERGR, http://bioinfo.mc.vanderbilt.edu/ERGR/). Based on multidimensional evidence among these datasets, we prioritized 57 EtOH-related candidate genes. To explore their biological roles, and the molecular mechanisms of EtOH response and alcohol dependence, we examined the features of these genes by the Gene Ontology (GO) term-enrichment test and network/pathway analysis. Our analysis revealed that these candidate genes were highly enriched in alcohol dependence/alcoholism and highly expressed in brain or liver tissues. All the significantly enriched GO terms were related to neurotransmitter systems or EtOH metabolic processes. Using the Ingenuity Pathway Analysis system, we found that these genes were involved in networks of neurological disease, cardiovascular disease, inflammatory response, and small molecular metabolism. Many key genes in signaling pathways were in the central position of these networks. Furthermore, our protein-protein interaction (PPI) network analysis suggested some novel candidate genes which also had evidence in the ERGR database. This study demonstrated that our candidate gene selection is effective and our network/pathway analysis is useful for uncovering the molecular mechanisms of EtOH response and alcohol dependence. This approach can be applied to study the features of candidate genes of other complex traits/phenotypes. PMID:20491071

  20. Compartmentalization analysis using discrete fracture network models

    SciTech Connect

    La Pointe, P.R.; Eiben, T.; Dershowitz, W.; Wadleigh, E.

    1997-08-01

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

  1. Compartmentalization analysis using discrete fracture network models

    SciTech Connect

    La Pointe, P.R.; Eiben, T.; Dershowitz, W.; Wadleigh, E.

    1997-12-31

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

  2. Functional connectivity and network analysis of midbrain and brainstem nuclei.

    PubMed

    Bär, Karl-Jürgen; de la Cruz, Feliberto; Schumann, Andy; Koehler, Stefanie; Sauer, Heinrich; Critchley, Hugo; Wagner, Gerd

    2016-07-01

    There is limited understanding of how monoamine-producing nuclei within midbrain and brainstem contribute to the formation and functional dynamics of brain networks across the human neocortex. We used resting state fMRI in 154 healthy participants to elucidate patterns of functional connectivity and network organization between cortical/subcortical regions and midbrain/brainstem nuclei. By means of univariate functional connectivity and graph-based analysis, we show that dopaminergic midbrain centers and the serotonergic dorsal raphe nucleus (DRN) are functionally integrated with the default mode network (DMN), whereas the remaining serotonergic raphe nuclei and the noradrenergic locus coeruleus are functionally integrated with the executive-control network (ECN). The majority of midbrain/brainstem nuclei show a high level of connectedness to other network modules classifying these nuclei as "connector" hubs. The additionally applied probabilistic independent component analysis (PICA) broadly corresponded with the results of the GT analysis, describing similar functionally-relevant cortical networks. Since monoaminergic neurotransmission is essential to neocortical function, and represents an important target for pharmacotherapy, our novel findings contribute to a comprehensive understanding of the functional organization of the human brain. PMID:27046112

  3. Imaging spectroscopic analysis at the Advanced Light Source

    SciTech Connect

    MacDowell, A. A.; Warwick, T.; Anders, S.; Lamble, G.M.; Martin, M.C.; McKinney, W.R.; Padmore, H.A.

    1999-05-12

    One of the major advances at the high brightness third generation synchrotrons is the dramatic improvement of imaging capability. There is a large multi-disciplinary effort underway at the ALS to develop imaging X-ray, UV and Infra-red spectroscopic analysis on a spatial scale from. a few microns to 10nm. These developments make use of light that varies in energy from 6meV to 15KeV. Imaging and spectroscopy are finding applications in surface science, bulk materials analysis, semiconductor structures, particulate contaminants, magnetic thin films, biology and environmental science. This article is an overview and status report from the developers of some of these techniques at the ALS. The following table lists all the currently available microscopes at the. ALS. This article will describe some of the microscopes and some of the early applications.

  4. Advanced Video Analysis Needs for Human Performance Evaluation

    NASA Technical Reports Server (NTRS)

    Campbell, Paul D.

    1994-01-01

    Evaluators of human task performance in space missions make use of video as a primary source of data. Extraction of relevant human performance information from video is often a labor-intensive process requiring a large amount of time on the part of the evaluator. Based on the experiences of several human performance evaluators, needs were defined for advanced tools which could aid in the analysis of video data from space missions. Such tools should increase the efficiency with which useful information is retrieved from large quantities of raw video. They should also provide the evaluator with new analytical functions which are not present in currently used methods. Video analysis tools based on the needs defined by this study would also have uses in U.S. industry and education. Evaluation of human performance from video data can be a valuable technique in many industrial and institutional settings where humans are involved in operational systems and processes.

  5. Tool for Sizing Analysis of the Advanced Life Support System

    NASA Technical Reports Server (NTRS)

    Yeh, Hue-Hsie Jannivine; Brown, Cheryl B.; Jeng, Frank J.

    2005-01-01

    Advanced Life Support Sizing Analysis Tool (ALSSAT) is a computer model for sizing and analyzing designs of environmental-control and life support systems (ECLSS) for spacecraft and surface habitats involved in the exploration of Mars and Moon. It performs conceptual designs of advanced life support (ALS) subsystems that utilize physicochemical and biological processes to recycle air and water, and process wastes in order to reduce the need of resource resupply. By assuming steady-state operations, ALSSAT is a means of investigating combinations of such subsystems technologies and thereby assisting in determining the most cost-effective technology combination available. In fact, ALSSAT can perform sizing analysis of the ALS subsystems that are operated dynamically or steady in nature. Using the Microsoft Excel spreadsheet software with Visual Basic programming language, ALSSAT has been developed to perform multiple-case trade studies based on the calculated ECLSS mass, volume, power, and Equivalent System Mass, as well as parametric studies by varying the input parameters. ALSSAT s modular format is specifically designed for the ease of future maintenance and upgrades.

  6. Fast discrimination of danshen from different geographical areas by NIR spectroscopy and advanced cluster analysis method

    NASA Astrophysics Data System (ADS)

    Li, Ning; Wang, Yan; Xu, Kexin

    2006-09-01

    Near infrared (NIR) diffuse reflection spectroscopy has been an effective way to perform quantitative analysis without the requirement of sample pretreatnient. In this paper, NIR Fourier transform infrared (FTIR) spectroscopy has been introduced to probe spectral features of traditional Chinese medicine Danshen. Infrared fingerprint spectra of Danshen can be established. Influence of differentiation of spectrum is also discussed. After pretreatment and derivation on the spectral data, methods of principal analysis (PCA), soft independent modeling of class analogy (SIMCA) and Artificial Neural Network (ANN) are combined to sort the geographical origins of 53 samples by local modeling. The result show that, as a basis of the other two methods, PCA is a more efficient one for identifying the geographical origins of Danshen. Combining SIMCA with PCA, an effective model is built to analyze the data after normalization and differentiation, the correct identification rate reaches above 90%. Then 36 samples are chosen as training set while other 17 samples being verifying set. Using ANN-based Back Propagation method, after proper training of BP network, the origins of Danshen are completely classified. Therefore, combined with advanced mathematical analysis, NIR diffuse spectroscopy can be a novel and rapid way to accurately evaluate the origin of Chinese medicine, and also to accelerate the modernization process of Chinese drugs.

  7. Performance analysis of local area networks

    NASA Technical Reports Server (NTRS)

    Alkhatib, Hasan S.; Hall, Mary Grace

    1990-01-01

    A simulation of the TCP/IP protocol running on a CSMA/CD data link layer was described. The simulation was implemented using the simula language, and object oriented discrete event language. It allows the user to set the number of stations at run time, as well as some station parameters. Those parameters are the interrupt time and the dma transfer rate for each station. In addition, the user may configure the network at run time with stations of differing characteristics. Two types are available, and the parameters of both types are read from input files at run time. The parameters include the dma transfer rate, interrupt time, data rate, average message size, maximum frame size and the average interarrival time of messages per station. The information collected for the network is the throughput and the mean delay per packet. For each station, the number of messages attempted as well as the number of messages successfully transmitted is collected in addition to the throughput and mean packet delay per station.

  8. Neural network analysis for hazardous waste characterization

    SciTech Connect

    Misra, M.; Pratt, L.Y.; Farris, C.

    1995-12-31

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

  9. Sandia`s research network for Supercomputing `93: A demonstration of advanced technologies for building high-performance networks

    SciTech Connect

    Gossage, S.A.; Vahle, M.O.

    1993-12-01

    Supercomputing `93, a high-performance computing and communications conference, was held November 15th through 19th, 1993 in Portland, Oregon. For the past two years, Sandia National Laboratories has used this conference to showcase and focus its communications and networking endeavors. At the 1993 conference, the results of Sandia`s efforts in exploring and utilizing Asynchronous Transfer Mode (ATM) and Synchronous Optical Network (SONET) technologies were vividly demonstrated by building and operating three distinct networks. The networks encompassed a Switched Multimegabit Data Service (SMDS) network running at 44.736 megabits per second, an ATM network running on a SONET circuit at the Optical Carrier (OC) rate of 155.52 megabits per second, and a High Performance Parallel Interface (HIPPI) network running over a 622.08 megabits per second SONET circuit. The SMDS and ATM networks extended from Albuquerque, New Mexico to the showroom floor, while the HIPPI/SONET network extended from Beaverton, Oregon to the showroom floor. This paper documents and describes these networks.

  10. Adaptive Modeling, Engineering Analysis and Design of Advanced Aerospace Vehicles

    NASA Technical Reports Server (NTRS)

    Mukhopadhyay, Vivek; Hsu, Su-Yuen; Mason, Brian H.; Hicks, Mike D.; Jones, William T.; Sleight, David W.; Chun, Julio; Spangler, Jan L.; Kamhawi, Hilmi; Dahl, Jorgen L.

    2006-01-01

    This paper describes initial progress towards the development and enhancement of a set of software tools for rapid adaptive modeling, and conceptual design of advanced aerospace vehicle concepts. With demanding structural and aerodynamic performance requirements, these high fidelity geometry based modeling tools are essential for rapid and accurate engineering analysis at the early concept development stage. This adaptive modeling tool was used for generating vehicle parametric geometry, outer mold line and detailed internal structural layout of wing, fuselage, skin, spars, ribs, control surfaces, frames, bulkheads, floors, etc., that facilitated rapid finite element analysis, sizing study and weight optimization. The high quality outer mold line enabled rapid aerodynamic analysis in order to provide reliable design data at critical flight conditions. Example application for structural design of a conventional aircraft and a high altitude long endurance vehicle configuration are presented. This work was performed under the Conceptual Design Shop sub-project within the Efficient Aerodynamic Shape and Integration project, under the former Vehicle Systems Program. The project objective was to design and assess unconventional atmospheric vehicle concepts efficiently and confidently. The implementation may also dramatically facilitate physics-based systems analysis for the NASA Fundamental Aeronautics Mission. In addition to providing technology for design and development of unconventional aircraft, the techniques for generation of accurate geometry and internal sub-structure and the automated interface with the high fidelity analysis codes could also be applied towards the design of vehicles for the NASA Exploration and Space Science Mission projects.

  11. 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.

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

    PubMed

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

    2015-01-01

    We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. PMID:25933413

  13. Bank-Firm Credit Network in Japan: An Analysis of a Bipartite Network

    PubMed Central

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

    2015-01-01

    We investigate the networked nature of the Japanese credit market. Our investigation is performed with tools of network science. In our investigation we perform community detection with an algorithm which is identifying communities composed of both banks and firms. We show that the communities obtained by directly working on the bipartite network carry information about the networked nature of the Japanese credit market. Our analysis is performed for each calendar year during the time period from 1980 to 2011. To investigate the time evolution of the networked structure of the credit market we introduce a new statistical method to track the time evolution of detected communities. We then characterize the time evolution of communities by detecting for each time evolving set of communities the over-expression of attributes of firms and banks. Specifically, we consider as attributes the economic sector and the geographical location of firms and the type of banks. In our 32-year-long analysis we detect a persistence of the over-expression of attributes of communities of banks and firms together with a slow dynamic of changes from some specific attributes to new ones. Our empirical observations show that the credit market in Japan is a networked market where the type of banks, geographical location of firms and banks, and economic sector of the firm play a role in shaping the credit relationships between banks and firms. PMID:25933413

  14. Biological Network Inference and Analysis using SEBINI and CABIN

    SciTech Connect

    Taylor, Ronald C.; Singhal, Mudita

    2008-01-01

    Attaining a detailed understanding of the various biological networks in an organism lies at the core of the emerging discipline of systems biology. A precise description of the relationships formed between genes, mRNA molecules, and proteins is a necessary step toward a complete description of the dynamic behavior of an organism at the cellular level; and towards intelligent, efficient and directed modification of an organism. The importance of understanding such regulatory, signaling, and interaction networks has fueled the development of numerous in silico inference algorithms, as well as new experimental techniques and a growing collection of public databases. The Software Environment for BIological Network Inference (SEBINI) has been created to provide an interactive environment for the deployment, evaluation, and improvement of algorithms used to reconstruct the structure of biological regulatory and interaction networks. SEBINI can be used to analyze high-throughput gene expression, protein expression, or protein activation data via a suite of state-of-the-art network inference algorithms. It also allows algorithm developers to compare and train network inference methods on artificial networks and simulated gene expression perturbation data. SEBINI can therefore be used by software developers wishing to evaluate, refine, or combine inference techniques, as well as by bioinformaticians analyzing experimental data. Networks inferred from the SEBINI software platform can be further analyzed using the Collective Analysis of Biological Interaction Networks (CABIN) tool, which is exploratory data analysis software that enables integration and analysis of protein-protein interaction and gene-to-gene regulatory evidence obtained from multiple sources. The collection of edges in public databases, along with the confidence held in each edge (if available), can be fed into CABIN as one “evidence network”, using the Cytoscape SIF file format. Using CABIN, one may

  15. A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

    NASA Astrophysics Data System (ADS)

    McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

    2013-12-01

    among members, we have, collectively, been able to advance all of our efforts. The member institutions, through regular face-to-face workshops and an online community, share practices in creation and cataloging of datasets, new methods for delivering content via SOS, and updates on the SOS system and software. One hallmark of the SOS Users Collaborative Network is that it exemplifies an ideal partnership between federal science agencies and informal science education institutions. The science agencies (including NOAA, NASA, and the Department of Energy) provide continuously updated global datasets, scientific expertise, funding, and support. In turn, museums act as trusted public providers of scientific information, provide audience-appropriate presentations, localized relevance to global phenomena and a forum for discussing the complex science and repercussions of global change. We will discuss the characteristics of this Network that maximize collaboration and what we're learning as a community to improve climate literacy.

  16. Advanced probabilistic risk analysis using RAVEN and RELAP-7

    SciTech Connect

    Rabiti, Cristian; Alfonsi, Andrea; Mandelli, Diego; Cogliati, Joshua; Kinoshita, Robert

    2014-06-01

    RAVEN, under the support of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program [1], is advancing its capability to perform statistical analyses of stochastic dynamic systems. This is aligned with its mission to provide the tools needed by the Risk Informed Safety Margin Characterization (RISMC) path-lead [2] under the Department Of Energy (DOE) Light Water Reactor Sustainability program [3]. In particular this task is focused on the synergetic development with the RELAP-7 [4] code to advance the state of the art on the safety analysis of nuclear power plants (NPP). The investigation of the probabilistic evolution of accident scenarios for a complex system such as a nuclear power plant is not a trivial challenge. The complexity of the system to be modeled leads to demanding computational requirements even to simulate one of the many possible evolutions of an accident scenario (tens of CPU/hour). At the same time, the probabilistic analysis requires thousands of runs to investigate outcomes characterized by low probability and severe consequence (tail problem). The milestone reported in June of 2013 [5] described the capability of RAVEN to implement complex control logic and provide an adequate support for the exploration of the probabilistic space using a Monte Carlo sampling strategy. Unfortunately the Monte Carlo approach is ineffective with a problem of this complexity. In the following year of development, the RAVEN code has been extended with more sophisticated sampling strategies (grids, Latin Hypercube, and adaptive sampling). This milestone report illustrates the effectiveness of those methodologies in performing the assessment of the probability of core damage following the onset of a Station Black Out (SBO) situation in a boiling water reactor (BWR). The first part of the report provides an overview of the available probabilistic analysis capabilities, ranging from the different types of distributions available, possible sampling

  17. Structure network analysis to gain insights into GPCR function.

    PubMed

    Fanelli, Francesca; Felline, Angelo; Raimondi, Francesco; Seeber, Michele

    2016-04-15

    G protein coupled receptors (GPCRs) are allosteric proteins whose functioning fundamentals are the communication between the two poles of the helix bundle. Protein structure network (PSN) analysis is one of the graph theory-based approaches currently used to investigate the structural communication in biomolecular systems. Information on system's dynamics can be provided by atomistic molecular dynamics (MD) simulations or coarse grained elastic network models paired with normal mode analysis (ENM-NMA). The present review article describes the application of PSN analysis to uncover the structural communication in G protein coupled receptors (GPCRs). Strategies to highlight changes in structural communication upon misfolding, dimerization and activation are described. Focus is put on the ENM-NMA-based strategy applied to the crystallographic structures of rhodopsin in its inactive (dark) and signalling active (meta II (MII)) states, highlighting changes in structure network and centrality of the retinal chromophore in differentiating the inactive and active states of the receptor. PMID:27068978

  18. Reducing the power consumption in LTE-Advanced wireless access networks by a capacity based deployment tool

    NASA Astrophysics Data System (ADS)

    Deruyck, Margot; Joseph, Wout; Tanghe, Emmeric; Martens, Luc

    2014-09-01

    As both the bit rate required by applications on mobile devices and the number of those mobile devices are steadily growing, wireless access networks need to be expanded. As wireless networks also consume a lot of energy, it is important to develop energy-efficient wireless access networks in the near future. In this study, a capacity-based deployment tool for the design of energy-efficient wireless access networks is proposed. Capacity-based means that the network responds to the instantaneous bit rate requirements of the users active in the selected area. To the best of our knowledge, such a deployment tool for energy-efficient wireless access networks has never been presented before. This deployment tool is applied to a realistic case in Ghent, Belgium, to investigate three main functionalities incorporated in LTE-Advanced: carrier aggregation, heterogeneous deployments, and Multiple-Input Multiple-Output (MIMO). The results show that it is recommended to introduce femtocell base stations, supporting both MIMO and carrier aggregation, into the network (heterogeneous deployment) to reduce the network's power consumption. For the selected area and the assumptions made, this results in a power consumption reduction up to 70%. Introducing femtocell base stations without MIMO and carrier aggregation can already result in a significant power consumption reduction of 38%.

  19. Detecting network modules in fMRI time series: a weighted network analysis approach.

    PubMed

    Mumford, Jeanette A; Horvath, Steve; Oldham, Michael C; Langfelder, Peter; Geschwind, Daniel H; Poldrack, Russell A

    2010-10-01

    Many network analyses of fMRI data begin by defining a set of regions, extracting the mean signal from each region and then analyzing the correlations between regions. One essential question that has not been addressed in the literature is how to best define the network neighborhoods over which a signal is combined for network analyses. Here we present a novel unsupervised method for the identification of tightly interconnected voxels, or modules, from fMRI data. This approach, weighted voxel coactivation network analysis (WVCNA), is based on a method that was originally developed to find modules of genes in gene networks. This approach differs from many of the standard network approaches in fMRI in that connections between voxels are described by a continuous measure, whereas typically voxels are considered to be either connected or not connected depending on whether the correlation between the two voxels survives a hard threshold value. Additionally, instead of simply using pairwise correlations to describe the connection between two voxels, WVCNA relies on a measure of topological overlap, which not only compares how correlated two voxels are but also the degree to which the pair of voxels is highly correlated with the same other voxels. We demonstrate the use of WVCNA to parcellate the brain into a set of modules that are reliably detected across data within the same subject and across subjects. In addition we compare WVCNA to ICA and show that the WVCNA modules have some of the same structure as the ICA components, but tend to be more spatially focused. We also demonstrate the use of some of the WVCNA network metrics for assessing a voxel's membership to a module and also how that voxel relates to other modules. Last, we illustrate how WVCNA modules can be used in a network analysis to find connections between regions of the brain and show that it produces reasonable results. PMID:20553896

  20. Detecting network modules in fMRI time series: A weighted network analysis approach

    PubMed Central

    Mumford, Jeanette A; Horvath, Steve; Oldham, Michael C.; Langfelder, Peter; Geschwind, Daniel H.; Poldrack, Russell A

    2010-01-01

    Many network analyses of fMRI data begin by defining a set of regions, extracting the mean signal from each region and then analyzing the correlations between regions. One essential question that has not been addressed in the literature is how to best define the network neighborhoods over which a signal is combined for network analyses. Here we present a novel unsupervised method for the identification of tightly interconnected voxels, or modules, from fMRI data. This approach, weighted voxel coactivation network analysis (WVCNA) is based on a method that was originally developed to find modules of genes in gene networks. This approach differs from many of the standard network approaches in fMRI in that connections between voxels are described by a continuous measure, whereas typically voxels are considered to be either connected or not connected depending on whether the correlation between the two voxels survives a hard threshold value. Additionally, instead of simply using pairwise correlations to describe the connection between two voxels, WVCNA relies on a measure of topological overlap, which not only compares how correlated two voxels are, but also the degree to which the pair of voxels is highly correlated with the same other voxels. We demonstrate the use of WVCNA to parcellate the brain into a set of modules that are reliably detected across data within the same subject and across subjects. In addition we compare WVCNA to ICA and show that the WVCNA modules have some of the same structure as the ICA components, but tend to be more spatially focused. We also demonstrate the use of some of the WVCNA network metrics for assessing a voxel’s membership to a module and also how that voxel relates to other modules. Last, we illustrate how WVCNA modules can be used in a network analysis to find connections between regions of the brain and show that it produces reasonable results. PMID:20553896