Science.gov

Sample records for large sharing networks

  1. Fixed Access Network Sharing

    NASA Astrophysics Data System (ADS)

    Cornaglia, Bruno; Young, Gavin; Marchetta, Antonio

    2015-12-01

    Fixed broadband network deployments are moving inexorably to the use of Next Generation Access (NGA) technologies and architectures. These NGA deployments involve building fiber infrastructure increasingly closer to the customer in order to increase the proportion of fiber on the customer's access connection (Fibre-To-The-Home/Building/Door/Cabinet… i.e. FTTx). This increases the speed of services that can be sold and will be increasingly required to meet the demands of new generations of video services as we evolve from HDTV to "Ultra-HD TV" with 4k and 8k lines of video resolution. However, building fiber access networks is a costly endeavor. It requires significant capital in order to cover any significant geographic coverage. Hence many companies are forming partnerships and joint-ventures in order to share the NGA network construction costs. One form of such a partnership involves two companies agreeing to each build to cover a certain geographic area and then "cross-selling" NGA products to each other in order to access customers within their partner's footprint (NGA coverage area). This is tantamount to a bi-lateral wholesale partnership. The concept of Fixed Access Network Sharing (FANS) is to address the possibility of sharing infrastructure with a high degree of flexibility for all network operators involved. By providing greater configuration control over the NGA network infrastructure, the service provider has a greater ability to define the network and hence to define their product capabilities at the active layer. This gives the service provider partners greater product development autonomy plus the ability to differentiate from each other at the active network layer.

  2. Expansible quantum secret sharing network

    NASA Astrophysics Data System (ADS)

    Sun, Ying; Xu, Sheng-Wei; Chen, Xiu-Bo; Niu, Xin-Xin; Yang, Yi-Xian

    2013-08-01

    In the practical applications, member expansion is a usual demand during the development of a secret sharing network. However, there are few consideration and discussion on network expansibility in the existing quantum secret sharing schemes. We propose an expansible quantum secret sharing scheme with relatively simple and economical quantum resources and show how to split and reconstruct the quantum secret among an expansible user group in our scheme. Its trait, no requirement of any agent's assistant during the process of member expansion, can help to prevent potential menaces of insider cheating. We also give a discussion on the security of this scheme from three aspects.

  3. Sharing Writing through Computer Networking.

    ERIC Educational Resources Information Center

    Fey, Marion H.

    1997-01-01

    Suggests computer networking can support the essential purposes of the collaborative-writing movement, offering opportunities for sharing writing. Notes that literacy teachers are exploring the connectivity of computer networking through numerous designs that use either real-time or asynchronous communication. Discusses new roles for students and…

  4. Data sharing and intellectual property in a genomic epidemiology network: policies for large-scale research collaboration.

    PubMed Central

    Chokshi, Dave A.; Parker, Michael; Kwiatkowski, Dominic P.

    2006-01-01

    Genomic epidemiology is a field of research that seeks to improve the prevention and management of common diseases through an understanding of their molecular origins. It involves studying thousands of individuals, often from different populations, with exacting techniques. The scale and complexity of such research has required the formation of research consortia. Members of these consortia need to agree on policies for managing shared resources and handling genetic data. Here we consider data-sharing and intellectual property policies for an international research consortium working on the genomic epidemiology of malaria. We outline specific guidelines governing how samples and data are transferred among its members; how results are released into the public domain; when to seek protection for intellectual property; and how intellectual property should be managed. We outline some pragmatic solutions founded on the basic principles of promoting innovation and access. PMID:16710548

  5. Analysis and improvement of vehicle information sharing networks

    NASA Astrophysics Data System (ADS)

    Gong, Hang; He, Kun; Qu, Yingchun; Wang, Pu

    2016-06-01

    Based on large-scale mobile phone data, mobility demand was estimated and locations of vehicles were inferred in the Boston area. Using the spatial distribution of vehicles, we analyze the vehicle information sharing network generated by the vehicle-to-vehicle (V2V) communications. Although a giant vehicle cluster is observed, the coverage and the efficiency of the information sharing network remain limited. Consequently, we propose a method to extend the information sharing network's coverage by adding long-range connections between targeted vehicle clusters. Furthermore, we employ the optimal design strategy discovered in square lattice to improve the efficiency of the vehicle information sharing network.

  6. Knowledge Searching and Sharing on Virtual Networks.

    ERIC Educational Resources Information Center

    Helokunnas, Tuija; Herrala, Juha

    2001-01-01

    Describes searching and sharing of knowledge on virtual networks, based on experiences gained when hosting virtual knowledge networks at Tampere University of Technology in Finland. Discusses information and knowledge management studies; role of information technology in knowledge searching and sharing; implementation and experiences of the…

  7. Distributed shared memory for roaming large volumes.

    PubMed

    Castanié, Laurent; Mion, Christophe; Cavin, Xavier; Lévy, Bruno

    2006-01-01

    We present a cluster-based volume rendering system for roaming very large volumes. This system allows to move a gigabyte-sized probe inside a total volume of several tens or hundreds of gigabytes in real-time. While the size of the probe is limited by the total amount of texture memory on the cluster, the size of the total data set has no theoretical limit. The cluster is used as a distributed graphics processing unit that both aggregates graphics power and graphics memory. A hardware-accelerated volume renderer runs in parallel on the cluster nodes and the final image compositing is implemented using a pipelined sort-last rendering algorithm. Meanwhile, volume bricking and volume paging allow efficient data caching. On each rendering node, a distributed hierarchical cache system implements a global software-based distributed shared memory on the cluster. In case of a cache miss, this system first checks page residency on the other cluster nodes instead of directly accessing local disks. Using two Gigabit Ethernet network interfaces per node, we accelerate data fetching by a factor of 4 compared to directly accessing local disks. The system also implements asynchronous disk access and texture loading, which makes it possible to overlap data loading, volume slicing and rendering for optimal volume roaming. PMID:17080865

  8. Designing a Networked-Sharing Construction Environment.

    ERIC Educational Resources Information Center

    Lin, Sunny; Sun, Chuen-Tsai; Kao, Gloria

    2002-01-01

    Discusses group learning on the Internet and problems of unequal participation and describes the development of a Web-based learning system called NetShare (Networked Sharing Construction Environment) that uses a cooperative-competitive learning strategy to facilitate participants' equal contributions. Reports preliminary results of a study with…

  9. Traffic sharing algorithms for hybrid mobile networks

    NASA Technical Reports Server (NTRS)

    Arcand, S.; Murthy, K. M. S.; Hafez, R.

    1995-01-01

    In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

  10. Network Adaptive Deadband: NCS Data Flow Control for Shared Networks

    PubMed Central

    Díaz-Cacho, Miguel; Delgado, Emma; Prieto, José A. G.; López, Joaquín

    2012-01-01

    This paper proposes a new middleware solution called Network Adaptive Deadband (NAD) for long time operation of Networked Control Systems (NCS) through the Internet or any shared network based on IP technology. The proposed middleware takes into account the network status and the NCS status, to improve the global system performance and to share more effectively the network by several NCS and sensor/actuator data flows. Relationship between network status and NCS status is solved with a TCP-friendly transport flow control protocol and the deadband concept, relating deadband value and transmission throughput. This creates a deadband-based flow control solution. Simulation and experiments in shared networks show that the implemented network adaptive deadband has better performance than an optimal constant deadband solution in the same circumstances. PMID:23208556

  11. Sharing Clouds: Showing, Distributing, and Sharing Large Point Datasets

    NASA Astrophysics Data System (ADS)

    Grigsby, S.

    2012-12-01

    Sharing large data sets with colleagues and the general public presents a unique technological challenge for scientists. In addition to large data volumes, there are significant challenges in representing data that is often irregular, multidimensional and spatial in nature. For derived data products, additional challenges exist in displaying and providing provenance data. For this presentation, several open source technologies are demonstrated for the remote display and access of large irregular point data sets. These technologies and techniques include the remote viewing of point data using HTML5 and OpenGL, which provides a highly accessible preview of the data sets for a range of audiences. Intermediate levels of accessibility and high levels of interactivity are accomplished with technologies such as wevDAV, which allows collaborators to run analysis on local clients, using data stored and administered on remote servers. Remote processing and analysis, including provenance tracking, will be discussed at the workgroup level. The data sets used for this presentation include data acquired from the NSF funded National Center for Airborne Laser Mapping (NCALM), and data acquired for research and instructional use in NASA's Student Airborne Research Program (SARP). These datasets include Light Ranging And Detection (LiDAR) point clouds ranging in size from several hundred thousand to several hundred million data points; the techniques and technologies discussed are applicable to other forms of irregular point data.

  12. Creating, documenting and sharing network models.

    PubMed

    Crook, Sharon M; Bednar, James A; Berger, Sandra; Cannon, Robert; Davison, Andrew P; Djurfeldt, Mikael; Eppler, Jochen; Kriener, Birgit; Furber, Steve; Graham, Bruce; Plesser, Hans E; Schwabe, Lars; Smith, Leslie; Steuber, Volker; van Albada, Sacha

    2012-01-01

    As computational neuroscience matures, many simulation environments are available that are useful for neuronal network modeling. However, methods for successfully documenting models for publication and for exchanging models and model components among these projects are still under development. Here we briefly review existing software and applications for network model creation, documentation and exchange. Then we discuss a few of the larger issues facing the field of computational neuroscience regarding network modeling and suggest solutions to some of these problems, concentrating in particular on standardized network model terminology, notation, and descriptions and explicit documentation of model scaling. We hope this will enable and encourage computational neuroscientists to share their models more systematically in the future. PMID:22994683

  13. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 2 2012-10-01 2012-10-01 false Shared wireless broadband network. 27.1305... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1305 Shared wireless broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private...

  14. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 5 2012-10-01 2012-10-01 false Shared wireless broadband network. 90.1405... SERVICES PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1405 Shared wireless broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private...

  15. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 5 2011-10-01 2011-10-01 false Network sharing agreement. 90.1410 Section 90... PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1410 Network sharing agreement... related entities as the Commission may require or allow will be governed by the Network Sharing...

  16. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Network sharing agreement. 90.1410 Section 90... PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1410 Network sharing agreement... related entities as the Commission may require or allow will be governed by the Network Sharing...

  17. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 5 2011-10-01 2011-10-01 false Shared wireless broadband network. 90.1405... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network....

  18. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Shared wireless broadband network. 27.1305... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network....

  19. 47 CFR 27.1305 - Shared wireless broadband network.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Shared wireless broadband network. 27.1305... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network....

  20. 47 CFR 90.1405 - Shared wireless broadband network.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 5 2010-10-01 2010-10-01 false Shared wireless broadband network. 90.1405... broadband network. The Shared Wireless Broadband Network developed by the 700 MHz Public/Private Partnership must be designed to meet requirements associated with a nationwide, public safety broadband network....

  1. Secure Peer-to-Peer Networks for Scientific Information Sharing

    NASA Technical Reports Server (NTRS)

    Karimabadi, Homa

    2012-01-01

    The most common means of remote scientific collaboration today includes the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. With the growth of broadband Internet, there has been a desire to share large files (movies, files, scientific data files) over the Internet. Email has limits on the size of files that can be attached and transmitted. FTP is often used to share large files, but this requires the user to set up an FTP site for which it is hard to set group privileges, it is not straightforward for everyone, and the content is not searchable. Peer-to-peer technology (P2P), which has been overwhelmingly successful in popular content distribution, is the basis for development of a scientific collaboratory called Scientific Peer Network (SciPerNet). This technology combines social networking with P2P file sharing. SciPerNet will be a standalone application, written in Java and Swing, thus insuring portability to a number of different platforms. Some of the features include user authentication, search capability, seamless integration with a data center, the ability to create groups and social networks, and on-line chat. In contrast to P2P networks such as Gnutella, Bit Torrent, and others, SciPerNet incorporates three design elements that are critical to application of P2P for scientific purposes: User authentication, Data integrity validation, Reliable searching SciPerNet also provides a complementary solution to virtual observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase scientific returns from NASA missions. As such, SciPerNet can serve a two-fold purpose for NASA: a cost-savings software as well as a productivity tool for scientists working with data from NASA missions.

  2. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 47 Telecommunication 2 2010-10-01 2010-10-01 false Network sharing agreement. 27.1310 Section 27... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1310 Network sharing..., and related entities as the Commission may require or allow will be governed by the Network...

  3. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... 47 Telecommunication 2 2011-10-01 2011-10-01 false Network sharing agreement. 27.1310 Section 27... MISCELLANEOUS WIRELESS COMMUNICATIONS SERVICES 700 MHz Public/Private Partnership § 27.1310 Network sharing..., and related entities as the Commission may require or allow will be governed by the Network...

  4. Querying Large Biological Network Datasets

    ERIC Educational Resources Information Center

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  5. Learning Theory for Collaborative Large Shared Digital Spaces

    ERIC Educational Resources Information Center

    McGivern, Daniela; Morgan, Michael; Butler, Matthew

    2012-01-01

    This research applies Socio-Cultural theory and Distributed Cognition/Activity theory to conceptualize the design of collaborative learning activities in large shared digital spaces. The paper begins by providing a summary of previous work in the creation of a technology platform for large shared digital spaces. It then details how Socio-Cultural…

  6. Shared Access Optical Networks For The Local Loop

    NASA Astrophysics Data System (ADS)

    Payne, D. B.; Stern, J. R.

    1988-09-01

    The application of single mode fibre to the local network environment opens up major opportunities for service provision via shared access networks. Previous technologies (copper pair, coaxial cable and multimode fibre) had bandwidth limitation problems that placed a severe restriction on both the level of resource sharing and the service package that could be delivered. The enormous bandwidth capability of single mode fibre can be used to provide significant resource sharing without incurring fundamental restrictions on the capacity of the services carried. The paper briefly outlines some of the activities within British Telecom on shared access systems. Early systems concepts were either based on fibre feeders to remote multiplexers for the delivery of telephony and data services to large customers or the use of advanced wavelength multiplexing techniques over passive optical networks for the transmission of wideband services to business and residential customers. Recently activity has concentrated on a passive optical network that shows good potential for the economic provision of telephony services. The structure of the network allows the later addition of broadband services via additional wavelengths without disturbing existing telephony/data customers. The basic network has a fibre feeder from the exchange to passive optical splitters housed at the Cabinet and Distribution Points (DP). Each customer receives a fibre from DP and via this a TDM multiplex broadcast from the exchange which carries the customer's traffic. The customer equipment accesses the time slots destined for the customer and delivers the data via a suitable interface to provide the services required. Customers transmit back to the exchange in a time multiplex synchronised by a ranging protocol that sets an appropriate delay in the customer equipment to avoid collisions at the optical combiners in the DPs and Cabinet. Present studies are considering a total optical split of 128 ways with a

  7. Detecting communities in large networks

    NASA Astrophysics Data System (ADS)

    Capocci, A.; Servedio, V. D. P.; Caldarelli, G.; Colaiori, F.

    2005-07-01

    We develop an algorithm to detect community structure in complex networks. The algorithm is based on spectral methods and takes into account weights and link orientation. Since the method detects efficiently clustered nodes in large networks even when these are not sharply partitioned, it turns to be specially suitable for the analysis of social and information networks. We test the algorithm on a large-scale data-set from a psychological experiment of word association. In this case, it proves to be successful both in clustering words, and in uncovering mental association patterns.

  8. Shared Service Center vs. Shared Service Network: A Multiple Case Study Analysis of Factors Impacting on Shared Service Configurations

    NASA Astrophysics Data System (ADS)

    Becker, Jörg; Niehaves, Björn; Krause, Andreas

    Shared services have proven to be a key element when it comes to increasing government efficiency by collaboration. Here, we seek to investigate into the shared services phenomenon in the context of government reforms. For this purpose, an interview and document analysis-based multiple case study has been conducted in Germany. The qualitative analysis covers two shared service implementations on the local government level and identifies important preconditions for shared service emergence, namely cost pressure as motive, the existence of key actors promoting the topic and the existence of prior cooperation. Moreover, it is shown that the structure of such previous cooperation determines, if shared services are being organised in a centralised (shared service centre) or decentralised format (shared service network).

  9. 77 FR 50712 - Information Collection: Southern Alaska Sharing Network and Subsistence Study; Proposed...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-08-22

    ... Bureau of Ocean Energy Management Information Collection: Southern Alaska Sharing Network and Subsistence... in Alaska, ``Southern Alaska Sharing Network and Subsistence Study.'' DATES: Submit written comments.... Title: Southern Alaska Sharing Network and Subsistence Study. Abstract: The Bureau of Ocean...

  10. Food-Sharing Networks in Lamalera, Indonesia: Status, Sharing, and Signaling.

    PubMed

    Nolin, David A

    2012-07-01

    Costly signaling has been proposed as a possible mechanism to explain food sharing in foraging populations. This sharing-as-signaling hypothesis predicts an association between sharing and status. Using exponential random graph modeling (ERGM), this prediction is tested on a social network of between-household food-sharing relationships in the fishing and sea-hunting village of Lamalera, Indonesia. Previous analyses (Nolin 2010) have shown that most sharing in Lamalera is consistent with reciprocal altruism. The question addressed here is whether any additional variation may be explained as sharing-as-signaling by high-status households. The results show that high-status households both give and receive more than other households, a pattern more consistent with reciprocal altruism than costly signaling. However, once the propensity to reciprocate and household productivity are controlled, households of men holding leadership positions show greater odds of unreciprocated giving when compared to households of non-leaders. This pattern of excessive giving by leaders is consistent with the sharing-as-signaling hypothesis. Wealthy households show the opposite pattern, giving less and receiving more than other households. These households may reciprocate in a currency other than food or their wealth may attract favor-seeking behavior from others. Overall, status covariates explain little variation in the sharing network as a whole, and much of the sharing observed by high-status households is best explained by the same factors that explain sharing by other households. This pattern suggests that multiple mechanisms may operate simultaneously to promote sharing in Lamalera and that signaling may motivate some sharing by some individuals even within sharing regimes primarily maintained by other mechanisms. PMID:22822299

  11. Food-Sharing Networks in Lamalera, Indonesia: Status, Sharing, and Signaling

    PubMed Central

    Nolin, David A.

    2012-01-01

    Costly signaling has been proposed as a possible mechanism to explain food sharing in foraging populations. This sharing-as-signaling hypothesis predicts an association between sharing and status. Using exponential random graph modeling (ERGM), this prediction is tested on a social network of between-household food-sharing relationships in the fishing and sea-hunting village of Lamalera, Indonesia. Previous analyses (Nolin 2010) have shown that most sharing in Lamalera is consistent with reciprocal altruism. The question addressed here is whether any additional variation may be explained as sharing-as-signaling by high-status households. The results show that high-status households both give and receive more than other households, a pattern more consistent with reciprocal altruism than costly signaling. However, once the propensity to reciprocate and household productivity are controlled, households of men holding leadership positions show greater odds of unreciprocated giving when compared to households of non-leaders. This pattern of excessive giving by leaders is consistent with the sharing-as-signaling hypothesis. Wealthy households show the opposite pattern, giving less and receiving more than other households. These households may reciprocate in a currency other than food or their wealth may attract favor-seeking behavior from others. Overall, status covariates explain little variation in the sharing network as a whole, and much of the sharing observed by high-status households is best explained by the same factors that explain sharing by other households. This pattern suggests that multiple mechanisms may operate simultaneously to promote sharing in Lamalera and that signaling may motivate some sharing by some individuals even within sharing regimes primarily maintained by other mechanisms. PMID:22822299

  12. Complex Dynamics in Information Sharing Networks

    NASA Astrophysics Data System (ADS)

    Cronin, Bruce

    This study examines the roll-out of an electronic knowledge base in a medium-sized professional services firm over a six year period. The efficiency of such implementation is a key business problem in IT systems of this type. Data from usage logs provides the basis for analysis of the dynamic evolution of social networks around the depository during this time. The adoption pattern follows an "s-curve" and usage exhibits something of a power law distribution, both attributable to network effects, and network position is associated with organisational performance on a number of indicators. But periodicity in usage is evident and the usage distribution displays an exponential cut-off. Further analysis provides some evidence of mathematical complexity in the periodicity. Some implications of complex patterns in social network data for research and management are discussed. The study provides a case study demonstrating the utility of the broad methodological approach.

  13. Information Sharing in a Nonprofit Network

    ERIC Educational Resources Information Center

    Stoll, Jennifer

    2012-01-01

    The civil rights and other social justice movements, neighborhood watches, local garden cooperatives, and so forth are examples of a grassroots context that is largely understudied in CSCW. In recent history, movements to fight child sex trafficking, end hunger in New York City, advocate for financial reform, or even overthrow governments have…

  14. A physical layer perspective on access network sharing

    NASA Astrophysics Data System (ADS)

    Pfeiffer, Thomas

    2015-12-01

    Unlike in copper or wireless networks, there is no sharing of resources in fiber access networks yet, other than bit stream access or cable sharing, in which the fibers of a cable are let to one or multiple operators. Sharing optical resources on a single fiber among multiple operators or different services has not yet been applied. While this would allow for a better exploitation of installed infrastructures, there are operational issues which still need to be resolved, before this sharing model can be implemented in networks. Operating multiple optical systems and services over a common fiber plant, autonomously and independently from each other, can result in mutual distortions on the physical layer. These distortions will degrade the performance of the involved systems, unless precautions are taken in the infrastructure hardware to eliminate or to reduce them to an acceptable level. Moreover, the infrastructure needs to be designed such as to support different system technologies and to ensure a guaranteed quality of the end-to-end connections. In this paper, suitable means are proposed to be introduced in fiber access infrastructures that will allow for shared utilization of the fibers while safeguarding the operational needs and business interests of the involved parties.

  15. User Expectations for Media Sharing Practices in Open Display Networks

    PubMed Central

    Jose, Rui; Cardoso, Jorge C. S.; Hong, Jason

    2015-01-01

    Open Display Networks have the potential to allow many content creators to publish their media to an open-ended set of screen displays. However, this raises the issue of how to match that content to the right displays. In this study, we aim to understand how the perceived utility of particular media sharing scenarios is affected by three independent variables, more specifically: (a) the locativeness of the content being shared; (b) how personal that content is and (c) the scope in which it is being shared. To assess these effects, we composed a set of 24 media sharing scenarios embedded with different treatments of our three independent variables. We then asked 100 participants to express their perception of the relevance of those scenarios. The results suggest a clear preference for scenarios where content is both local and directly related to the person that is publishing it. This is in stark contrast to the types of content that are commonly found in public displays, and confirms the opportunity that open displays networks may represent a new media for self-expression. This novel understanding may inform the design of new publication paradigms that will enable people to share media across the display networks. PMID:26153770

  16. Distributed simulation using a real-time shared memory network

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

    1993-01-01

    The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

  17. Efficient generation of large random networks

    NASA Astrophysics Data System (ADS)

    Batagelj, Vladimir; Brandes, Ulrik

    2005-03-01

    Random networks are frequently generated, for example, to investigate the effects of model parameters on network properties or to test the performance of algorithms. Recent interest in the statistics of large-scale networks sparked a growing demand for network generators that can generate large numbers of large networks quickly. We here present simple and efficient algorithms to randomly generate networks according to the most commonly used models. Their running time and space requirement is linear in the size of the network generated, and they are easily implemented.

  18. esyN: Network Building, Sharing and Publishing

    PubMed Central

    Bean, Daniel M.; Heimbach, Joshua; Ficorella, Lorenzo; Micklem, Gos; Oliver, Stephen G.; Favrin, Giorgio

    2014-01-01

    The construction and analysis of networks is increasingly widespread in biological research. We have developed esyN (“easy networks”) as a free and open source tool to facilitate the exchange of biological network models between researchers. esyN acts as a searchable database of user-created networks from any field. We have developed a simple companion web tool that enables users to view and edit networks using data from publicly available databases. Both normal interaction networks (graphs) and Petri nets can be created. In addition to its basic tools, esyN contains a number of logical templates that can be used to create models more easily. The ability to use previously published models as building blocks makes esyN a powerful tool for the construction of models and network graphs. Users are able to save their own projects online and share them either publicly or with a list of collaborators. The latter can be given the ability to edit the network themselves, allowing online collaboration on network construction. esyN is designed to facilitate unrestricted exchange of this increasingly important type of biological information. Ultimately, the aim of esyN is to bring the advantages of Open Source software development to the construction of biological networks. PMID:25181461

  19. Four health data networks illustrate the potential for a shared national multipurpose big-data network.

    PubMed

    Curtis, Lesley H; Brown, Jeffrey; Platt, Richard

    2014-07-01

    Information in electronic health data that are drawn from large populations of patients is transforming health care, public health practice, and clinical research. This article describes our experience in developing data networks that repurpose electronic health records and administrative data. The four programs we feature are the Food and Drug Administration's Mini-Sentinel program (which focuses on medical product safety), the National Patient-Centered Clinical Research Network (PCORnet, comparative effectiveness research), the National Institutes of Health's Health Care Systems Research Collaboratory Distributed Research Network (biomedical research), and ESPnet (public health surveillance). Challenges to these uses of electronic health data include understanding the factors driving the collection, coding, and preservation of the data; the extensive customization of different systems that collect similar data; the fragmentation of the US health care delivery system and its records; and privacy and proprietary considerations. We view these four programs as examples of the first stage in the development of a shared national big-data resource that leverages the investments of many agencies and organizations for the benefit of multiple networks and users. PMID:25006144

  20. Efficient capacity sharing for path protection in meshed optical networks

    NASA Astrophysics Data System (ADS)

    Dziong, Zbigniew; Nagarajan, Ramesh

    2004-03-01

    Efficient resource management in meshed optical networks is critical for supporting differentiated services, such as network restoration, in a cost-competitive manner. We propose and study several alternatives for dynamic and distributed selection of primary and protection paths. The focus is on algorithms where the bandwidth can be shared efficiently among protection paths, although other alternatives are considered as well. The routing algorithm and link cost function are based on a Markov decision-process framework. In particular, we use this framework to justify the link cost structure for primary and shared bandwidth. We also propose and study several options for describing the link state, which in turn determines the link cost, with the objective of minimizing the amount of data to be advertised without sacrificing performance. The proposed solutions can be implemented without changing the existing set of protocols. The numerical results show performance and cost savings for the different algorithm options.

  1. To share or not to share: Drivers and barriers for sharing data via online amateur weather networks

    NASA Astrophysics Data System (ADS)

    Gharesifard, Mohammad; Wehn, Uta

    2016-04-01

    Increasing attention is being paid to the importance and potential of crowd-sourced data to complement current environmental data-streams (i.e. in-situ observations and RS data). In parallel, the diffusion of Information Communication Technologies (ICTs) that are interactive and easy to use have provided a way forward in facing extreme climatic events and the threatening hazards resulting from those. The combination of these two trends is referred to as ICT-enabled 'citizen observatories' of the environment. Nevertheless, the success of these citizen observatories hinges on the continued involvement of citizens as central actors of these initiatives. Developing strategies to (further) engage citizens requires in-depth understanding of the behavioral determinants that encourage or impede individuals to collect and share environment-related data. This paper takes the case of citizen-sensed weather data using Personal Weather Stations (PWSs) and looks at the drivers and barriers for sharing such data via online amateur weather networks. This is done employing a behavioral science lens that considers data sharing a decision and systematically investigates the influential factors that affect this decision. The analysis and findings are based on qualitative empirical research carried out in the Netherlands, United Kingdom and Italy. Subsequently, a model was developed that depicts the main drivers and barriers for citizen participation in weather observatories. This resulting model can be utilized as a tool to develop strategies for further enhancing ICT-enabled citizen participation in climatic observations and, consequently, in environmental management.

  2. Graph theoretic modeling of large-scale semantic networks.

    PubMed

    Bales, Michael E; Johnson, Stephen B

    2006-08-01

    During the past several years, social network analysis methods have been used to model many complex real-world phenomena, including social networks, transportation networks, and the Internet. Graph theoretic methods, based on an elegant representation of entities and relationships, have been used in computational biology to study biological networks; however they have not yet been adopted widely by the greater informatics community. The graphs produced are generally large, sparse, and complex, and share common global topological properties. In this review of research (1998-2005) on large-scale semantic networks, we used a tailored search strategy to identify articles involving both a graph theoretic perspective and semantic information. Thirty-one relevant articles were retrieved. The majority (28, 90.3%) involved an investigation of a real-world network. These included corpora, thesauri, dictionaries, large computer programs, biological neuronal networks, word association networks, and files on the Internet. Twenty-two of the 28 (78.6%) involved a graph comprised of words or phrases. Fifteen of the 28 (53.6%) mentioned evidence of small-world characteristics in the network investigated. Eleven (39.3%) reported a scale-free topology, which tends to have a similar appearance when examined at varying scales. The results of this review indicate that networks generated from natural language have topological properties common to other natural phenomena. It has not yet been determined whether artificial human-curated terminology systems in biomedicine share these properties. Large network analysis methods have potential application in a variety of areas of informatics, such as in development of controlled vocabularies and for characterizing a given domain. PMID:16442849

  3. Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness

    PubMed Central

    Buchler, Norbou; Fitzhugh, Sean M.; Marusich, Laura R.; Ungvarsky, Diane M.; Lebiere, Christian; Gonzalez, Cleotilde

    2016-01-01

    A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In

  4. Mission Command in the Age of Network-Enabled Operations: Social Network Analysis of Information Sharing and Situation Awareness.

    PubMed

    Buchler, Norbou; Fitzhugh, Sean M; Marusich, Laura R; Ungvarsky, Diane M; Lebiere, Christian; Gonzalez, Cleotilde

    2016-01-01

    A common assumption in organizations is that information sharing improves situation awareness and ultimately organizational effectiveness. The sheer volume and rapid pace of information and communications received and readily accessible through computer networks, however, can overwhelm individuals, resulting in data overload from a combination of diverse data sources, multiple data formats, and large data volumes. The current conceptual framework of network enabled operations (NEO) posits that robust networking and information sharing act as a positive feedback loop resulting in greater situation awareness and mission effectiveness in military operations (Alberts and Garstka, 2004). We test this assumption in a large-scale, 2-week military training exercise. We conducted a social network analysis of email communications among the multi-echelon Mission Command staff (one Division and two sub-ordinate Brigades) and assessed the situational awareness of every individual. Results from our exponential random graph models challenge the aforementioned assumption, as increased email output was associated with lower individual situation awareness. It emerged that higher situation awareness was associated with a lower probability of out-ties, so that broadly sending many messages decreased the likelihood of attaining situation awareness. This challenges the hypothesis that increased information sharing improves situation awareness, at least for those doing the bulk of the sharing. In addition, we observed two trends that reflect a compartmentalizing of networked information sharing as email links were more commonly formed among members of the command staff with both similar functions and levels of situation awareness, than between two individuals with dissimilar functions and levels of situation awareness; both those findings can be interpreted to reflect effects of homophily. Our results have major implications that challenge the current conceptual framework of NEO. In

  5. Power-aware provisioning strategy with shared path protection in optical WDM networks

    NASA Astrophysics Data System (ADS)

    Bao, Ning-Hai; Li, Le-Min; Yu, Hong-Fang; Zhang, Zhi-Zhong; Luo, Hong-Bin

    2012-03-01

    As the Internet continues to grow, the power consumption of telecommunication networks is rising at a considerable speed, which seriously increases the operational expenditure and greenhouse gas emission. Since optical Wavelength Division Multiplexing (WDM) networks are currently the most promising network infrastructures, power saving issue on these networks has received more attention in recent years. In traditional optical WDM networks, a large amount of power is drained by the redundant idle resources and reserved backup resources although these powered on resources do not carry traffic in most of the time. In order to reduce the network power consumption, turning off the corresponding network components or switching them to a low-power, standby state (or called sleep mode) is a promising greening approach. In this paper, we study the power-aware provisioning strategies and propose a sleep mode based Power-Aware Shared Path Protection (PASPP) heuristic algorithm to achieve the power efficiency of optical WDM networks. By jointly utilizing link-cost and fiber-cost in path routing, resource assignment, and resource release, PASPP makes working paths and backup paths converge on different fibers as much as possible, and switch idle and backup components to sleep mode to realize power saving. Simulation results show that our PASPP can obtain notable power saving and achieve satisfactory tradeoff between power efficiency and blocking probability with respect to Power-Unaware Shared Path Protection (PUSPP).

  6. Network Analysis of an Emergent Massively Collaborative Creation on Video Sharing Website

    NASA Astrophysics Data System (ADS)

    Hamasaki, Masahiro; Takeda, Hideaki; Nishimura, Takuichi

    The Web technology enables numerous people to collaborate in creation. We designate it as massively collaborative creation via the Web. As an example of massively collaborative creation, we particularly examine video development on Nico Nico Douga, which is a video sharing website that is popular in Japan. We specifically examine videos on Hatsune Miku, a version of a singing synthesizer application software that has inspired not only song creation but also songwriting, illustration, and video editing. As described herein, creators of interact to create new contents through their social network. In this paper, we analyzed the process of developing thousands of videos based on creators' social networks and investigate relationships among creation activity and social networks. The social network reveals interesting features. Creators generate large and sparse social networks including some centralized communities, and such centralized community's members shared special tags. Different categories of creators have different roles in evolving the network, e.g., songwriters gather more links than other categories, implying that they are triggers to network evolution.

  7. Refuge sharing network predicts ectoparasite load in a lizard.

    PubMed

    Leu, Stephan T; Kappeler, Peter M; Bull, C Michael

    2010-09-01

    Living in social groups facilitates cross-infection by parasites. However, empirical studies on indirect transmission within wildlife populations are scarce. We investigated whether asynchronous overnight refuge sharing among neighboring sleepy lizards, Tiliqua rugosa, facilitates indirect transmission of its ectoparasitic tick, Amblyomma limbatum. We fitted 18 neighboring lizards with GPS recorders, observed their overnight refuge use each night over 3 months, and counted their ticks every fortnight. We constructed a transmission network to estimate the cross-infection risk based on asynchronous refuge sharing frequencies among all lizards and the life history traits of the tick. Although self-infection was possible, the network provided a powerful predictor of measured tick loads. Highly connected lizards that frequently used their neighbors' refuges were characterized by higher tick loads. Thus, indirect contact had a major influence on transmission pathways and parasite loads. Furthermore, lizards that used many different refuges had lower cross- and self-infection risks and lower tick loads than individuals that used relatively fewer refuges. Increasing the number of refuges used by a lizard may be an important defense mechanism against ectoparasite transmission in this species. Our study provides important empirical data to further understand how indirectly transmitted parasites move through host populations and influence individual parasite loads. PMID:20802788

  8. Online Community Detection for Large Complex Networks

    PubMed Central

    Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian

    2014-01-01

    Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683

  9. Large-scale quantum networks based on graphs

    NASA Astrophysics Data System (ADS)

    Epping, Michael; Kampermann, Hermann; Bruß, Dagmar

    2016-05-01

    Society relies and depends increasingly on information exchange and communication. In the quantum world, security and privacy is a built-in feature for information processing. The essential ingredient for exploiting these quantum advantages is the resource of entanglement, which can be shared between two or more parties. The distribution of entanglement over large distances constitutes a key challenge for current research and development. Due to losses of the transmitted quantum particles, which typically scale exponentially with the distance, intermediate quantum repeater stations are needed. Here we show how to generalise the quantum repeater concept to the multipartite case, by describing large-scale quantum networks, i.e. network nodes and their long-distance links, consistently in the language of graphs and graph states. This unifying approach comprises both the distribution of multipartite entanglement across the network, and the protection against errors via encoding. The correspondence to graph states also provides a tool for optimising the architecture of quantum networks.

  10. Integrative Biology Identifies Shared Transcriptional Networks in CKD

    PubMed Central

    Martini, Sebastian; Nair, Viji; Keller, Benjamin J.; Eichinger, Felix; Hawkins, Jennifer J.; Randolph, Ann; Böger, Carsten A.; Gadegbeku, Crystal A.; Fox, Caroline S.; Cohen, Clemens D.

    2014-01-01

    A previous meta-analysis of genome-wide association data by the Cohorts for Heart and Aging Research in Genomic Epidemiology and CKDGen consortia identified 16 loci associated with eGFR. To define how each of these single-nucleotide polymorphisms (SNPs) could affect renal function, we integrated GFR-associated loci with regulatory pathways, producing a molecular map of CKD. In kidney biopsy specimens from 157 European subjects representing nine different CKDs, renal transcript levels for 18 genes in proximity to the SNPs significantly correlated with GFR. These 18 genes were mapped into their biologic context by testing coregulated transcripts for enriched pathways. A network of 97 pathways linked by shared genes was constructed and characterized. Of these pathways, 56 pathways were reported previously to be associated with CKD; 41 pathways without prior association with CKD were ranked on the basis of the number of candidate genes connected to the respective pathways. All pathways aggregated into a network of two main clusters comprising inflammation- and metabolism-related pathways, with the NRF2-mediated oxidative stress response pathway serving as the hub between the two clusters. In all, 78 pathways and 95% of the connections among those pathways were verified in an independent North American biopsy cohort. Disease-specific analyses showed that most pathways are shared between sets of three diseases, with closest interconnection between lupus nephritis, IgA nephritis, and diabetic nephropathy. Taken together, the network integrates candidate genes from genome-wide association studies into their functional context, revealing interactions and defining established and novel biologic mechanisms of renal impairment in renal diseases. PMID:24925724

  11. Image transmission in tactical radio frequency shared network propagation environments

    NASA Astrophysics Data System (ADS)

    White, Kent H.; Wagner, Kerry A.; O'Hanian, Scott

    1997-06-01

    The need to transmit images across tactical radio frequency (rf) links has been identified in army digitization applications. For example, military doctrine requires that tactical functions like identification of battlefield entities as potential targets and battle damage assessment be performed by the soldier. Currently, a key input to these processes is imagery. Therefore, the quality and timeliness of the image directly impact tactical performance. The military is investigating the employment of remote sensors and advanced communications systems to meet this requirement as part of its digitization effort. Army communications systems exist that partially meet this requirement. However, many existing solutions employ these legacy systems in the context of a point-to-point communications architecture. Solutions to the problem of transmitting images across a rf network have not been fully explored. The term network implies that the rf transmission media is common to and shared by multiple subscribers. It is a suite of capabilities that collectively manage media access and information transfer for its subscribers thus providing substantial improvements in effectiveness, efficiency, and robustness. This paper discusses the challenges of transmitting images using one army legacy communications system in a tactical rf network, presents a conceptual framework for attacking the problem, and discusses one solution.

  12. Optimal media sharing policies in peer-to-peer networks

    NASA Astrophysics Data System (ADS)

    Sood, Ritesh; van der Schaar, Mihaela

    2004-11-01

    Multimedia content distribution through a distributed system, a peer-to-peer (P2P) network for instance, is attractive since it harnesses the resources available with the numerous peers in the network. Another advantage of such a system is that the potentially available resources scale in proportion to the demand as more and more peers join the system. Recent studies have concentrated mainly on such aspects of these distributed networks as querying, indexing, etc. These studies however take for granted the voluntary contribution of resources by peers in the system. Empirical evidence however points to the contrary, i.e. in existing P2P systems, a substantial fraction of peers do not contribute resources to the system, while benefiting from the services it provides at the expense of the contributing peers. In this paper we analyze a P2P system in a game-theoretic setting in which games involving content exchange are played repeatedly. The model takes into account the manner in which a peer adapts his contribution to the system depending on the benefit he has derived from the system so far and expects to derive in the long run. The model enables us to formulate an optimization problem that yields optimal content sharing strategies that a peer should adopt in order to maximize his net benefit by participating in the system.

  13. Information sharing and relationships on social networking sites.

    PubMed

    Steijn, Wouter M P; Schouten, Alexander P

    2013-08-01

    This article investigates the relationship between sharing personal information and relationship development in the context of social networking sites (SNSs). Information disclosed on these sites could affect relationships in a different manner compared to more traditional interactions, such as instant messaging or face-to-face interaction. Respondents in the age range of 12 to 83 were surveyed about experiences of relationship development as a consequence of contact through Facebook or Hyves-the most popular Dutch SNSs. Results showed a primarily positive effect of information sharing on SNSs on our relationships. Furthermore, relationship development mainly occurs among acquaintances and friends, and public posts are most strongly related to relationship development. These findings suggest that SNSs might affect relationships in a distinct fashion as acquaintances and friends gain access to public self-disclosures that might normally only be reserved for close friends and family. Overall, this study provides an insight into some of the positive aspects of the public nature of SNSs in contrast with the general negative associations. PMID:23659723

  14. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... the network sharing agreement. 90.1415 Section 90.1415 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 90.1415 Establishment, execution, and application of the network sharing agreement... to the NSA must also include the Upper 700 MHz D Block licensee, the Network Assets Holder, and...

  15. 47 CFR 27.1315 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... the network sharing agreement. 27.1315 Section 27.1315 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 27.1315 Establishment, execution, and application of the network sharing agreement... Upper 700 MHz D Block licensee, the Network Assets Holder, and the Operating Company, as these...

  16. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... the network sharing agreement. 90.1415 Section 90.1415 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 90.1415 Establishment, execution, and application of the network sharing agreement... to the NSA must also include the Upper 700 MHz D Block licensee, the Network Assets Holder, and...

  17. 47 CFR 27.1315 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... the network sharing agreement. 27.1315 Section 27.1315 Telecommunication FEDERAL COMMUNICATIONS.../Private Partnership § 27.1315 Establishment, execution, and application of the network sharing agreement... Upper 700 MHz D Block licensee, the Network Assets Holder, and the Operating Company, as these...

  18. [Study on network architecture of a tele-medical information sharing platform].

    PubMed

    Pan, Lin; Yu, Lun; Chen, Jin-xiong

    2006-07-01

    In the article,a plan of network construction which satisfies the demand of applications for a telemedical information sharing platform is proposed. We choice network access plans in view of user actual situation, through the analysis of the service demand and many kinds of network access technologies. Hospital servers that locate in LAN link sharing platform with node servers, should separate from the broadband network of sharing platform in order to ensure the security of the internal hospital network and the administration management. We use the VPN technology to realize the safe transmission of information in the platform network. Preliminary experiments have proved the plan is practicable. PMID:17039943

  19. Partly shared spinal cord networks for locomotion and scratching.

    PubMed

    Berkowitz, Ari; Hao, Zhao-Zhe

    2011-12-01

    Animals produce a variety of behaviors using a limited number of muscles and motor neurons. Rhythmic behaviors are often generated in basic form by networks of neurons within the central nervous system, or central pattern generators (CPGs). It is known from several invertebrates that different rhythmic behaviors involving the same muscles and motor neurons can be generated by a single CPG, multiple separate CPGs, or partly overlapping CPGs. Much less is known about how vertebrates generate multiple, rhythmic behaviors involving the same muscles. The spinal cord of limbed vertebrates contains CPGs for locomotion and multiple forms of scratching. We investigated the extent of sharing of CPGs for hind limb locomotion and for scratching. We used the spinal cord of adult red-eared turtles. Animals were immobilized to remove movement-related sensory feedback and were spinally transected to remove input from the brain. We took two approaches. First, we monitored individual spinal cord interneurons (i.e., neurons that are in between sensory neurons and motor neurons) during generation of each kind of rhythmic output of motor neurons (i.e., each motor pattern). Many spinal cord interneurons were rhythmically activated during the motor patterns for forward swimming and all three forms of scratching. Some of these scratch/swim interneurons had physiological and morphological properties consistent with their playing a role in the generation of motor patterns for all of these rhythmic behaviors. Other spinal cord interneurons, however, were rhythmically activated during scratching motor patterns but inhibited during swimming motor patterns. Thus, locomotion and scratching may be generated by partly shared spinal cord CPGs. Second, we delivered swim-evoking and scratch-evoking stimuli simultaneously and monitored the resulting motor patterns. Simultaneous stimulation could cause interactions of scratch inputs with subthreshold swim inputs to produce normal swimming, acceleration

  20. Shared and Distributed Memory Parallel Security Analysis of Large-Scale Source Code and Binary Applications

    SciTech Connect

    Quinlan, D; Barany, G; Panas, T

    2007-08-30

    Many forms of security analysis on large scale applications can be substantially automated but the size and complexity can exceed the time and memory available on conventional desktop computers. Most commercial tools are understandably focused on such conventional desktop resources. This paper presents research work on the parallelization of security analysis of both source code and binaries within our Compass tool, which is implemented using the ROSE source-to-source open compiler infrastructure. We have focused on both shared and distributed memory parallelization of the evaluation of rules implemented as checkers for a wide range of secure programming rules, applicable to desktop machines, networks of workstations and dedicated clusters. While Compass as a tool focuses on source code analysis and reports violations of an extensible set of rules, the binary analysis work uses the exact same infrastructure but is less well developed into an equivalent final tool.

  1. Implementation of the morphological shared-weight neural network (MSNN) for target recognition on the Parallel Algebraic Logic (PAL) computer

    NASA Astrophysics Data System (ADS)

    Li, Hongzheng; Shi, Hongchi; Gader, Paul D.; Keller, James M.

    1998-09-01

    The morphological shared-weight neural network (MSNN) is an effective approach to automatic target recognition. Implementation of the network in parallel is critical for real-time target recognition systems. Although there is significant parallelism inherent in the MSNN, it is a challenge to implement it on an SIMD parallel computer consisting of a large array of simple processing elements. This paper discusses issues related to detection accuracy and throughput in implementing the MSNN on the Parallel Algebraic Logic computer.

  2. Bibliographic Automation of Large Library Operations Using a Time-Sharing System: Phase I. Final Report.

    ERIC Educational Resources Information Center

    Epstein, A. H.; And Others

    The first phase of an ongoing library automation project at Stanford University is described. Project BALLOTS (Bibliographic Automation of Large Library Operations Using a Time-Sharing System) seeks to automate the acquisition and cataloging functions of a large library using an on-line time-sharing computer. The main objectives are to control…

  3. The Development and Evaluation of a Network for Producing and Sharing Video Presentations

    ERIC Educational Resources Information Center

    Sadik, Alaa

    2014-01-01

    This paper describes the technology and methodology used in the development and evaluation of an online network to help the instructors to produce and share video presentations in a new and innovative way. The network offers an application and platform for recording and sharing video presentations. The application allows instructors to narrate and…

  4. Cultural Differences in an Interorganizational Network: Shared Public Relations Firms among Japanese and American Companies.

    ERIC Educational Resources Information Center

    Jang, Ha-Yong

    1997-01-01

    Investigates impact of national culture on interorganizational relationships among organizations. Matches 35 Japanese and American companies by their business types. Reveals that the network of shared public relations firms was loosely connected--American companies were more central. Indicates the network structure of shared public relations firms…

  5. Predictive Control of Large Complex Networks

    NASA Astrophysics Data System (ADS)

    Haber, Aleksandar; Motter, Adilson E.

    Networks of coupled dynamical subsystems are increasingly used to represent complex natural and engineered systems. While recent technological developments give us improved means to actively control the dynamics of individual subsystems in various domains, network control remains a challenging problem due to difficulties imposed by intrinsic nonlinearities, control constraints, and the large-scale nature of the systems. In this talk, we will present a model predictive control approach that is effective while accounting for these realistic properties of complex networks. Our method can systematically identify control interventions that steer the trajectory to a desired state, even in the presence of strong nonlinearities and constraints. Numerical tests show that the method is applicable to a variety of networks, ranging from power grids to chemical reaction systems.

  6. The Double-Stranded DNA Virosphere as a Modular Hierarchical Network of Gene Sharing

    PubMed Central

    Iranzo, Jaime

    2016-01-01

    ABSTRACT Virus genomes are prone to extensive gene loss, gain, and exchange and share no universal genes. Therefore, in a broad-scale study of virus evolution, gene and genome network analyses can complement traditional phylogenetics. We performed an exhaustive comparative analysis of the genomes of double-stranded DNA (dsDNA) viruses by using the bipartite network approach and found a robust hierarchical modularity in the dsDNA virosphere. Bipartite networks consist of two classes of nodes, with nodes in one class, in this case genomes, being connected via nodes of the second class, in this case genes. Such a network can be partitioned into modules that combine nodes from both classes. The bipartite network of dsDNA viruses includes 19 modules that form 5 major and 3 minor supermodules. Of these modules, 11 include tailed bacteriophages, reflecting the diversity of this largest group of viruses. The module analysis quantitatively validates and refines previously proposed nontrivial evolutionary relationships. An expansive supermodule combines the large and giant viruses of the putative order “Megavirales” with diverse moderate-sized viruses and related mobile elements. All viruses in this supermodule share a distinct morphogenetic tool kit with a double jelly roll major capsid protein. Herpesviruses and tailed bacteriophages comprise another supermodule, held together by a distinct set of morphogenetic proteins centered on the HK97-like major capsid protein. Together, these two supermodules cover the great majority of currently known dsDNA viruses. We formally identify a set of 14 viral hallmark genes that comprise the hubs of the network and account for most of the intermodule connections. PMID:27486193

  7. 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

    be merged into a single quality-control file (v) Multiple flux stations can be linked into an automated time-synchronized network (vi) Flux network managers, or PI's, can see all stations in real-time, including fluxes, supporting data, automated reports, and email alerts (vii) PI's can assign rights, allow or restrict access to stations and data: selected stations can be shared via rights-managed access internally or with external institutions (viii) Researchers without stations could form "virtual networks" for specific projects by collaborating with PIs from different actual networks This presentation provides detailed examples of FluxSuite currently utilized to manage two large flux networks in China (National Academy of Sciences and Agricultural Academy of Sciences), and smaller networks with stations in the USA, Germany, Ireland, Malaysia and other locations around the globe. Very latest 2016 developments and expanded functionality are also discussed.

  8. Data Validation and Sharing in a Large Research Program

    EPA Science Inventory

    Appropriate data handling practices are important in the support of large research teams with shifting and competing priorities. Determining those best practices is an ongoing effort for the US EPA’s National Aquatic Resource Surveys. We focus on the well understood data ...

  9. Time geography for ad-hoc shared-ride trip planning in mobile geosensor networks

    NASA Astrophysics Data System (ADS)

    Raubal, Martin; Winter, Stephan; Teβmann, Sven; Gaisbauer, Christian

    Ad-hoc shared-ride trip planning in an urban environment is a complex task within a non-deterministic transportation network. Mobile geosensor networks provide the technical environment for realizing ad-hoc shared-ride trip planning: Network nodes are autonomous agents that interact locally by ad-hoc short-range communication and arrange for shared rides. In a mobile geosensor network, communication costs are critical because of constraints regarding bandwidth, available energy, and memory. This paper introduces spatio-temporal concepts from time geography, which can be employed during the planning process to significantly reduce communication costs. We will integrate network-based algorithms and different wayfinding strategies to assist both shared-ride clients and hosts in finding optimal travel assignments. Multi-agent geosimulation in a real street network is used to demonstrate the applicability of the approach and quantitatively confirm the theoretically foreseen reduction in communication costs.

  10. 77 FR 58415 - Large Scale Networking (LSN); Joint Engineering Team (JET)

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-20

    ... From the Federal Register Online via the Government Publishing Office NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN); Joint Engineering Team (JET) AGENCY: The Networking and Information..._Engineering_Team_ (JET). SUMMARY: The JET, established in 1997, provides for information sharing among...

  11. Coupled cluster algorithms for networks of shared memory parallel processors

    NASA Astrophysics Data System (ADS)

    Bentz, Jonathan L.; Olson, Ryan M.; Gordon, Mark S.; Schmidt, Michael W.; Kendall, Ricky A.

    2007-05-01

    As the popularity of using SMP systems as the building blocks for high performance supercomputers increases, so too increases the need for applications that can utilize the multiple levels of parallelism available in clusters of SMPs. This paper presents a dual-layer distributed algorithm, using both shared-memory and distributed-memory techniques to parallelize a very important algorithm (often called the "gold standard") used in computational chemistry, the single and double excitation coupled cluster method with perturbative triples, i.e. CCSD(T). The algorithm is presented within the framework of the GAMESS [M.W. Schmidt, K.K. Baldridge, J.A. Boatz, S.T. Elbert, M.S. Gordon, J.J. Jensen, S. Koseki, N. Matsunaga, K.A. Nguyen, S. Su, T.L. Windus, M. Dupuis, J.A. Montgomery, General atomic and molecular electronic structure system, J. Comput. Chem. 14 (1993) 1347-1363]. (General Atomic and Molecular Electronic Structure System) program suite and the Distributed Data Interface [M.W. Schmidt, G.D. Fletcher, B.M. Bode, M.S. Gordon, The distributed data interface in GAMESS, Comput. Phys. Comm. 128 (2000) 190]. (DDI), however, the essential features of the algorithm (data distribution, load-balancing and communication overhead) can be applied to more general computational problems. Timing and performance data for our dual-level algorithm is presented on several large-scale clusters of SMPs.

  12. A Networked NMR Spectrometer: Configuring a Shared Instrument

    ERIC Educational Resources Information Center

    Alonso, David; Mutch, G. William; Wong, Peter; Warren, Steven; Barot, Bal; Kosinski, Jan; Sinton, Mark

    2005-01-01

    A model for a shared nuclear magnetic resonance spectroscopy (NMR) facility between a private university and two local community colleges is presented. The discussion of the components required for the shared facility, modes of data distribution, and overall effect on the curriculum is presented.

  13. Shared and Distinct Intrinsic Functional Network Centrality in Autism and Attention-Deficit/Hyperactivity Disorder

    PubMed Central

    Di Martino, Adriana; Zuo, Xi-Nian; Kelly, Clare; Grzadzinski, Rebecca; Mennes, Maarten; Schvarcz, Ariel; Rodman, Jennifer; Lord, Catherine; Castellanos, F. Xavier; Milham, Michael P.

    2015-01-01

    Background Individuals with autism spectrum disorders (ASD) often exhibit symptoms of Attention-Deficit/Hyperactivity Disorder (ADHD). Across both disorders, observations of distributed functional abnormalities suggest aberrant large-scale brain network connectivity. Yet, common and distinct network correlates of ASD and ADHD remain unidentified. Here, we aimed to examine patterns of dysconnection in school-age children with ASD, ADHD and typically developing children (TDC) who completed a resting state fMRI (R-fMRI) scan. Methods We measured voxel-wise network centrality, functional connectivity metrics indexing local (degree centrality; DC) and global (eigenvector centrality; EC) functional relationships across the entire brain connectome, in R-fMRI data from 56 children with ASD, 45 children with ADHD and 50 TDC. A one-way ANCOVA, with group as fixed factor (whole-brain corrected), was followed by post-hoc pair-wise comparisons. Results Cortical and subcortical areas exhibited centrality abnormalities; some common to both ADHD and ASD, such as in precuneus. Others were disorder-specific and included ADHD-related increases in DC in right striatum/pallidum, in contrast with ASD-related increases in bilateral temporolimbic areas. Secondary analyses differentiating children with ASD into those with or without ADHD-like comorbidity (ASD+ and ASD−, respectively) revealed that the ASD+ group shared ADHD-specific abnormalities in basal ganglia. By contrast, centrality increases in temporolimbic areas characterized children with ASD regardless of ADHD-like comorbidity. At the cluster level eignevector centrality group patterns were similar to DC. Conclusions ADHD and ASD are neurodevelopmental disorders with distinct and overlapping clinical presentations. This work provides evidence for both shared and distinct underlying mechanisms at the large-scale network level. PMID:23541632

  14. Fuzzy-rule-based Adaptive Resource Control for Information Sharing in P2P Networks

    NASA Astrophysics Data System (ADS)

    Wu, Zhengping; Wu, Hao

    With more and more peer-to-peer (P2P) technologies available for online collaboration and information sharing, people can launch more and more collaborative work in online social networks with friends, colleagues, and even strangers. Without face-to-face interactions, the question of who can be trusted and then share information with becomes a big concern of a user in these online social networks. This paper introduces an adaptive control service using fuzzy logic in preference definition for P2P information sharing control, and designs a novel decision-making mechanism using formal fuzzy rules and reasoning mechanisms adjusting P2P information sharing status following individual users' preferences. Applications of this adaptive control service into different information sharing environments show that this service can provide a convenient and accurate P2P information sharing control for individual users in P2P networks.

  15. Bounded link prediction in very large networks

    NASA Astrophysics Data System (ADS)

    Cui, Wei; Pu, Cunlai; Xu, Zhongqi; Cai, Shimin; Yang, Jian; Michaelson, Andrew

    2016-09-01

    Evaluating link prediction methods is a hard task in very large complex networks due to the prohibitive computational cost. However, if we consider the lower bound of node pairs' similarity scores, this task can be greatly optimized. In this paper, we study CN index in the bounded link prediction framework, which is applicable to enormous heterogeneous networks. Specifically, we propose a fast algorithm based on the parallel computing scheme to obtain all node pairs with CN values larger than the lower bound. Furthermore, we propose a general measurement, called self-predictability, to quantify the performance of similarity indices in link prediction, which can also indicate the link predictability of networks with respect to given similarity indices.

  16. Network issues for large mass storage requirements

    NASA Technical Reports Server (NTRS)

    Perdue, James

    1992-01-01

    File Servers and Supercomputing environments need high performance networks to balance the I/O requirements seen in today's demanding computing scenarios. UltraNet is one solution which permits both high aggregate transfer rates and high task-to-task transfer rates as demonstrated in actual tests. UltraNet provides this capability as both a Server-to-Server and Server-to-Client access network giving the supercomputing center the following advantages highest performance Transport Level connections (to 40 MBytes/sec effective rates); matches the throughput of the emerging high performance disk technologies, such as RAID, parallel head transfer devices and software striping; supports standard network and file system applications using SOCKET's based application program interface such as FTP, rcp, rdump, etc.; supports access to the Network File System (NFS) and LARGE aggregate bandwidth for large NFS usage; provides access to a distributed, hierarchical data server capability using DISCOS UniTree product; supports file server solutions available from multiple vendors, including Cray, Convex, Alliant, FPS, IBM, and others.

  17. Future large broadband switched satellite communications networks

    NASA Technical Reports Server (NTRS)

    Staelin, D. H.; Harvey, R. R.

    1979-01-01

    Critical technical, market, and policy issues relevant to future large broadband switched satellite networks are summarized. Our market projections for the period 1980 to 2000 are compared. Clusters of switched satellites, in lieu of large platforms, etc., are shown to have significant advantages. Analysis of an optimum terrestrial network architecture suggests the proper densities of ground stations and that link reliabilities 99.99% may entail less than a 10% cost premium for diversity protection at 20/30 GHz. These analyses suggest that system costs increase as the 0.6 power of traffic. Cost estimates for nominal 20/30 GHz satellite and ground facilities suggest optimum system configurations might employ satellites with 285 beams, multiple TDMA bands each carrying 256 Mbps, and 16 ft ground station antennas. A nominal development program is outlined.

  18. Sharing by Design: Understanding and Supporting Personal Health Information Sharing and Collaboration within Social Networks

    ERIC Educational Resources Information Center

    Skeels, Meredith McLain

    2010-01-01

    Friends, family, and community provide important support and help to patients who face an illness. Unfortunately, keeping a social network informed about a patient's health status and needs takes effort, making it difficult for people who are sick and exhausted from illness. Members of a patient's social network are often eager to help, but can be…

  19. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

    PubMed Central

    Lee, Sandra Soo-Jin; Vernez, Simone L.; Ormond, K.E.; Granovetter, Mark

    2013-01-01

    Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities. PMID:25562728

  20. Potential Parasite Transmission in Multi-Host Networks Based on Parasite Sharing

    PubMed Central

    Pilosof, Shai; Morand, Serge; Krasnov, Boris R.; Nunn, Charles L.

    2015-01-01

    Epidemiological networks are commonly used to explore dynamics of parasite transmission among individuals in a population of a given host species. However, many parasites infect multiple host species, and thus multi-host networks may offer a better framework for investigating parasite dynamics. We investigated the factors that influence parasite sharing – and thus potential transmission pathways – among rodent hosts in Southeast Asia. We focused on differences between networks of a single host species and networks that involve multiple host species. In host-parasite networks, modularity (the extent to which the network is divided into subgroups of rodents that interact with similar parasites) was higher in the multi-species than in the single-species networks. This suggests that phylogeny affects patterns of parasite sharing, which was confirmed in analyses showing that it predicted affiliation of individuals to modules. We then constructed “potential transmission networks” based on the host-parasite networks, in which edges depict the similarity between a pair of individuals in the parasites they share. The centrality of individuals in these networks differed between multi- and single-species networks, with species identity and individual characteristics influencing their position in the networks. Simulations further revealed that parasite dynamics differed between multi- and single-species networks. We conclude that multi-host networks based on parasite sharing can provide new insights into the potential for transmission among hosts in an ecological community. In addition, the factors that determine the nature of parasite sharing (i.e. structure of the host-parasite network) may impact transmission patterns. PMID:25748947

  1. Matchmaking in Learning Networks: Bringing Learners Together for Knowledge Sharing

    ERIC Educational Resources Information Center

    Kester, Liesbeth; van Rosmalen, Peter; Sloep, Peter; Brouns, Francis; Kone, Malik; Koper, Rob

    2007-01-01

    In this article we describe a system that matches learners with complementary content expertise in reaction to a learner-request for knowledge sharing. It works through the formation of "ad hoc," transient communities, that exist for a limited period of time and stimulate learners socially to interact. The matchmaking system consists of a request…

  2. Oklahoma Library Technology Network Plan for Information Sharing and Telecommunications.

    ERIC Educational Resources Information Center

    Oklahoma State Dept. of Libraries, Oklahoma City.

    This plan sets forth approaches for state-level assistance for Oklahoma libraries to exchange information and to share or acquire machine-readable information from public and private sources through telecommunications, as well as for access to these libraries for existing and future state informational databases. Objectives and requirements are…

  3. Good Samaritans in Networks: An Experiment on How Networks Influence Egalitarian Sharing and the Evolution of Inequality

    PubMed Central

    Chiang, Yen-Sheng

    2015-01-01

    The fact that the more resourceful people are sharing with the poor to mitigate inequality—egalitarian sharing—is well documented in the behavioral science research. How inequality evolves as a result of egalitarian sharing is determined by the structure of “who gives whom”. While most prior experimental research investigates allocation of resources in dyads and groups, the paper extends the research of egalitarian sharing to networks for a more generalized structure of social interaction. An agent-based model is proposed to predict how actors, linked in networks, share their incomes with neighbors. A laboratory experiment with human subjects further shows that income distributions evolve to different states in different network topologies. Inequality is significantly reduced in networks where the very rich and the very poor are connected so that income discrepancy is salient enough to motivate the rich to share their incomes with the poor. The study suggests that social networks make a difference in how egalitarian sharing influences the evolution of inequality. PMID:26061642

  4. Large-Scale Organization of Glycosylation Networks

    NASA Astrophysics Data System (ADS)

    Kim, Pan-Jun; Lee, Dong-Yup; Jeong, Hawoong

    2009-03-01

    Glycosylation is a highly complex process to produce a diverse repertoire of cellular glycans that are frequently attached to proteins and lipids. Glycans participate in fundamental biological processes including molecular trafficking and clearance, cell proliferation and apoptosis, developmental biology, immune response, and pathogenesis. N-linked glycans found on proteins are formed by sequential attachments of monosaccharides with the help of a relatively small number of enzymes. Many of these enzymes can accept multiple N-linked glycans as substrates, thus generating a large number of glycan intermediates and their intermingled pathways. Motivated by the quantitative methods developed in complex network research, we investigate the large-scale organization of such N-glycosylation pathways in a mammalian cell. The uncovered results give the experimentally-testable predictions for glycosylation process, and can be applied to the engineering of therapeutic glycoproteins.

  5. Sharing, Privacy and Trust in Our Networked World. A Report to the OCLC Membership

    ERIC Educational Resources Information Center

    Storey, Tom, Ed.

    2007-01-01

    The practice of using a social network to establish and enhance relationships based on some common ground--shared interests, related skills, or a common geographic location--is as old as human societies, but social networking has flourished due to the ease of connecting on the Web. This OCLC membership report explores this web of social…

  6. Categorical Structure among Shared Features in Networks of Early-Learned Nouns

    ERIC Educational Resources Information Center

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

  7. 78 FR 3447 - Information Collection: Southern Alaska Sharing Network and Subsistence Study; Submitted for OMB...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-01-16

    ... notice (77 FR 50712) announcing that we would submit this ICR to OMB for approval. The notice provided... Bureau of Ocean Energy Management Information Collection: Southern Alaska Sharing Network and Subsistence... networks in coastal Alaska. This notice provides the public a second opportunity to comment on...

  8. Horizontal Evaluation: Fostering Knowledge Sharing and Program Improvement within a Network

    ERIC Educational Resources Information Center

    Thiele, Graham; Devaux, Andre; Velasco, Claudio; Horton, Douglas

    2007-01-01

    Horizontal evaluation combines self-assessment and external evaluation by peers. Papa Andina, a regional network that works to reduce rural poverty in the Andean region by fostering innovation in potato production and marketing, has used horizontal evaluations to improve the work of local project teams and to share knowledge within the network. In…

  9. Enhancing topology adaptation in information-sharing social networks

    NASA Astrophysics Data System (ADS)

    Cimini, Giulio; Chen, Duanbing; Medo, Matúš; Lü, Linyuan; Zhang, Yi-Cheng; Zhou, Tao

    2012-04-01

    The advent of the Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. It has thus become important to address issues like who gets followed and how to allow people to discover new and better information sources. In this paper we conduct an empirical analysis of different online social networking sites and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. These rules create networks which are effective in information diffusion and resemble structures resulting from real social systems.

  10. A Method of Discovery of Shared Topic Networks among People from WWW Bookmarks and Its Evaluations

    NASA Astrophysics Data System (ADS)

    Hamasaki, Masahiro; Takeda, Hideaki; Matsuzuka, Takeshi; Taniguchi, Yuichiro; Kono, Yasuyuki; Kidode, Masatsugu

    In this paper, we propose shared topic networks as a model of human network to organize Internet Information, and developed a system called kMedia that can generate shared topic networks by using WWW bookmark files. We also evaluate the system with experiments to know how shared topics network can help uesrs especially to know each other. A shared topic network is formed by linking topics of participants, and used to know interests of others and to exchange information with others. kMedia can generate shared topics networks by using structures of WWW bookmarks, i.e., folders of bookmarks are regarded as topics of their owners. Relations among topics of different users are estimated by aggregating similarity among pages in these topics. The experiments were performed to clarify two points; one is whether topics is a better way to exchange information among people and the other is how we can measure human relationship. The first point is examined that topic recommendation is more acceptable than page recommendation. For the second point, we propose category resemblance as measurement of human relationship. Since we compare results between cases with subjects belonging to the same community and cases without communities, we noticed similarity of topics structure is affective. The category resemblance is to estimate this similarity of topic structure and it is proved that it is better than any other parameters with respect to measurement for human relationship.

  11. Library Resource-Sharing in the Network-Centric World.

    ERIC Educational Resources Information Center

    McGee, Rob

    This paper discusses changes in services, technology, and organization as libraries prepare to enter the "network-centric library world." Part 1 addresses the transition from the analog era to the digital age, and the convergence of libraries and education, including opportunities for library leadership in Internet access, digital literacy, and…

  12. Knowledge Sharing via Social Networking Platforms in Organizations

    ERIC Educational Resources Information Center

    Kettles, Degan

    2012-01-01

    Knowledge Management Systems have been actively promoted for decades within organizations but have frequently failed to be used. Recently, deployments of enterprise social networking platforms used for knowledge management have become commonplace. These platforms help harness the knowledge of workers by serving as repositories of knowledge as well…

  13. 47 CFR 90.1410 - Network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... specifications and equipment are consistent with reasonable network control requirements established in the NSA... that includes a seamlessly integrated satellite solution pursuant to the terms, conditions, and... this chapter. (c) The definition of “emergency” for purposes of emergency priority access. (d)...

  14. 47 CFR 27.1310 - Network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... specifications and equipment are consistent with reasonable network control requirements established in the NSA... that includes a seamlessly integrated satellite solution pursuant to the terms, conditions, and... comply with § 27.1305. (c) The definition of “emergency” for purposes of emergency priority access....

  15. Synchronization of coupled large-scale Boolean networks

    SciTech Connect

    Li, Fangfei

    2014-03-15

    This paper investigates the complete synchronization and partial synchronization of two large-scale Boolean networks. First, the aggregation algorithm towards large-scale Boolean network is reviewed. Second, the aggregation algorithm is applied to study the complete synchronization and partial synchronization of large-scale Boolean networks. Finally, an illustrative example is presented to show the efficiency of the proposed results.

  16. Networking Biology: The Origins of Sequence-Sharing Practices in Genomics.

    PubMed

    Stevens, Hallam

    2015-10-01

    The wide sharing of biological data, especially nucleotide sequences, is now considered to be a key feature of genomics. Historians and sociologists have attempted to account for the rise of this sharing by pointing to precedents in model organism communities and in natural history. This article supplements these approaches by examining the role that electronic networking technologies played in generating the specific forms of sharing that emerged in genomics. The links between early computer users at the Stanford Artificial Intelligence Laboratory in the 1960s, biologists using local computer networks in the 1970s, and GenBank in the 1980s, show how networking technologies carried particular practices of communication, circulation, and data distribution from computing into biology. In particular, networking practices helped to transform sequences themselves into objects that had value as a community resource. PMID:26593711

  17. Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive1

    PubMed Central

    Kalpathy-Cramer, Jayashree; Freymann, John Blake; Kirby, Justin Stephen; Kinahan, Paul Eugene; Prior, Fred William

    2014-01-01

    The Quantitative Imaging Network (QIN), supported by the National Cancer Institute, is designed to promote research and development of quantitative imaging methods and candidate biomarkers for the measurement of tumor response in clinical trial settings. An integral aspect of the QIN mission is to facilitate collaborative activities that seek to develop best practices for the analysis of cancer imaging data. The QIN working groups and teams are developing new algorithms for image analysis and novel biomarkers for the assessment of response to therapy. To validate these algorithms and biomarkers and translate them into clinical practice, algorithms need to be compared and evaluated on large and diverse data sets. Analysis competitions, or “challenges,” are being conducted within the QIN as a means to accomplish this goal. The QIN has demonstrated, through its leveraging of The Cancer Imaging Archive (TCIA), that data sharing of clinical images across multiple sites is feasible and that it can enable and support these challenges. In addition to Digital Imaging and Communications in Medicine (DICOM) imaging data, many TCIA collections provide linked clinical, pathology, and “ground truth” data generated by readers that could be used for further challenges. The TCIA-QIN partnership is a successful model that provides resources for multisite sharing of clinical imaging data and the implementation of challenges to support algorithm and biomarker validation. PMID:24772218

  18. HydroShare: Applying professional software engineering to a new NSF-funded large software project

    NASA Astrophysics Data System (ADS)

    Idaszak, R.; Tarboton, D. G.; Ames, D.; Saleem Arrigo, J. A.; Band, L. E.; Bedig, A.; Castronova, A. M.; Christopherson, L.; Coposky, J.; Couch, A.; Dash, P.; Gan, T.; Goodall, J.; Gustafson, K.; Heard, J.; Hooper, R. P.; Horsburgh, J. S.; Jackson, S.; Johnson, H.; Maidment, D. R.; Mbewe, P.; Merwade, V.; Miles, B.; Reeder, S.; Russell, T.; Song, C.; Taylor, A.; Thakur, S.; Valentine, D. W.; Whiteaker, T. L.

    2013-12-01

    HydroShare is an online, collaborative system being developed for sharing hydrologic data and models as part of the NSF's Software Infrastructure for Sustained Innovation (SI2) program (NSF collaborative award numbers 1148453 and 1148090). HydroShare involves a large software development effort requiring cooperative research and distributed software development between domain scientists, professional software engineers (here 'professional' denotes previous commercial experience in the application of modern software engineering), and university software developers. HydroShare expands upon the data sharing capabilities of the Hydrologic Information System of the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI) by broadening the classes of data accommodated, expanding capability to include the sharing of models and model components, and taking advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. With a goal of enabling better science concomitant with improved sustainable software practices, we will describe our approach, experiences, and lessons learned thus-far in applying professional software engineering to a large NSF-funded software project from the project's onset.

  19. Comparative analysis of articulated and behavioural social networks in a social news sharing website

    NASA Astrophysics Data System (ADS)

    Kaltenbrunner, Andreas; Gonzalez, Gustavo; Ruiz De Querol, Ricard; Volkovich, Yana

    2011-12-01

    This study analyses and contrasts the explicit (articulated) and implicit (behavioural) social networks on the Spanish Digg-like social news website meneame.net. The explicit network is given in the form of declared but not necessarily bidirectional friendship links; the behavioural network is extracted from conversations through comments to the shared links. These two directed social networks and their intersection are analysed and described in detail, which leads to some important conclusions about user behaviour on link sharing websites and online conversation habits in general. We find that reply interactions are more likely to occur between non-friends and that these interactions are (if bidirectional) also more balanced in the case of non-friends. A k-core decomposition of the networks reveals a fundamental difference in the practice of establishing behavioural and articulated links.

  20. Developing A Large-Scale, Collaborative, Productive Geoscience Education Network

    NASA Astrophysics Data System (ADS)

    Manduca, C. A.; Bralower, T. J.; Egger, A. E.; Fox, S.; Ledley, T. S.; Macdonald, H.; Mcconnell, D. A.; Mogk, D. W.; Tewksbury, B. J.

    2012-12-01

    Over the past 15 years, the geoscience education community has grown substantially and developed broad and deep capacity for collaboration and dissemination of ideas. While this community is best viewed as emergent from complex interactions among changing educational needs and opportunities, we highlight the role of several large projects in the development of a network within this community. In the 1990s, three NSF projects came together to build a robust web infrastructure to support the production and dissemination of on-line resources: On The Cutting Edge (OTCE), Earth Exploration Toolbook, and Starting Point: Teaching Introductory Geoscience. Along with the contemporaneous Digital Library for Earth System Education, these projects engaged geoscience educators nationwide in exploring professional development experiences that produced lasting on-line resources, collaborative authoring of resources, and models for web-based support for geoscience teaching. As a result, a culture developed in the 2000s in which geoscience educators anticipated that resources for geoscience teaching would be shared broadly and that collaborative authoring would be productive and engaging. By this time, a diverse set of examples demonstrated the power of the web infrastructure in supporting collaboration, dissemination and professional development . Building on this foundation, more recent work has expanded both the size of the network and the scope of its work. Many large research projects initiated collaborations to disseminate resources supporting educational use of their data. Research results from the rapidly expanding geoscience education research community were integrated into the Pedagogies in Action website and OTCE. Projects engaged faculty across the nation in large-scale data collection and educational research. The Climate Literacy and Energy Awareness Network and OTCE engaged community members in reviewing the expanding body of on-line resources. Building Strong

  1. Survivable VON mapping with ambiguity similitude for differentiable maximum shared capacity in elastic optical networks

    NASA Astrophysics Data System (ADS)

    Yang, Hui; Zhu, Xiaoxu; Bai, Wei; Zhao, Yongli; Zhang, Jie; Liu, Zhu; Zhou, Ziguan; Ou, Qinghai

    2016-09-01

    Virtualization is considered to be a promising solution to support various emerging applications. This paper illustrates the problem of virtual mapping from a new perspective, and mainly focuses on survivable mapping of virtual networks and the potential trade-off between spectral resource usage effectiveness and failure resilience level. We design an optimum shared protection mapping (OSPM) scheme in elastic optical networks. A differentiable maximum shared capacity of each frequency slot is defined to more efficiently shared protection resource. In order to satisfy various assessment standards, a metric called ambiguity similitude is defined for the first time to give insight on the optimizing difficulty. Simulation results are presented to compare the outcome of the novel OSPM algorithm with traditional dedicated link protection and maximum shared protection mapping. By synthetic analysis, OSPM outperforms the other two schemes in terms of striking a perfect balance among blocking probability, resources utilization, protective success rate, and spectrum redundancy.

  2. Accelerated Training for Large Feedforward Neural Networks

    NASA Technical Reports Server (NTRS)

    Stepniewski, Slawomir W.; Jorgensen, Charles C.

    1998-01-01

    In this paper we introduce a new training algorithm, the scaled variable metric (SVM) method. Our approach attempts to increase the convergence rate of the modified variable metric method. It is also combined with the RBackprop algorithm, which computes the product of the matrix of second derivatives (Hessian) with an arbitrary vector. The RBackprop method allows us to avoid computationally expensive, direct line searches. In addition, it can be utilized in the new, 'predictive' updating technique of the inverse Hessian approximation. We have used directional slope testing to adjust the step size and found that this strategy works exceptionally well in conjunction with the Rbackprop algorithm. Some supplementary, but nevertheless important enhancements to the basic training scheme such as improved setting of a scaling factor for the variable metric update and computationally more efficient procedure for updating the inverse Hessian approximation are presented as well. We summarize by comparing the SVM method with four first- and second- order optimization algorithms including a very effective implementation of the Levenberg-Marquardt method. Our tests indicate promising computational speed gains of the new training technique, particularly for large feedforward networks, i.e., for problems where the training process may be the most laborious.

  3. Connection Availability Analysis of Shared Backup Path-Protected Mesh Networks

    NASA Astrophysics Data System (ADS)

    Zhou, Ling; Held, Marcel; Sennhauser, Urs

    2007-05-01

    Dual-span failures dominate the system unavailability in a mesh-restorable network with full restorability to single-span failures. Traditional availability analysis based on reliability block diagrams is not suitable for survivable networks with shared spare capacity. Therefore, a new concept is proposed to facilitate the calculations of connection availability. A U.S. network consisting of 19 nodes and 28 spans yielding 171 bidirectional connections is investigated. We find that networks with shared backup path protection can have average connection unavailabilities of the same order of magnitude as those with dedicated automatic protection switching, however, with a much better capacity efficiency. The proposed method can exactly calculate the unavailability of a specific connection with known restoration details or the average connection performance without any restoration details by presuming the dual-span failures to be the only failure mode and an arbitrary allocation rule of spare capacity.

  4. Validating Large Scale Networks Using Temporary Local Scale Networks

    Technology Transfer Automated Retrieval System (TEKTRAN)

    The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

  5. Gene-sharing networks reveal organizing principles of transcriptomes in Arabidopsis and other multicellular organisms.

    PubMed

    Li, Song; Pandey, Sona; Gookin, Timothy E; Zhao, Zhixin; Wilson, Liza; Assmann, Sarah M

    2012-04-01

    Understanding tissue-related gene expression patterns can provide important insights into gene, tissue, and organ function. Transcriptome analyses often have focused on housekeeping or tissue-specific genes or on gene coexpression. However, by analyzing thousands of single-gene expression distributions in multiple tissues of Arabidopsis thaliana, rice (Oryza sativa), human (Homo sapiens), and mouse (Mus musculus), we found that these organisms primarily operate by gene sharing, a phenomenon where, in each organism, most genes exhibit a high expression level in a few key tissues. We designed an analytical pipeline to characterize this phenomenon and then derived Arabidopsis and human gene-sharing networks, in which tissues are connected solely based on the extent of shared preferentially expressed genes. The results show that tissues or cell types from the same organ system tend to group together to form network modules. Tissues that are in consecutive developmental stages or have common physiological functions are connected in these networks, revealing the importance of shared preferentially expressed genes in conferring specialized functions of each tissue type. The networks provide predictive power for each tissue type regarding gene functions of both known and heretofore unknown genes, as shown by the identification of four new genes with functions in guard cell and abscisic acid response. We provide a Web interface that enables, based on the extent of gene sharing, both prediction of tissue-related functions for any Arabidopsis gene of interest and predictions concerning the relatedness of tissues. Common gene-sharing patterns observed in the four model organisms suggest that gene sharing evolved as a fundamental organizing principle of gene expression in diverse multicellular eukaryotes. PMID:22517316

  6. Heuristic approaches for energy-efficient shared restoration in WDM networks

    NASA Astrophysics Data System (ADS)

    Alilou, Shahab

    In recent years, there has been ongoing research on the design of energy-efficient Wavelength Division Multiplexing (WDM) networks. The explosive growth of Internet traffic has led to increased power consumption of network components. Network survivability has also been a relevant research topic, as it plays a crucial role in assuring continuity of service with no disruption, regardless of network component failure. Network survivability mechanisms tend to utilize considerable resources such as spare capacity in order to protect and restore information. This thesis investigates techniques for reducing energy demand and enhancing energy efficiency in the context of network survivability. We propose two novel heuristic energy-efficient shared protection approaches for WDM networks. These approaches intend to save energy by setting on sleep mode devices that are not being used while providing shared backup paths to satisfy network survivability. The first approach exploits properties of a math series in order to assign weight to the network links. It aims at reducing power consumption at the network indirectly by aggregating traffic on a set of nodes and links with high traffic load level. Routing traffic on links and nodes that are already under utilization makes it possible for the links and nodes with no load to be set on sleep mode. The second approach is intended to dynamically route traffic through nodes and links with high traffic load level. Similar to the first approach, this approach computes a pair of paths for every newly arrived demand. It computes these paths for every new demand by comparing the power consumption of nodes and links in the network before the demand arrives with their potential power consumption if they are chosen along the paths of this demand. Simulations of two different networks were used to compare the total network power consumption obtained using the proposed techniques against a standard shared-path restoration scheme. Shared

  7. Network Computing Infrastructure to Share Tools and Data in Global Nuclear Energy Partnership

    NASA Astrophysics Data System (ADS)

    Kim, Guehee; Suzuki, Yoshio; Teshima, Naoya

    CCSE/JAEA (Center for Computational Science and e-Systems/Japan Atomic Energy Agency) integrated a prototype system of a network computing infrastructure for sharing tools and data to support the U.S. and Japan collaboration in GNEP (Global Nuclear Energy Partnership). We focused on three technical issues to apply our information process infrastructure, which are accessibility, security, and usability. In designing the prototype system, we integrated and improved both network and Web technologies. For the accessibility issue, we adopted SSL-VPN (Security Socket Layer-Virtual Private Network) technology for the access beyond firewalls. For the security issue, we developed an authentication gateway based on the PKI (Public Key Infrastructure) authentication mechanism to strengthen the security. Also, we set fine access control policy to shared tools and data and used shared key based encryption method to protect tools and data against leakage to third parties. For the usability issue, we chose Web browsers as user interface and developed Web application to provide functions to support sharing tools and data. By using WebDAV (Web-based Distributed Authoring and Versioning) function, users can manipulate shared tools and data through the Windows-like folder environment. We implemented the prototype system in Grid infrastructure for atomic energy research: AEGIS (Atomic Energy Grid Infrastructure) developed by CCSE/JAEA. The prototype system was applied for the trial use in the first period of GNEP.

  8. Analyzing large biological datasets with association networks

    SciTech Connect

    Karpinets, T. V.; Park, B. H.; Uberbacher, E. C.

    2012-05-25

    Due to advances in high throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches for timely processing of the collected data into new knowledge. In this study we address this problem by developing a new approach for discovering modular structure, relationships and regularities in complex data. These goals are achieved by converting records of biological annotations of an object, like organism, gene, chemical, sequence, into networks (Anets) and rules (Arules) of the associated annotations. Anets are based on similarity of annotation profiles of objects and can be further analyzed and visualized providing a compact birds-eye view of most significant relationships in the collected data and a way of their clustering and classification. Arules are generated by Apriori considering each record of annotations as a transaction and augmenting each annotation item by its type. Arules provide a way to validate relationships discovered by Anets producing comprehensive statistics on frequently associated annotations and specific confident relationships among them. A combination of Anets and Arules represents condensed information on associations among the collected data, helping to discover new knowledge and generate hypothesis. As an example we have applied the approach to analyze bacterial metadata from the Genomes OnLine Database. The analysis allowed us to produce a map of sequenced bacterial and archaeal organisms based on their genomic, metabolic and physiological characteristics with three major clusters of metadata representing bacterial pathogens, environmental isolates, and plant symbionts. A signature profile of clustered annotations of environmental bacteria if compared with pathogens linked the aerobic respiration, the high GC content and the large genome size to diversity of metabolic activities and physiological features of the organisms.

  9. More than a Master: Developing, Sharing, and Using Knowledge in School-University Research Networks

    ERIC Educational Resources Information Center

    Cornelissen, Frank; Daly, Alan J.; Liou, Yi-Hwa; van Swet, Jacqueline; Beijaard, Douwe; Bergen, Theo C. M.

    2014-01-01

    Postgraduate master's programs for in-service teachers may be a promising new avenue in developing research partnership networks that link schools and university and enable collaborative development, sharing and use of knowledge of teacher research. This study explores the way these knowledge processes originating from master's…

  10. 47 CFR 90.1415 - Establishment, execution, and application of the network sharing agreement.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 47 Telecommunication 5 2012-10-01 2012-10-01 false Establishment, execution, and application of... COMMISSION (CONTINUED) SAFETY AND SPECIAL RADIO SERVICES PRIVATE LAND MOBILE RADIO SERVICES 700 MHz Public/Private Partnership § 90.1415 Establishment, execution, and application of the network sharing...

  11. Confucius Institutes: Distributed Leadership and Knowledge Sharing in a Worldwide Network

    ERIC Educational Resources Information Center

    Li, Hsi Chang; Mirmirani, Sam; Ilacqua, Joseph A.

    2009-01-01

    Purpose: The purpose of this paper is to focus on Confucius Institutes and assess the applicability of theories of leadership and knowledge sharing to multinational organizations and worldwide networks. Growth of multinational trade and decrease in international tension have facilitated the globalization of both profit-seeking and non-profit…

  12. Resource Sharing or Cost Shifting?--The Unequal Burden of Cooperative Cataloging and ILL in Network.

    ERIC Educational Resources Information Center

    Lowry, Charles B.

    1990-01-01

    Examines the dilemmas of participation in resource sharing library networks and proposes solutions based on shifting inducements toward contribution by remunerating the contributing library for the unit cost of original cataloging. A "contribution pricing" model recently announced by OCLC is also evaluated as a possible solution. (21 references)…

  13. World Bank's Global Development Learning Network: Sharing Knowledge Electronically between Nations To "Fight Poverty."

    ERIC Educational Resources Information Center

    Lorenzo, George

    2002-01-01

    Describes the Global Development Learning Network (GDLN), a satellite-driven global communication system developed by the World Bank to help developing countries fight poverty and share in a global exchange of information. Explains Distance Learning Centers that are used by private and public organizations and institutions for distance education…

  14. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking.

    PubMed

    Wang, Mingxun; Carver, Jeremy J; Phelan, Vanessa V; Sanchez, Laura M; Garg, Neha; Peng, Yao; Nguyen, Don Duy; Watrous, Jeramie; Kapono, Clifford A; Luzzatto-Knaan, Tal; Porto, Carla; Bouslimani, Amina; Melnik, Alexey V; Meehan, Michael J; Liu, Wei-Ting; Crüsemann, Max; Boudreau, Paul D; Esquenazi, Eduardo; Sandoval-Calderón, Mario; Kersten, Roland D; Pace, Laura A; Quinn, Robert A; Duncan, Katherine R; Hsu, Cheng-Chih; Floros, Dimitrios J; Gavilan, Ronnie G; Kleigrewe, Karin; Northen, Trent; Dutton, Rachel J; Parrot, Delphine; Carlson, Erin E; Aigle, Bertrand; Michelsen, Charlotte F; Jelsbak, Lars; Sohlenkamp, Christian; Pevzner, Pavel; Edlund, Anna; McLean, Jeffrey; Piel, Jörn; Murphy, Brian T; Gerwick, Lena; Liaw, Chih-Chuang; Yang, Yu-Liang; Humpf, Hans-Ulrich; Maansson, Maria; Keyzers, Robert A; Sims, Amy C; Johnson, Andrew R; Sidebottom, Ashley M; Sedio, Brian E; Klitgaard, Andreas; Larson, Charles B; Boya P, Cristopher A; Torres-Mendoza, Daniel; Gonzalez, David J; Silva, Denise B; Marques, Lucas M; Demarque, Daniel P; Pociute, Egle; O'Neill, Ellis C; Briand, Enora; Helfrich, Eric J N; Granatosky, Eve A; Glukhov, Evgenia; Ryffel, Florian; Houson, Hailey; Mohimani, Hosein; Kharbush, Jenan J; Zeng, Yi; Vorholt, Julia A; Kurita, Kenji L; Charusanti, Pep; McPhail, Kerry L; Nielsen, Kristian Fog; Vuong, Lisa; Elfeki, Maryam; Traxler, Matthew F; Engene, Niclas; Koyama, Nobuhiro; Vining, Oliver B; Baric, Ralph; Silva, Ricardo R; Mascuch, Samantha J; Tomasi, Sophie; Jenkins, Stefan; Macherla, Venkat; Hoffman, Thomas; Agarwal, Vinayak; Williams, Philip G; Dai, Jingqui; Neupane, Ram; Gurr, Joshua; Rodríguez, Andrés M C; Lamsa, Anne; Zhang, Chen; Dorrestein, Kathleen; Duggan, Brendan M; Almaliti, Jehad; Allard, Pierre-Marie; Phapale, Prasad; Nothias, Louis-Felix; Alexandrov, Theodore; Litaudon, Marc; Wolfender, Jean-Luc; Kyle, Jennifer E; Metz, Thomas O; Peryea, Tyler; Nguyen, Dac-Trung; VanLeer, Danielle; Shinn, Paul; Jadhav, Ajit; Müller, Rolf; Waters, Katrina M; Shi, Wenyuan; Liu, Xueting; Zhang, Lixin; Knight, Rob; Jensen, Paul R; Palsson, Bernhard Ø; Pogliano, Kit; Linington, Roger G; Gutiérrez, Marcelino; Lopes, Norberto P; Gerwick, William H; Moore, Bradley S; Dorrestein, Pieter C; Bandeira, Nuno

    2016-08-01

    The potential of the diverse chemistries present in natural products (NP) for biotechnology and medicine remains untapped because NP databases are not searchable with raw data and the NP community has no way to share data other than in published papers. Although mass spectrometry (MS) techniques are well-suited to high-throughput characterization of NP, there is a pressing need for an infrastructure to enable sharing and curation of data. We present Global Natural Products Social Molecular Networking (GNPS; http://gnps.ucsd.edu), an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. In GNPS, crowdsourced curation of freely available community-wide reference MS libraries will underpin improved annotations. Data-driven social-networking should facilitate identification of spectra and foster collaborations. We also introduce the concept of 'living data' through continuous reanalysis of deposited data. PMID:27504778

  15. Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

    NASA Technical Reports Server (NTRS)

    Stoenescu, Tudor M.; Woo, Simon S.

    2009-01-01

    In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

  16. A Scalable Long-Reach Wavelength-Division Multiplexing Access Network Sharing Both Fiber Protection and Broadcasting Services

    NASA Astrophysics Data System (ADS)

    Feng, Chen; Gan, Chaoqin; Gao, Ziyue; Guo, Su; Li, Wei; Fang, Yiqin

    2014-07-01

    A novel scalable wavelength-division multiplexing access network is proposed in this article. By newly designing the remote node, this network can not only support the long-reach transmission and broadcasting services, it can also have flexible scalability and the ability of sharing fiber protection. These make this network have great resilient capability. Also, this scheme still has the characteristic of Rayleigh backscattering mitigation and shared-seeding light of upstream signals. The simulation results indicate this network has good performance.

  17. Molecular analysis reveals high compartmentalization in aphid-primary parasitoid networks and low parasitoid sharing between crop and noncrop habitats.

    PubMed

    Derocles, Stephane A P; Le Ralec, Anne; Besson, Mathilde M; Maret, Marion; Walton, Alan; Evans, Darren M; Plantegenest, Manuel

    2014-08-01

    The ecosystem service of insect pest regulation by natural enemies, such as primary parasitoids, may be enhanced by the presence of uncultivated, semi-natural habitats within agro-ecosystems, although quantifying such host-parasitoid interactions is difficult. Here, we use rRNA 16S gene sequencing to assess both the level of parasitism by Aphidiinae primary parasitoids and parasitoid identity on a large sample of aphids collected in cultivated and uncultivated agricultural habitats in Western France. We used these data to construct ecological networks to assess the level of compartmentalization between aphid and parasitoid food webs of cultivated and uncultivated habitats. We evaluated the extent to which uncultivated margins provided a resource for parasitoids shared between pest and nonpest aphids. We compared the observed quantitative ecological network described by our molecular approach to an empirical qualitative network based on aphid-parasitoid interactions from traditional rearing data found in the literature. We found that the molecular network was highly compartmentalized and that parasitoid sharing is relatively rare between aphids, especially between crop and noncrop compartments. Moreover, the few cases of putative shared generalist parasitoids were questionable and could be due to the lack of discrimination of cryptic species or from intraspecific host specialization. Our results suggest that apparent competition mediated by Aphidiinae parasitoids is probably rare in agricultural areas and that the contribution of field margins as a source of these biocontrol agents is much more limited than expected. Further large-scale (spatial and temporal) studies on other crops and noncrop habitats are needed to confirm this. PMID:24612360

  18. Food-Sharing Networks in Lamalera, Indonesia: Reciprocity, Kinship, and Distance

    PubMed Central

    Nolin, David A.

    2010-01-01

    Exponential random graph modeling (ERGM) is used here to test hypotheses derived from human behavioral ecology about the adaptive nature of human food sharing. Respondents in all (n=317) households in the fishing and sea-hunting village of Lamalera, Indonesia were asked to name those households to whom they had more frequently given (and from whom they had more frequently received) food during the preceding sea-hunting season. The responses were used to construct a social network of between-household food-sharing relationships in the village. The results show that kinship, proximity, and reciprocal sharing all strongly increase the probability of giving food to a household. The effects of kinship and distance are relatively independent of each other, while reciprocity is more common among residentially and genealogically close households. The results show support for reciprocal altruism as a motivation for food sharing while kinship and distance appear to be important partner-choice criteria. PMID:21218145

  19. Categorical Structure among Shared Features in Networks of Early-learned Nouns

    PubMed Central

    Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-01-01

    The shared-features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the overlap of words normatively acquired by children prior to 2 ½ years of age and perceptual and conceptual (functional) features acquired from adult feature generation norms. The resulting networks have small-world structure, indicative of a high degree of feature overlap in local clusters. However, perceptual features—due to their abundance and redundancy—generate networks more robust to feature omissions, while conceptual features are more discriminating and, per feature, offer more categorical information than perceptual features. Using a network specific cluster identification algorithm (the clique percolation method) we also show that shared features among these early learned nouns create higher-order groupings common to adult taxonomic designations. Again, perceptual and conceptual features play distinct roles among different categories, typically with perceptual features being more inclusive and conceptual features being more exclusive of category memberships. The results offer new and testable hypotheses about the role of shared features in human category knowledge. PMID:19576579

  20. Categorical structure among shared features in networks of early-learned nouns.

    PubMed

    Hills, Thomas T; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

    2009-09-01

    The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the overlap of words normatively acquired by children prior to 2(1/2) years of age and perceptual and conceptual (functional) features acquired from adult feature generation norms. The resulting networks have small-world structure, indicative of a high degree of feature overlap in local clusters. However, perceptual features--due to their abundance and redundancy--generate networks more robust to feature omissions, while conceptual features are more discriminating and, per feature, offer more categorical information than perceptual features. Using a network specific cluster identification algorithm (the clique percolation method) we also show that shared features among these early-learned nouns create higher-order groupings common to adult taxonomic designations. Again, perceptual and conceptual features play distinct roles among different categories, typically with perceptual features being more inclusive and conceptual features being more exclusive of category memberships. The results offer new and testable hypotheses about the role of shared features in human category knowledge. PMID:19576579

  1. Beyond Networking: How Large-Scale Change Really Happens

    ERIC Educational Resources Information Center

    Wheatley, Margaret; Frieze, Deborah

    2007-01-01

    Despite the claims of a popular slogan, the world does not change one person at a time. It changes as networks of relationships form among people who share a common cause and vision of what is possible. This is good news for those who want to change public education. Making connections however is not the whole story. This article describes how a…

  2. A comparative analysis of the statistical properties of large mobile phone calling networks.

    PubMed

    Li, Ming-Xia; Jiang, Zhi-Qiang; Xie, Wen-Jie; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2014-01-01

    Mobile phone calling is one of the most widely used communication methods in modern society. The records of calls among mobile phone users provide us a valuable proxy for the understanding of human communication patterns embedded in social networks. Mobile phone users call each other forming a directed calling network. If only reciprocal calls are considered, we obtain an undirected mutual calling network. The preferential communication behavior between two connected users can be statistically tested and it results in two Bonferroni networks with statistically validated edges. We perform a comparative analysis of the statistical properties of these four networks, which are constructed from the calling records of more than nine million individuals in Shanghai over a period of 110 days. We find that these networks share many common structural properties and also exhibit idiosyncratic features when compared with previously studied large mobile calling networks. The empirical findings provide us an intriguing picture of a representative large social network that might shed new lights on the modelling of large social networks. PMID:24875444

  3. Sharing and Specificity of Co-expression Networks across 35 Human Tissues

    PubMed Central

    Pierson, Emma; Koller, Daphne; Battle, Alexis; Mostafavi, Sara

    2015-01-01

    To understand the regulation of tissue-specific gene expression, the GTEx Consortium generated RNA-seq expression data for more than thirty distinct human tissues. This data provides an opportunity for deriving shared and tissue specific gene regulatory networks on the basis of co-expression between genes. However, a small number of samples are available for a majority of the tissues, and therefore statistical inference of networks in this setting is highly underpowered. To address this problem, we infer tissue-specific gene co-expression networks for 35 tissues in the GTEx dataset using a novel algorithm, GNAT, that uses a hierarchy of tissues to share data between related tissues. We show that this transfer learning approach increases the accuracy with which networks are learned. Analysis of these networks reveals that tissue-specific transcription factors are hubs that preferentially connect to genes with tissue specific functions. Additionally, we observe that genes with tissue-specific functions lie at the peripheries of our networks. We identify numerous modules enriched for Gene Ontology functions, and show that modules conserved across tissues are especially likely to have functions common to all tissues, while modules that are upregulated in a particular tissue are often instrumental to tissue-specific function. Finally, we provide a web tool, available at mostafavilab.stat.ubc.ca/GNAT, which allows exploration of gene function and regulation in a tissue-specific manner. PMID:25970446

  4. Does motor imagery share neural networks with executed movement: a multivariate fMRI analysis

    PubMed Central

    Sharma, Nikhil; Baron, Jean-Claude

    2013-01-01

    Introduction: Motor imagery (MI) is the mental rehearsal of a motor first person action-representation. There is interest in using MI to access the motor network after stroke. Conventional fMRI modeling has shown that MI and executed movement (EM) activate similar cortical areas but it remains unknown whether they share cortical networks. Proving this is central to using MI to access the motor network and as a form of motor training. Here we use multivariate analysis (tensor independent component analysis-TICA) to map the array of neural networks involved during MI and EM. Methods: Fifteen right-handed healthy volunteers (mean-age 28.4 years) were recruited and screened for their ability to carry out MI (Chaotic MI Assessment). fMRI consisted of an auditory-paced (1 Hz) right hand finger-thumb opposition sequence (2,3,4,5; 2…) with two separate runs acquired (MI & rest and EM & rest: block design). No distinction was made between MI and EM until the final stage of processing. This allowed TICA to identify independent-components (IC) that are common or distinct to both tasks with no prior assumptions. Results: TICA defined 52 ICs. Non-significant ICs and those representing artifact were excluded. Components in which the subject scores were significantly different to zero (for either EM or MI) were included. Seven IC remained. There were IC's shared between EM and MI involving the contralateral BA4, PMd, parietal areas and SMA. IC's exclusive to EM involved the contralateral BA4, S1 and ipsilateral cerebellum whereas the IC related exclusively to MI involved ipsilateral BA4 and PMd. Conclusion: In addition to networks specific to each task indicating a degree of independence, we formally demonstrate here for the first time that MI and EM share cortical networks. This significantly strengthens the rationale for using MI to access the motor networks, but the results also highlight important differences. PMID:24062666

  5. Comparison of large networks with sub-sampling strategies

    PubMed Central

    Ali, Waqar; Wegner, Anatol E.; Gaunt, Robert E.; Deane, Charlotte M.; Reinert, Gesine

    2016-01-01

    Networks are routinely used to represent large data sets, making the comparison of networks a tantalizing research question in many areas. Techniques for such analysis vary from simply comparing network summary statistics to sophisticated but computationally expensive alignment-based approaches. Most existing methods either do not generalize well to different types of networks or do not provide a quantitative similarity score between networks. In contrast, alignment-free topology based network similarity scores empower us to analyse large sets of networks containing different types and sizes of data. Netdis is such a score that defines network similarity through the counts of small sub-graphs in the local neighbourhood of all nodes. Here, we introduce a sub-sampling procedure based on neighbourhoods which links naturally with the framework of network comparisons through local neighbourhood comparisons. Our theoretical arguments justify basing the Netdis statistic on a sample of similar-sized neighbourhoods. Our tests on empirical and synthetic datasets indicate that often only 10% of the neighbourhoods of a network suffice for optimal performance, leading to a drastic reduction in computational requirements. The sampling procedure is applicable even when only a small sample of the network is known, and thus provides a novel tool for network comparison of very large and potentially incomplete datasets. PMID:27380992

  6. Comparison of large networks with sub-sampling strategies

    NASA Astrophysics Data System (ADS)

    Ali, Waqar; Wegner, Anatol E.; Gaunt, Robert E.; Deane, Charlotte M.; Reinert, Gesine

    2016-07-01

    Networks are routinely used to represent large data sets, making the comparison of networks a tantalizing research question in many areas. Techniques for such analysis vary from simply comparing network summary statistics to sophisticated but computationally expensive alignment-based approaches. Most existing methods either do not generalize well to different types of networks or do not provide a quantitative similarity score between networks. In contrast, alignment-free topology based network similarity scores empower us to analyse large sets of networks containing different types and sizes of data. Netdis is such a score that defines network similarity through the counts of small sub-graphs in the local neighbourhood of all nodes. Here, we introduce a sub-sampling procedure based on neighbourhoods which links naturally with the framework of network comparisons through local neighbourhood comparisons. Our theoretical arguments justify basing the Netdis statistic on a sample of similar-sized neighbourhoods. Our tests on empirical and synthetic datasets indicate that often only 10% of the neighbourhoods of a network suffice for optimal performance, leading to a drastic reduction in computational requirements. The sampling procedure is applicable even when only a small sample of the network is known, and thus provides a novel tool for network comparison of very large and potentially incomplete datasets.

  7. Displacement and deformation measurement for large structures by camera network

    NASA Astrophysics Data System (ADS)

    Shang, Yang; Yu, Qifeng; Yang, Zhen; Xu, Zhiqiang; Zhang, Xiaohu

    2014-03-01

    A displacement and deformation measurement method for large structures by a series-parallel connection camera network is presented. By taking the dynamic monitoring of a large-scale crane in lifting operation as an example, a series-parallel connection camera network is designed, and the displacement and deformation measurement method by using this series-parallel connection camera network is studied. The movement range of the crane body is small, and that of the crane arm is large. The displacement of the crane body, the displacement of the crane arm relative to the body and the deformation of the arm are measured. Compared with a pure series or parallel connection camera network, the designed series-parallel connection camera network can be used to measure not only the movement and displacement of a large structure but also the relative movement and deformation of some interesting parts of the large structure by a relatively simple optical measurement system.

  8. Incentive Mechanism for P2P Content Sharing over Heterogenous Access Networks

    NASA Astrophysics Data System (ADS)

    Sato, Kenichiro; Hashimoto, Ryo; Yoshino, Makoto; Shinkuma, Ryoichi; Takahashi, Tatsuro

    In peer-to-peer (P2P) content sharing, users can share their content by contributing their own resources to one another. However, since there is no incentive for contributing contents or resources to others, users may attempt to obtain content without any contribution. To motivate users to contribute their resources to the service, incentive-rewarding mechanisms have been proposed. On the other hand, emerging wireless technologies, such as IEEE 802.11 wireless local area networks, beyond third generation (B3G) cellular networks and mobile WiMAX, provide high-speed Internet access for wireless users. Using these high-speed wireless access, wireless users can use P2P services and share their content with other wireless users and with fixed users. However, this diversification of access networks makes it difficult to appropriately assign rewards to each user according to their contributions. This is because the cost necessary for contribution is different in different access networks. In this paper, we propose a novel incentive-rewarding mechanism called EMOTIVER that can assign rewards to users appropriately. The proposed mechanism uses an external evaluator and interactive learning agents. We also investigate a way of appropriately controlling rewards based on the system service's quality and managing policy.

  9. Visualization techniques and tools for large geo-physical networks

    NASA Astrophysics Data System (ADS)

    Nocke, Thomas; Buschmann, Stefan; Donges, Jonathan F.; Marwan, Norbert

    2016-04-01

    Network analysis is an important approach in studying complex phenomena within geophysical observation and simulation data. This field produces increasing numbers of large geo-referenced networks to be analyzed. Particular focus lies on the network analysis of the complex statistical interrelationship structure within climatological fields. The typical procedure for such network analyzes is the extraction of network measures in combination with static standard visualization methods. To analyze the visualization challenges within this field, we performed a questionnaire with climate and complex system scientists, and identified a strong requirement for solutions visualizing large and very large geo-referenced networks by providing alternative mappings for static plots and allowing for interactive visualization for networks with 100.000 or even millions of edges. In addition, the questionnaire revealed, that existing interactive visualization methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. Within this presentation, we illustrate how interactive visual analytics methods in combination with geo-visualisation can be tailored for visual large climate network investigation (see as well Nocke et al. 2015). Therefore, we present a survey of requirements of network analysts and the related challenges and, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualization techniques and tools, underpinned with concrete examples from climate network research and innovative solutions (e.g. alternative projections, 3D layered networks) implemented within the network visualization system GTX. References: Nocke, T., S. Buschmann, J. F. Donges, N. Marwan, H.-J. Schulz, and C. Tominski: Review: Visual analytics of climate networks, Nonlinear Processes in Geophysics, 22, 545-570, doi:10.5194/npg-22-545-2015, 2015

  10. Tractable Analysis for Large Social Networks

    ERIC Educational Resources Information Center

    Zhang, Bin

    2012-01-01

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

  11. Evolutionary constraints permeate large metabolic networks

    PubMed Central

    Wagner, Andreas

    2009-01-01

    Background Metabolic networks show great evolutionary plasticity, because they can differ substantially even among closely related prokaryotes. Any one metabolic network can also effectively compensate for the blockage of individual reactions by rerouting metabolic flux through other pathways. These observations, together with the continual discovery of new microbial metabolic pathways and enzymes, raise the possibility that metabolic networks are only weakly constrained in changing their complement of enzymatic reactions. Results To ask whether this is the case, I characterized pairwise and higher-order associations in the co-occurrence of genes encoding metabolic enzymes in more than 200 completely sequenced representatives of prokaryotic genera. The majority of reactions show constrained evolution. Specifically, genes encoding most reactions tend to co-occur with genes encoding other reaction(s). Constrained reaction pairs occur in small sets whose number is substantially greater than expected by chance alone. Most such sets are associated with single biochemical pathways. The respective genes are not always tightly linked, which renders horizontal co-transfer of constrained reaction sets an unlikely sole cause for these patterns of association. Conclusion Even a limited number of available genomes suffices to show that metabolic network evolution is highly constrained by reaction combinations that are favored by natural selection. With increasing numbers of completely sequenced genomes, an evolutionary constraint-based approach may enable a detailed characterization of co-evolving metabolic modules. PMID:19747381

  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. Extracting and Utilizing Social Networks from Log Files of Shared Workspaces

    NASA Astrophysics Data System (ADS)

    Nasirifard, Peyman; Peristeras, Vassilios; Hayes, Conor; Decker, Stefan

    Log files of online shared workspaces contain rich information that can be further analyzed. In this paper, log-file information is used to extract object-centric and user-centric social networks. The object-centric social networks are used as a means for assigning concept-based expertise elements to users based on the documents that they created, revised or read. The user-centric social networks are derived from users working on common documents. Weights, called the Cooperation Index, are assigned to links between users in a user-centric social network, which indicates how closely two people have collaborated together, based on their history. We also present a set of tools that was developed to realize our approach.

  14. Country food sharing networks, household structure, and implications for understanding food insecurity in Arctic Canada.

    PubMed

    Collings, Peter; Marten, Meredith G; Pearce, Tristan; Young, Alyson G

    2016-01-01

    We examine the cultural context of food insecurity among Inuit in Ulukhaktok, Northwest Territories, Canada. An analysis of the social network of country food exchanges among 122 households in the settlement reveals that a household's betweenness centrality-a measure of brokerage-in the country food network is predicted by the age of the household. The households of married couples were better positioned within the sharing network than were the households of single females or single males. Households with an active hunter or elder were also better positioned in the network. The households of single men and women appear to experience limited access to country food, a considerable problem given the increasing number of single-adult households over time. We conclude that the differences between how single women and single men experience constrained access to country foods may partially account for previous findings that single women in arctic settlements appear to be at particular risk for food insecurity. PMID:26595315

  15. A Group Based Key Sharing and Management Algorithm for Vehicular Ad Hoc Networks

    PubMed Central

    Moharram, Mohammed Morsi; Azam, Farzana

    2014-01-01

    Vehicular ad hoc networks (VANETs) are one special type of ad hoc networks that involves vehicles on roads. Typically like ad hoc networks, broadcast approach is used for data dissemination. Blind broadcast to each and every node results in exchange of useless and irrelevant messages and hence creates an overhead. Unicasting is not preferred in ad-hoc networks due to the dynamic topology and the resource requirements as compared to broadcasting. Simple broadcasting techniques create several problems on privacy, disturbance, and resource utilization. In this paper, we propose media mixing algorithm to decide what information should be provided to each user and how to provide such information. Results obtained through simulation show that fewer number of keys are needed to share compared to simple broadcasting. Privacy is also enhanced through this approach. PMID:24587749

  16. A new method optimizing the subgraph centrality of large networks

    NASA Astrophysics Data System (ADS)

    Yan, Xin; Li, Chunlin; Zhang, Ling; Hu, Yaogai

    2016-02-01

    Since many realistic networks such as wireless sensor/ad hoc networks usually do not agree very well with the basic network models such as small-word and scale-free models, we often need to obtain some expected structural features such as a small average path length and a regular degree distribution while optimizing the connectivity of these networks. Although a minor addition of links for optimizing network connectivity is not likely to change the structural properties of a network, it is necessary to investigate the impact of link addition on network properties as the number of the added links increases. However, to the best of our knowledge, the study of that problem has not been found so far. Furthermore, two closely related questions to that problem, i.e., how to measure and how to improve network connectivity, have not been studied carefully enough yet. To address the three problems above, the authors derive a better measure of network connectivity for large networks and a new strategy that can increase/decrease network connectivity the most, and propose a spectral density algorithm optimizing the connectivity of large networks, which is able to indicate the impact on the structural properties of a network while increasing/decreasing its connectivity, providing us a guided optimization of network connectivity. In other words, our algorithm can optimize not only the connectivity of a large network but also its structural features. Meanwhile, our new findings about spectral density are also concluded in this paper. In addition, we may also apply this algorithm to solve all eigenvalues of an N × N matrix, with a low complexity of O(N2) at most.

  17. Measuring structural similarity in large online networks.

    PubMed

    Shi, Yongren; Macy, Michael

    2016-09-01

    Structural similarity based on bipartite graphs can be used to detect meaningful communities, but the networks have been tiny compared to massive online networks. Scalability is important in applications involving tens of millions of individuals with highly skewed degree distributions. Simulation analysis holding underlying similarity constant shows that two widely used measures - Jaccard index and cosine similarity - are biased by the distribution of out-degree in web-scale networks. However, an alternative measure, the Standardized Co-incident Ratio (SCR), is unbiased. We apply SCR to members of Congress, musical artists, and professional sports teams to show how massive co-following on Twitter can be used to map meaningful affiliations among cultural entities, even in the absence of direct connections to one another. Our results show how structural similarity can be used to map cultural alignments and demonstrate the potential usefulness of social media data in the study of culture, politics, and organizations across the social and behavioral sciences. PMID:27480374

  18. 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

  19. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks.

    PubMed

    Fang, Gengfa; Orgun, Mehmet A; Shankaran, Rajan; Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner's bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings. PMID:26844888

  20. Truthful Channel Sharing for Self Coexistence of Overlapping Medical Body Area Networks

    PubMed Central

    Dutkiewicz, Eryk; Zheng, Guanglou

    2016-01-01

    As defined by IEEE 802.15.6 standard, channel sharing is a potential method to coordinate inter-network interference among Medical Body Area Networks (MBANs) that are close to one another. However, channel sharing opens up new vulnerabilities as selfish MBANs may manipulate their online channel requests to gain unfair advantage over others. In this paper, we address this issue by proposing a truthful online channel sharing algorithm and a companion protocol that allocates channel efficiently and truthfully by punishing MBANs for misreporting their channel request parameters such as time, duration and bid for the channel. We first present an online channel sharing scheme for unit-length channel requests and prove that it is truthful. We then generalize our model to settings with variable-length channel requests, where we propose a critical value based channel pricing and preemption scheme. A bid adjustment procedure prevents unbeneficial preemption by artificially raising the ongoing winner’s bid controlled by a penalty factor λ. Our scheme can efficiently detect selfish behaviors by monitoring a trust parameter α of each MBAN and punish MBANs from cheating by suspending their requests. Our extensive simulation results show our scheme can achieve a total profit that is more than 85% of the offline optimum method in the typical MBAN settings. PMID:26844888

  1. LARGE-SCALE TOPOLOGICAL PROPERTIES OF MOLECULAR NETWORKS.

    SciTech Connect

    MASLOV,S.SNEPPEN,K.

    2003-11-17

    Bio-molecular networks lack the top-down design. Instead, selective forces of biological evolution shape them from raw material provided by random events such as gene duplications and single gene mutations. As a result individual connections in these networks are characterized by a large degree of randomness. One may wonder which connectivity patterns are indeed random, while which arose due to the network growth, evolution, and/or its fundamental design principles and limitations? Here we introduce a general method allowing one to construct a random null-model version of a given network while preserving the desired set of its low-level topological features, such as, e.g., the number of neighbors of individual nodes, the average level of modularity, preferential connections between particular groups of nodes, etc. Such a null-model network can then be used to detect and quantify the non-random topological patterns present in large networks. In particular, we measured correlations between degrees of interacting nodes in protein interaction and regulatory networks in yeast. It was found that in both these networks, links between highly connected proteins are systematically suppressed. This effect decreases the likelihood of cross-talk between different functional modules of the cell, and increases the overall robustness of a network by localizing effects of deleterious perturbations. It also teaches us about the overall computational architecture of such networks and points at the origin of large differences in the number of neighbors of individual nodes.

  2. When Sharing Is a Bad Idea: The Effects of Online Social Network Engagement and Sharing Passwords with Friends on Cyberbullying Involvement.

    PubMed

    Meter, Diana J; Bauman, Sheri

    2015-08-01

    Every day, children and adolescents communicate online via social networking sites (SNSs). They also report sharing passwords with peers and friends, a potentially risky behavior in regard to cyber safety. This longitudinal study tested the hypotheses that social network engagement in multiple settings would predict more cyberbullying involvement over time, and that youth who reported sharing passwords would also experience an increase in cyberbullying involvement. Data were collected at two time points one year apart from 1,272 third through eighth grade students. In line with the first study hypothesis, participating in more online SNSs was associated with increased cyberbullying involvement over time, as well as sharing passwords over time. Cyberbullying involvement at T1 predicted decreases in sharing passwords over time, suggesting that youth become aware of the dangers of sharing passwords as a result of their experience. Sharing passwords at T1 was unrelated to cyberbullying involvement at T2. Although it seems that youth may be learning from their previous mistakes, due to the widespread use of social media and normality of sharing passwords among young people, it is important to continue to educate youth about cyber safety and risky online behavior. PMID:26252928

  3. Predictive coding accounts of shared representations in parieto-insular networks.

    PubMed

    Ishida, Hiroaki; Suzuki, Keisuke; Grandi, Laura Clara

    2015-04-01

    The discovery of mirror neurons in the ventral premotor cortex (area F5) and inferior parietal cortex (area PFG) in the macaque monkey brain has provided the physiological evidence for direct matching of the intrinsic motor representations of the self and the visual image of the actions of others. The existence of mirror neurons implies that the brain has mechanisms reflecting shared self and other action representations. This may further imply that the neural basis self-body representations may also incorporate components that are shared with other-body representations. It is likely that such a mechanism is also involved in predicting other's touch sensations and emotions. However, the neural basis of shared body representations has remained unclear. Here, we propose a neural basis of body representation of the self and of others in both human and non-human primates. We review a series of behavioral and physiological findings which together paint a picture that the systems underlying such shared representations require integration of conscious exteroception and interoception subserved by a cortical sensory-motor network involving parieto-inner perisylvian circuits (the ventral intraparietal area [VIP]/inferior parietal area [PFG]-secondary somatosensory cortex [SII]/posterior insular cortex [pIC]/anterior insular cortex [aIC]). Based on these findings, we propose a computational mechanism of the shared body representation in the predictive coding (PC) framework. Our mechanism proposes that processes emerging from generative models embedded in these specific neuronal circuits play a pivotal role in distinguishing a self-specific body representation from a shared one. The model successfully accounts for normal and abnormal shared body phenomena such as mirror-touch synesthesia and somatoparaphrenia. In addition, it generates a set of testable experimental predictions. PMID:25447372

  4. On-demand Overlay Networks for Large Scientific Data Transfers

    SciTech Connect

    Ramakrishnan, Lavanya; Guok, Chin; Jackson, Keith; Kissel, Ezra; Swany, D. Martin; Agarwal, Deborah

    2009-10-12

    Large scale scientific data transfers are central to scientific processes. Data from large experimental facilities have to be moved to local institutions for analysis or often data needs to be moved between local clusters and large supercomputing centers. In this paper, we propose and evaluate a network overlay architecture to enable highthroughput, on-demand, coordinated data transfers over wide-area networks. Our work leverages Phoebus and On-demand Secure Circuits and AdvanceReservation System (OSCARS) to provide high performance wide-area network connections. OSCARS enables dynamic provisioning of network paths with guaranteed bandwidth and Phoebus enables the coordination and effective utilization of the OSCARS network paths. Our evaluation shows that this approach leads to improved end-to-end data transfer throughput with minimal overheads. The achievedthroughput using our overlay was limited only by the ability of the end hosts to sink the data.

  5. Assessment on knowledge network sharing capability of industrial cluster based on dempster-shafer theory of evidence.

    PubMed

    Dai, Shengli; Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research. PMID:24795540

  6. Assessment on Knowledge Network Sharing Capability of Industrial Cluster Based on Dempster-Shafer Theory of Evidence

    PubMed Central

    Zhang, Hailin

    2014-01-01

    Based on Theory of Evidence and reviewing research papers concerned, a concept model of knowledge sharing network among industrial cluster firms, which can be applied to assess knowledge sharing capacity, has been built. Next, the authors create a set of assessment index systems including twelve subindexes under four principle indexes. In this study, ten experts in the same field were invited to score all the indexes of knowledge sharing capacity concerning one certain industrial cluster. The research result shows relatively high knowledge network sharing capacity among the certain industrial cluster firms. Another conclusion is that the assessment method with Theory of Evidence is feasible to conduct such a research. PMID:24795540

  7. Shared “Core” Areas between the Pain and Other Task-Related Networks

    PubMed Central

    Cauda, Franco; Torta, Diana M-E.; Sacco, Katiuscia; Geda, Elisabetta; D’Agata, Federico; Costa, Tommaso; Duca, Sergio; Geminiani, Giuliano; Amanzio, Martina

    2012-01-01

    The idea of a ‘pain matrix’ specifically devoted to the processing of nociceptive inputs has been challenged. Alternative views now propose that the activity of the primary and secondary somatosensory cortices (SI, SII), the insula and cingulate cortex may be related to a basic defensive system through which significant potentially dangerous events for the body's integrity are detected. By reviewing the role of the SI, SII, the cingulate and the insular cortices in the perception of nociceptive and tactile stimuli, in attentional, emotional and reward tasks, and in interoception and memory, we found that all these task-related networks overlap in the dorsal anterior cingulate cortex, the anterior insula and the dorsal medial thalamus. A thorough analysis revealed that the ‘pain-related’ network shares important functional similarities with both somatomotor-somatosensory networks and emotional-interoceptive ones. We suggest that these shared areas constitute the central part of an adaptive control system involved in the processing and integration of salient information coming both from external and internal sources. These areas are activated in almost all fMRI tasks and have been indicated to play a pivotal role in switching between externally directed and internally directed brain networks. PMID:22900003

  8. The development and achievement of a healthy cities network in Taiwan: sharing leadership and partnership building.

    PubMed

    Hu, Susan C; Kuo, Hsien-Wen

    2016-03-01

    The World Health Organization (WHO) Healthy Cities (HC) projects are the best known of the settings-based approaches to health promotion. They engage local governments in health development through a process of political commitment, institutional change, capacity-building, partnership-based planning and innovative projects. Many cities have promoted HC projects in Taiwan since 2002. In 2008, the Taiwan Alliance for Healthy Cities (TAHC) was launched to assist local governments in effectively establishing, operating and promoting HC projects. In this article, we share our experiences of establishing a platform and network to promote the HC program in Taiwan. Based on individual city profiles and governance in Taiwan, the TAHC developed a well-organized framework and model to encourage strong leadership in local governments and to promote participation and engagement in their communities. In the last 6 years, leaders from Taiwan's local governments in HC networks have integrated the HC concepts into their governance models, actively engaging and combining various resources with practical expertise and private sectors. The network of health in Taiwan allows each city to develop its unique perspective on the HC projects. Using this method, not only local government meets its needs, but also increases governance efficiency and effectiveness, resulting in the promotion of its citizens' overall sustainable urban health development. This HC network in Taiwan has partnerships with government and non-governmental organizations (NGOs), with academic support and citizen involvement, a dynamic data collection system and demonstrated leadership in the sharing of information in the Asian region. PMID:27199013

  9. Towards Online Multiresolution Community Detection in Large-Scale Networks

    PubMed Central

    Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

    2011-01-01

    The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

  10. Towards online multiresolution community detection in large-scale networks.

    PubMed

    Huang, Jianbin; Sun, Heli; Liu, Yaguang; Song, Qinbao; Weninger, Tim

    2011-01-01

    The investigation of community structure in networks has aroused great interest in multiple disciplines. One of the challenges is to find local communities from a starting vertex in a network without global information about the entire network. Many existing methods tend to be accurate depending on a priori assumptions of network properties and predefined parameters. In this paper, we introduce a new quality function of local community and present a fast local expansion algorithm for uncovering communities in large-scale networks. The proposed algorithm can detect multiresolution community from a source vertex or communities covering the whole network. Experimental results show that the proposed algorithm is efficient and well-behaved in both real-world and synthetic networks. PMID:21887325

  11. 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

  12. 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

  13. Simulation of large systems with neural networks

    SciTech Connect

    Paez, T.L.

    1994-09-01

    Artificial neural networks (ANNs) have been shown capable of simulating the behavior of complex, nonlinear, systems, including structural systems. Under certain circumstances, it is desirable to simulate structures that are analyzed with the finite element method. For example, when we perform a probabilistic analysis with the Monte Carlo method, we usually perform numerous (hundreds or thousands of) repetitions of a response simulation with different input and system parameters to estimate the chance of specific response behaviors. In such applications, efficiency in computation of response is critical, and response simulation with ANNs can be valuable. However, finite element analyses of complex systems involve the use of models with tens or hundreds of thousands of degrees of freedom, and ANNs are practically limited to simulations that involve far fewer variables. This paper develops a technique for reducing the amount of information required to characterize the response of a general structure. We show how the reduced information can be used to train a recurrent ANN. Then the trained ANN can be used to simulate the reduced behavior of the original system, and the reduction transformation can be inverted to provide a simulation of the original system. A numerical example is presented.

  14. Emergence of large cliques in random scale-free networks

    NASA Astrophysics Data System (ADS)

    Bianconi, Ginestra; Marsili, Matteo

    2006-05-01

    In a network cliques are fully connected subgraphs that reveal which are the tight communities present in it. Cliques of size c > 3 are present in random Erdös and Renyi graphs only in the limit of diverging average connectivity. Starting from the finding that real scale-free graphs have large cliques, we study the clique number in uncorrelated scale-free networks finding both upper and lower bounds. Interestingly, we find that in scale-free networks large cliques appear also when the average degree is finite, i.e. even for networks with power law degree distribution exponents γin(2,3). Moreover, as long as γ < 3, scale-free networks have a maximal clique which diverges with the system size.

  15. Optimal access to large databases via networks

    SciTech Connect

    Munro, J.K.; Fellows, R.L.; Phifer, D. Carrick, M.R.; Tarlton, N.

    1997-10-01

    A CRADA with Stephens Engineering was undertaken in order to transfer knowledge and experience about access to information in large text databases, with results of queries and searches provided using the multimedia capabilities of the World Wide Web. Data access is optimized by the use of intelligent agents. Technology Logic Diagram documents published for the DOE facilities in Oak Ridge (K-25, X-10, Y-12) were chosen for this effort because of the large number of technologies identified, described, evaluated, and ranked for possible use in the environmental remediation of these facilities. Fast, convenient access to this information is difficult because of the volume and complexity of the data. WAIS software used to provide full-text, field-based search capability can also be used, through the development of an appropriate hierarchy of menus, to provide tabular summaries of technologies satisfying a wide range of criteria. The menu hierarchy can also be used to regenerate dynamically many of the tables that appeared in the original hardcopy publications, all from a single text database of the technology descriptions. Use of the Web environment permits linking many of the Technology Logic Diagram references to on-line versions of these publications, particularly the DOE Orders and related directives providing the legal requirements that were the basis for undertaking the Technology Logic Diagram studies in the first place.

  16. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    PubMed Central

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-01-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

  17. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing.

    PubMed

    Fujiwara, M; Waseda, A; Nojima, R; Moriai, S; Ogata, W; Sasaki, M

    2016-01-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir's (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km). PMID:27363566

  18. Unbreakable distributed storage with quantum key distribution network and password-authenticated secret sharing

    NASA Astrophysics Data System (ADS)

    Fujiwara, M.; Waseda, A.; Nojima, R.; Moriai, S.; Ogata, W.; Sasaki, M.

    2016-07-01

    Distributed storage plays an essential role in realizing robust and secure data storage in a network over long periods of time. A distributed storage system consists of a data owner machine, multiple storage servers and channels to link them. In such a system, secret sharing scheme is widely adopted, in which secret data are split into multiple pieces and stored in each server. To reconstruct them, the data owner should gather plural pieces. Shamir’s (k, n)-threshold scheme, in which the data are split into n pieces (shares) for storage and at least k pieces of them must be gathered for reconstruction, furnishes information theoretic security, that is, even if attackers could collect shares of less than the threshold k, they cannot get any information about the data, even with unlimited computing power. Behind this scenario, however, assumed is that data transmission and authentication must be perfectly secure, which is not trivial in practice. Here we propose a totally information theoretically secure distributed storage system based on a user-friendly single-password-authenticated secret sharing scheme and secure transmission using quantum key distribution, and demonstrate it in the Tokyo metropolitan area (≤90 km).

  19. Exhaustive identification of steady state cycles in large stoichiometric networks

    PubMed Central

    Wright, Jeremiah; Wagner, Andreas

    2008-01-01

    Background Identifying cyclic pathways in chemical reaction networks is important, because such cycles may indicate in silico violation of energy conservation, or the existence of feedback in vivo. Unfortunately, our ability to identify cycles in stoichiometric networks, such as signal transduction and genome-scale metabolic networks, has been hampered by the computational complexity of the methods currently used. Results We describe a new algorithm for the identification of cycles in stoichiometric networks, and we compare its performance to two others by exhaustively identifying the cycles contained in the genome-scale metabolic networks of H. pylori, M. barkeri, E. coli, and S. cerevisiae. Our algorithm can substantially decrease both the execution time and maximum memory usage in comparison to the two previous algorithms. Conclusion The algorithm we describe improves our ability to study large, real-world, biochemical reaction networks, although additional methodological improvements are desirable. PMID:18616835

  20. The Structure of Spatial Networks and Communities in Bicycle Sharing Systems

    PubMed Central

    Zaltz Austwick, Martin; O’Brien, Oliver; Strano, Emanuele; Viana, Matheus

    2013-01-01

    Bicycle sharing systems exist in hundreds of cities around the world, with the aim of providing a form of public transport with the associated health and environmental benefits of cycling without the burden of private ownership and maintenance. Five cities have provided research data on the journeys (start and end time and location) taking place in their bicycle sharing system. In this paper, we employ visualization, descriptive statistics and spatial and network analysis tools to explore system usage in these cities, using techniques to investigate features specific to the unique geographies of each, and uncovering similarities between different systems. Journey displacement analysis demonstrates similar journey distances across the cities sampled, and the (out)strength rank curve for the top 50 stands in each city displays a similar scaling law for each. Community detection in the derived network can identify local pockets of use, and spatial network corrections provide the opportunity for insight above and beyond proximity/popularity correlations predicted by simple spatial interaction models. PMID:24040320

  1. Managing ISR sharing policies at the network edge using Controlled English

    NASA Astrophysics Data System (ADS)

    Parizas, Christos; Pizzocaro, Diego; Preece, Alun; Zerfos, Petros

    2013-05-01

    In domains such as emergency response and military operations the sharing of Intelligence, Surveillance and Reconnaissance (ISR) assets among different coalition partners is regulated through policies. Traditionally, poli­ cies are created at the center of a coalitions network by high-level decision makers and expressed in low-level policy languages (e.g. Common Information Model SPL) by technical personnel, which makes them difficult to be understood by non-technical users at the edge of the network. Moreover, policies must often be modified by negotiation among coalition partners, typically in rapid response to the changing operational situation. Com­ monly, the users who must cope first with situational changes are those on the edge, so it would be very effective if they were able to create and negotiate policies themselves. We investigate the use of Controlled English (CE) as a means to define a policy representation that is both human-friendly and machine processable. We show how a CE model can capture a variety of policy types, including those based on a traditional asset ownership model, and those defining team-based asset sharing across a coalition. The use of CE is intended to benefit coalition networks by bridging the gap between technical and non-technical users in terms of policy creation and negoti­ ation, while at the same time being directly processable by a policy-checking system without transformation to any other technical representation.

  2. Implicit and explicit social mentalizing: dual processes driven by a shared neural network

    PubMed Central

    Van Overwalle, Frank; Vandekerckhove, Marie

    2013-01-01

    Recent social neuroscientific evidence indicates that implicit and explicit inferences on the mind of another person (i.e., intentions, attributions or traits), are subserved by a shared mentalizing network. Under both implicit and explicit instructions, ERP studies reveal that early inferences occur at about the same time, and fMRI studies demonstrate an overlap in core mentalizing areas, including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC). These results suggest a rapid shared implicit intuition followed by a slower explicit verification processes (as revealed by additional brain activation during explicit vs. implicit inferences). These data provide support for a default-adjustment dual-process framework of social mentalizing. PMID:24062663

  3. Comparative Study of Message Passing and Shared Memory Parallel Programming Models in Neural Network Training

    SciTech Connect

    Vitela, J.; Gordillo, J.; Cortina, L; Hanebutte, U.

    1999-12-14

    It is presented a comparative performance study of a coarse grained parallel neural network training code, implemented in both OpenMP and MPI, standards for shared memory and message passing parallel programming environments, respectively. In addition, these versions of the parallel training code are compared to an implementation utilizing SHMEM the native SGI/CRAY environment for shared memory programming. The multiprocessor platform used is a SGI/Cray Origin 2000 with up to 32 processors. It is shown that in this study, the native CRAY environment outperforms MPI for the entire range of processors used, while OpenMP shows better performance than the other two environments when using more than 19 processors. In this study, the efficiency is always greater than 60% regardless of the parallel programming environment used as well as of the number of processors.

  4. The Deep Space Network Large Array

    NASA Astrophysics Data System (ADS)

    Gatti, M. S.

    2004-05-01

    In recent years it has become evident that, if future science needs are to be met, the capacity of the telecommunications link between planetary spacecraft and the Earth must be increased by orders of magnitude. Both the number of spacecraft and higher data rates demand the increased capacity. Technologies to support the increased capacity include even larger antennas, optical receiving systems, or arrays of antennas. This article describes a large array of small antennas that would be implemented for a fraction of the cost of an equivalent 70-m aperture. Adding additional antennas can increase the sensitivity many fold over current capabilities. The array will consist of 400 parabolic reflector antennas, each of which will be 12 m in diameter. Each antenna will operate simultaneously at both X-band (8 to 8.8 GHz) and Ka-band (31 to 38 GHz) and will be configured with radio frequency (RF) electronics, including the feeds, low-noise amplifiers, and frequency converters, as well as the appropriate servo controls and drives. The array also includes the signal transmission and signal processing to enable the system to track from between 1 and 16 different signals. A significant feature of this system is that it will be done for relatively very low cost compared to the current antenna paradigms. This is made possible by the use of low-cost antenna reflector technology, the extensive use of monolithic microwave integrated circuits (MMICs), and, finally, by using commercially available equipment to the maximum extent possible. Cost can be further reduced by the acceptance of lower antenna element reliability. High system availability will be maintained by a design paradigm that provides for a marginal set of excess antenna elements for any particular tracking period. Thus, the same total system availability is achieved for lower element availability. The "plug-and-play" aspects of the assemblies will enhance maintainability and operability. The project plans include a

  5. Control and management of large and dynamic networks

    SciTech Connect

    Tsai, W.T.

    1986-01-01

    Dynamic networks are computer networks whose links and nodes could fail and recover frequently. The nodes may also be mobile. Large dynamic networks are dynamic networks of large size and they are clustered as hierarchical networks. The objective of this research task is to design a mechanism to support nodes to communicate with each other. To communicate with each other, the nodes would first have to know the names of other nodes, then their addresses, and finally the routes. Thus, the network should provide two mechanisms to supports the communications: binding of names of nodes with their addresses, and binding of address of nodes to the routes dynamically. The first problem, i.e., bind the names of nodes with their addresses, is usually called the naming or addressing problem. The second problem, i.e., binding the addresses with the corresponding routes, is conventionally called the routing problem. This dissertation discusses techniques to handle both problems. The author first discusses techniques for the routing problem. As the network is assumed to be very large and dynamic, he concentrates on developing hierarchical routing algorithms. A new adaptive hierarchical routing algorithm is proposed. The algorithm is based on the new Arpanet algorithm. The algorithm is good for both updating and initialization the routing tables.

  6. 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.

  7. Detection and classification of MSTAR objects via morphological shared-weight neural networks

    NASA Astrophysics Data System (ADS)

    Theera-Umpon, Nipon; Khabou, Mohamed A.; Gader, Paul D.; Keller, James M.; Shi, Hongchi; Li, Hongzheng

    1998-09-01

    In this paper we describe the application of morphological shared-weight neural networks to the problems of classification and detection of vehicles in synthetic aperture radar (SAR). Classification experiments were carried out with SAR images of T72 tanks and armored personnel carriers. A correct classification rate of more than 98% was achieved on a testing data set. Detection experiments were carried out with T72 tanks embedded in SAR images of clutter scenes. A near perfect detection rate and a low false alarm rate were achieved. The data used in the experiments was the standard training and testing MSTAR data set collected by Sandia National Laboratory.

  8. Making Large-Scale Networks from fMRI Data

    PubMed Central

    Schmittmann, Verena D.; Jahfari, Sara; Borsboom, Denny; Savi, Alexander O.; Waldorp, Lourens J.

    2015-01-01

    Pairwise correlations are currently a popular way to estimate a large-scale network (> 1000 nodes) from functional magnetic resonance imaging data. However, this approach generally results in a poor representation of the true underlying network. The reason is that pairwise correlations cannot distinguish between direct and indirect connectivity. As a result, pairwise correlation networks can lead to fallacious conclusions; for example, one may conclude that a network is a small-world when it is not. In a simulation study and an application to resting-state fMRI data, we compare the performance of pairwise correlations in large-scale networks (2000 nodes) against three other methods that are designed to filter out indirect connections. Recovery methods are evaluated in four simulated network topologies (small world or not, scale-free or not) in scenarios where the number of observations is very small compared to the number of nodes. Simulations clearly show that pairwise correlation networks are fragmented into separate unconnected components with excessive connectedness within components. This often leads to erroneous estimates of network metrics, like small-world structures or low betweenness centrality, and produces too many low-degree nodes. We conclude that using partial correlations, informed by a sparseness penalty, results in more accurate networks and corresponding metrics than pairwise correlation networks. However, even with these methods, the presence of hubs in the generating network can be problematic if the number of observations is too small. Additionally, we show for resting-state fMRI that partial correlations are more robust than correlations to different parcellation sets and to different lengths of time-series. PMID:26325185

  9. Functional interactions between large-scale networks during memory search.

    PubMed

    Kragel, James E; Polyn, Sean M

    2015-03-01

    Neuroimaging studies have identified two major large-scale brain networks, the default mode network (DMN) and the dorsal attention network (DAN), which are engaged for internally and externally directed cognitive tasks respectively, and which show anticorrelated activity during cognitively demanding tests and at rest. We identified these brain networks using independent component analysis (ICA) of functional magnetic resonance imaging data, and examined their interactions during the free-recall task, a self-initiated memory search task in which retrieval is performed in the absence of external cues. Despite the internally directed nature of the task, the DAN showed transient engagement in the seconds leading up to successful retrieval. ICA revealed a fractionation of the DMN into 3 components. A posteromedial network increased engagement during memory search, while the two others showed suppressed activity during memory search. Cooperative interactions between this posteromedial network, a right-lateralized frontoparietal control network, and a medial prefrontal network were maintained during memory search. The DAN demonstrated heterogeneous task-dependent shifts in functional coupling with various subnetworks within the DMN. This functional reorganization suggests a broader role of the DAN in the absence of externally directed cognition, and highlights the contribution of the posteromedial network to episodic retrieval. PMID:24084128

  10. States of mind: Emotions, body feelings, and thoughts share distributed neural networks

    PubMed Central

    Oosterwijk, Suzanne; Lindquist, Kristen A.; Anderson, Eric; Dautoff, Rebecca; Moriguchi, Yoshiya; Barrett, Lisa Feldman

    2012-01-01

    Scientists have traditionally assumed that different kinds of mental states (e.g., fear, disgust, love, memory, planning, concentration, etc.) correspond to different psychological faculties that have domain-specific correlates in the brain. Yet, growing evidence points to the constructionist hypothesis that mental states emerge from the combination of domain-general psychological processes that map to large-scale distributed brain networks. In this paper, we report a novel study testing a constructionist model of the mind in which participants generated three kinds of mental states (emotions, body feelings, or thoughts) while we measured activity within large-scale distributed brain networks using fMRI. We examined the similarity and differences in the pattern of network activity across these three classes of mental states. Consistent with a constructionist hypothesis, a combination of large-scale distributed networks contributed to emotions, thoughts, and body feelings, although these mental states differed in the relative contribution of those networks. Implications for a constructionist functional architecture of diverse mental states are discussed. PMID:22677148

  11. Predicting Positive and Negative Relationships in Large Social Networks

    PubMed Central

    Wang, Guan-Nan; Gao, Hui; Chen, Lian; Mensah, Dennis N. A.; Fu, Yan

    2015-01-01

    In a social network, users hold and express positive and negative attitudes (e.g. support/opposition) towards other users. Those attitudes exhibit some kind of binary relationships among the users, which play an important role in social network analysis. However, some of those binary relationships are likely to be latent as the scale of social network increases. The essence of predicting latent binary relationships have recently began to draw researchers' attention. In this paper, we propose a machine learning algorithm for predicting positive and negative relationships in social networks inspired by structural balance theory and social status theory. More specifically, we show that when two users in the network have fewer common neighbors, the prediction accuracy of the relationship between them deteriorates. Accordingly, in the training phase, we propose a segment-based training framework to divide the training data into two subsets according to the number of common neighbors between users, and build a prediction model for each subset based on support vector machine (SVM). Moreover, to deal with large-scale social network data, we employ a sampling strategy that selects small amount of training data while maintaining high accuracy of prediction. We compare our algorithm with traditional algorithms and adaptive boosting of them. Experimental results of typical data sets show that our algorithm can deal with large social networks and consistently outperforms other methods. PMID:26075404

  12. Experimental performance evaluation of software defined networking (SDN) based data communication networks for large scale flexi-grid optical networks.

    PubMed

    Zhao, Yongli; He, Ruiying; Chen, Haoran; Zhang, Jie; Ji, Yuefeng; Zheng, Haomian; Lin, Yi; Wang, Xinbo

    2014-04-21

    Software defined networking (SDN) has become the focus in the current information and communication technology area because of its flexibility and programmability. It has been introduced into various network scenarios, such as datacenter networks, carrier networks, and wireless networks. Optical transport network is also regarded as an important application scenario for SDN, which is adopted as the enabling technology of data communication networks (DCN) instead of general multi-protocol label switching (GMPLS). However, the practical performance of SDN based DCN for large scale optical networks, which is very important for the technology selection in the future optical network deployment, has not been evaluated up to now. In this paper we have built a large scale flexi-grid optical network testbed with 1000 virtual optical transport nodes to evaluate the performance of SDN based DCN, including network scalability, DCN bandwidth limitation, and restoration time. A series of network performance parameters including blocking probability, bandwidth utilization, average lightpath provisioning time, and failure restoration time have been demonstrated under various network environments, such as with different traffic loads and different DCN bandwidths. The demonstration in this work can be taken as a proof for the future network deployment. PMID:24787842

  13. The Climate-G testbed: towards a large scale data sharing environment for climate change

    NASA Astrophysics Data System (ADS)

    Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

    2009-04-01

    The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for

  14. EPPS: Efficient and Privacy-Preserving Personal Health Information Sharing in Mobile Healthcare Social Networks

    PubMed Central

    Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin

    2015-01-01

    Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients’ full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs. PMID:26404300

  15. EPPS: Efficient and Privacy-Preserving Personal Health Information Sharing in Mobile Healthcare Social Networks.

    PubMed

    Jiang, Shunrong; Zhu, Xiaoyan; Wang, Liangmin

    2015-01-01

    Mobile healthcare social networks (MHSNs) have emerged as a promising next-generation healthcare system, which will significantly improve the quality of life. However, there are many security and privacy concerns before personal health information (PHI) is shared with other parities. To ensure patients' full control over their PHI, we propose a fine-grained and scalable data access control scheme based on attribute-based encryption (ABE). Besides, policies themselves for PHI sharing may be sensitive and may reveal information about underlying PHI or about data owners or recipients. In our scheme, we let each attribute contain an attribute name and its value and adopt the Bloom filter to efficiently check attributes before decryption. Thus, the data privacy and policy privacy can be preserved in our proposed scheme. Moreover, considering the fact that the computational cost grows with the complexity of the access policy and the limitation of the resource and energy in a smart phone, we outsource ABE decryption to the cloud while preventing the cloud from learning anything about the content and access policy. The security and performance analysis is carried out to demonstrate that our proposed scheme can achieve fine-grained access policies for PHI sharing in MHSNs. PMID:26404300

  16. Optical Shared Memory Computing and Multiple Access Protocols for Photonic Networks

    NASA Astrophysics Data System (ADS)

    Li, Kuang-Yu.

    In this research we investigate potential applications of optics in massively parallel computer systems, especially focusing on design issues in three-dimensional optical data storage and free-space photonic networks. An optical implementation of a shared memory uses a single photorefractive crystal and can realize the set of memory modules in a digital shared memory computer. A complete instruction set consists of R sc EAD, W sc RITE, S sc ELECTIVE E sc RASE, and R sc EFRESH, which can be applied to any memory module independent of (and in parallel with) instructions to the other memory modules. In addition, a memory module can execute a sequence of R sc EAD operations simultaneously with the execution of a W sc RITE operation to accommodate differences in optical recording and readout times common to optical volume storage media. An experimental shared memory system is demonstrated and its projected performance is analyzed. A multiplexing technique is presented to significantly reduce both grating- and beam-degeneracy crosstalk in volume holographic systems, by incorporating space, angle, and wavelength as the multiplexing parameters. In this approach, each hologram, which results from the interference between a single input node and an object array, partially overlaps with the other holograms in its neighborhood. This technique can offer improved interconnection density, optical throughput, signal fidelity, and space-bandwidth product utilization. Design principles and numerical simulation results are presented. A free-space photonic cellular hypercube parallel computer, with emphasis on the design of a collisionless multiple access protocol, is presented. This design incorporates wavelength-, space-, and time-multiplexing to achieve multiple access, wavelength reuse, dense connectivity, collisionless communications, and a simple control mechanism. Analytic models based on semi-Markov processes are employed to analyze this protocol. The performance of the

  17. Congenital blindness is associated with large-scale reorganization of anatomical networks

    PubMed Central

    Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

    2016-01-01

    Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind. PMID:26767944

  18. Congenital blindness is associated with large-scale reorganization of anatomical networks.

    PubMed

    Hasson, Uri; Andric, Michael; Atilgan, Hicret; Collignon, Olivier

    2016-03-01

    Blindness is a unique model for understanding the role of experience in the development of the brain's functional and anatomical architecture. Documenting changes in the structure of anatomical networks for this population would substantiate the notion that the brain's core network-level organization may undergo neuroplasticity as a result of life-long experience. To examine this issue, we compared whole-brain networks of regional cortical-thickness covariance in early blind and matched sighted individuals. This covariance is thought to reflect signatures of integration between systems involved in similar perceptual/cognitive functions. Using graph-theoretic metrics, we identified a unique mode of anatomical reorganization in the blind that differed from that found for sighted. This was seen in that network partition structures derived from subgroups of blind were more similar to each other than they were to partitions derived from sighted. Notably, after deriving network partitions, we found that language and visual regions tended to reside within separate modules in sighted but showed a pattern of merging into shared modules in the blind. Our study demonstrates that early visual deprivation triggers a systematic large-scale reorganization of whole-brain cortical-thickness networks, suggesting changes in how occipital regions interface with other functional networks in the congenitally blind. PMID:26767944

  19. Folksonomical P2P File Sharing Networks Using Vectorized KANSEI Information as Search Tags

    NASA Astrophysics Data System (ADS)

    Ohnishi, Kei; Yoshida, Kaori; Oie, Yuji

    We present the concept of folksonomical peer-to-peer (P2P) file sharing networks that allow participants (peers) to freely assign structured search tags to files. These networks are similar to folksonomies in the present Web from the point of view that users assign search tags to information distributed over a network. As a concrete example, we consider an unstructured P2P network using vectorized Kansei (human sensitivity) information as structured search tags for file search. Vectorized Kansei information as search tags indicates what participants feel about their files and is assigned by the participant to each of their files. A search query also has the same form of search tags and indicates what participants want to feel about files that they will eventually obtain. A method that enables file search using vectorized Kansei information is the Kansei query-forwarding method, which probabilistically propagates a search query to peers that are likely to hold more files having search tags that are similar to the query. The similarity between the search query and the search tags is measured in terms of their dot product. The simulation experiments examine if the Kansei query-forwarding method can provide equal search performance for all peers in a network in which only the Kansei information and the tendency with respect to file collection are different among all of the peers. The simulation results show that the Kansei query forwarding method and a random-walk-based query forwarding method, for comparison, work effectively in different situations and are complementary. Furthermore, the Kansei query forwarding method is shown, through simulations, to be superior to or equal to the random-walk based one in terms of search speed.

  20. Semantic overlay network for large-scale spatial information indexing

    NASA Astrophysics Data System (ADS)

    Zou, Zhiqiang; Wang, Yue; Cao, Kai; Qu, Tianshan; Wang, Zhongmin

    2013-08-01

    The increased demand for online services of spatial information poses new challenges to the combined filed of Computer Science and Geographic Information Science. Amongst others, these include fast indexing of spatial data in distributed networks. In this paper we propose a novel semantic overlay network for large-scale multi-dimensional spatial information indexing, called SON_LSII, which has a hybrid structure integrating a semantic quad-tree and Chord ring. The SON_LSII is a small world overlay network that achieves a very competitive trade-off between indexing efficiency and maintenance overhead. To create SON_LSII, we use an effective semantic clustering strategy that considers two aspects, i.e., the semantic of spatial information that peer holds in overlay network and physical network performances. Based on SON_LSII, a mapping method is used to reduce the multi-dimensional features into a single dimension and an efficient indexing algorithm is presented to support complex range queries of the spatial information with a massive number of concurrent users. The results from extensive experiments demonstrate that SON_LSII is superior to existing overlay networks in various respects, including scalability, maintenance, rate of indexing hits, indexing logical hops, and adaptability. Thus, the proposed SON_LSII can be used for large-scale spatial information indexing.

  1. Multi-dimension and Comprehensive Assessment on the Utilizing and Sharing of Regional Large-Scale Scientific Equipment

    PubMed Central

    Li, Chen; Yongbo, Lv; Chi, Chen

    2015-01-01

    Based on the data from 30 provincial regions in China, an assessment and empirical analysis was carried out on the utilizing and sharing of the large-scale scientific equipment with a comprehensive assessment model established on the three dimensions, namely, equipment, utilization and sharing. The assessment results were interpreted in light of relevant policies. The results showed that on the whole, the overall development level in the provincial regions in eastern and central China is higher than that in western China. This is mostly because of the large gap among the different provincial regions with respect to the equipped level. But in terms of utilizing and sharing, some of the Western provincial regions, such as Ningxia, perform well, which is worthy of our attention. Policy adjustment targeting at the differentiation, elevation of the capacity of the equipment management personnel, perfection of the sharing and cooperation platform, and the promotion of the establishment of open sharing funds, are all important measures to promote the utilization and sharing of the large-scale scientific equipment and to narrow the gap among different regions. PMID:25937850

  2. Application of the EVEX resource to event extraction and network construction: Shared Task entry and result analysis

    PubMed Central

    2015-01-01

    Background Modern methods for mining biomolecular interactions from literature typically make predictions based solely on the immediate textual context, in effect a single sentence. No prior work has been published on extending this context to the information automatically gathered from the whole biomedical literature. Thus, our motivation for this study is to explore whether mutually supporting evidence, aggregated across several documents can be utilized to improve the performance of the state-of-the-art event extraction systems. In this paper, we describe our participation in the latest BioNLP Shared Task using the large-scale text mining resource EVEX. We participated in the Genia Event Extraction (GE) and Gene Regulation Network (GRN) tasks with two separate systems. In the GE task, we implemented a re-ranking approach to improve the precision of an existing event extraction system, incorporating features from the EVEX resource. In the GRN task, our system relied solely on the EVEX resource and utilized a rule-based conversion algorithm between the EVEX and GRN formats. Results In the GE task, our re-ranking approach led to a modest performance increase and resulted in the first rank of the official Shared Task results with 50.97% F-score. Additionally, in this paper we explore and evaluate the usage of distributed vector representations for this challenge. In the GRN task, we ranked fifth in the official results with a strict/relaxed SER score of 0.92/0.81 respectively. To try and improve upon these results, we have implemented a novel machine learning based conversion system and benchmarked its performance against the original rule-based system. Conclusions For the GRN task, we were able to produce a gene regulatory network from the EVEX data, warranting the use of such generic large-scale text mining data in network biology settings. A detailed performance and error analysis provides more insight into the relatively low recall rates. In the GE task we

  3. Complex networks with large numbers of labelable attractors

    NASA Astrophysics Data System (ADS)

    Mi, Yuanyuan; Zhang, Lisheng; Huang, Xiaodong; Qian, Yu; Hu, Gang; Liao, Xuhong

    2011-09-01

    Information storage in many functional subsystems of the brain is regarded by theoretical neuroscientists to be related to attractors of neural networks. The number of attractors is large and each attractor can be temporarily represented or suppressed easily by corresponding external stimulus. In this letter, we discover that complex networks consisting of excitable nodes have similar fascinating properties of coexistence of large numbers of oscillatory attractors, most of which can be labeled with a few nodes. According to a simple labeling rule, different attractors can be identified and the number of labelable attractors can be predicted from the analysis of network topology. With the cues of the labeling association, these attractors can be conveniently retrieved or suppressed on purpose.

  4. DESIGN OF LARGE-SCALE AIR MONITORING NETWORKS

    EPA Science Inventory

    The potential effects of air pollution on human health have received much attention in recent years. In the U.S. and other countries, there are extensive large-scale monitoring networks designed to collect data to inform the public of exposure risks to air pollution. A major crit...

  5. Large-Scale Networked Virtual Environments: Architecture and Applications

    ERIC Educational Resources Information Center

    Lamotte, Wim; Quax, Peter; Flerackers, Eddy

    2008-01-01

    Purpose: Scalability is an important research topic in the context of networked virtual environments (NVEs). This paper aims to describe the ALVIC (Architecture for Large-scale Virtual Interactive Communities) approach to NVE scalability. Design/methodology/approach: The setup and results from two case studies are shown: a 3-D learning environment…

  6. Dataworks for GNSS: Software for Supporting Data Sharing and Federation of Geodetic Networks

    NASA Astrophysics Data System (ADS)

    Boler, F. M.; Meertens, C. M.; Miller, M. M.; Wier, S.; Rost, M.; Matykiewicz, J.

    2015-12-01

    Continuously-operating Global Navigation Satellite System (GNSS) networks are increasingly being installed globally for a wide variety of science and societal applications. GNSS enables Earth science research in areas including tectonic plate interactions, crustal deformation in response to loading by tectonics, magmatism, water and ice, and the dynamics of water - and thereby energy transfer - in the atmosphere at regional scale. The many individual scientists and organizations that set up GNSS stations globally are often open to sharing data, but lack the resources or expertise to deploy systems and software to manage and curate data and metadata and provide user tools that would support data sharing. UNAVCO previously gained experience in facilitating data sharing through the NASA-supported development of the Geodesy Seamless Archive Centers (GSAC) open source software. GSAC provides web interfaces and simple web services for data and metadata discovery and access, supports federation of multiple data centers, and simplifies transfer of data and metadata to long-term archives. The NSF supported the dissemination of GSAC to multiple European data centers forming the European Plate Observing System. To expand upon GSAC to provide end-to-end, instrument-to-distribution capability, UNAVCO developed Dataworks for GNSS with NSF funding to the COCONet project, and deployed this software on systems that are now operating as Regional GNSS Data Centers as part of the NSF-funded TLALOCNet and COCONet projects. Dataworks consists of software modules written in Python and Java for data acquisition, management and sharing. There are modules for GNSS receiver control and data download, a database schema for metadata, tools for metadata handling, ingest software to manage file metadata, data file management scripts, GSAC, scripts for mirroring station data and metadata from partner GSACs, and extensive software and operator documentation. UNAVCO plans to provide a cloud VM

  7. Conserved Noncoding Sequences Highlight Shared Components of Regulatory Networks in Dicotyledonous Plants[W

    PubMed Central

    Baxter, Laura; Jironkin, Aleksey; Hickman, Richard; Moore, Jay; Barrington, Christopher; Krusche, Peter; Dyer, Nigel P.; Buchanan-Wollaston, Vicky; Tiskin, Alexander; Beynon, Jim; Denby, Katherine; Ott, Sascha

    2012-01-01

    Conserved noncoding sequences (CNSs) in DNA are reliable pointers to regulatory elements controlling gene expression. Using a comparative genomics approach with four dicotyledonous plant species (Arabidopsis thaliana, papaya [Carica papaya], poplar [Populus trichocarpa], and grape [Vitis vinifera]), we detected hundreds of CNSs upstream of Arabidopsis genes. Distinct positioning, length, and enrichment for transcription factor binding sites suggest these CNSs play a functional role in transcriptional regulation. The enrichment of transcription factors within the set of genes associated with CNS is consistent with the hypothesis that together they form part of a conserved transcriptional network whose function is to regulate other transcription factors and control development. We identified a set of promoters where regulatory mechanisms are likely to be shared between the model organism Arabidopsis and other dicots, providing areas of focus for further research. PMID:23110901

  8. Development of large-scale functional brain networks in children.

    PubMed

    Supekar, Kaustubh; Musen, Mark; Menon, Vinod

    2009-07-01

    The ontogeny of large-scale functional organization of the human brain is not well understood. Here we use network analysis of intrinsic functional connectivity to characterize the organization of brain networks in 23 children (ages 7-9 y) and 22 young-adults (ages 19-22 y). Comparison of network properties, including path-length, clustering-coefficient, hierarchy, and regional connectivity, revealed that although children and young-adults' brains have similar "small-world" organization at the global level, they differ significantly in hierarchical organization and interregional connectivity. We found that subcortical areas were more strongly connected with primary sensory, association, and paralimbic areas in children, whereas young-adults showed stronger cortico-cortical connectivity between paralimbic, limbic, and association areas. Further, combined analysis of functional connectivity with wiring distance measures derived from white-matter fiber tracking revealed that the development of large-scale brain networks is characterized by weakening of short-range functional connectivity and strengthening of long-range functional connectivity. Importantly, our findings show that the dynamic process of over-connectivity followed by pruning, which rewires connectivity at the neuronal level, also operates at the systems level, helping to reconfigure and rebalance subcortical and paralimbic connectivity in the developing brain. Our study demonstrates the usefulness of network analysis of brain connectivity to elucidate key principles underlying functional brain maturation, paving the way for novel studies of disrupted brain connectivity in neurodevelopmental disorders such as autism. PMID:19621066

  9. Development of large-scale functional networks over the lifespan.

    PubMed

    Schlee, Winfried; Leirer, Vera; Kolassa, Stephan; Thurm, Franka; Elbert, Thomas; Kolassa, Iris-Tatjana

    2012-10-01

    The development of large-scale functional organization of the human brain across the lifespan is not well understood. Here we used magnetoencephalographic recordings of 53 adults (ages 18-89) to characterize functional brain networks in the resting state. Slow frequencies engage larger networks than higher frequencies and show different development over the lifespan. Networks in the delta (2-4 Hz) frequency range decrease, while networks in the beta/gamma frequency range (> 16 Hz) increase in size with advancing age. Results show that the right frontal lobe and the temporal areas in both hemispheres are important relay stations in the expanding high-frequency networks. Neuropsychological tests confirmed the tendency of cognitive decline with older age. The decrease in visual memory and visuoconstructive functions was strongly associated with the age-dependent enhancement of functional connectivity in both temporal lobes. Using functional network analysis this study elucidates important neuronal principles underlying age-related cognitive decline paving mental deterioration in senescence. PMID:22236372

  10. Large-scale functional connectivity networks in the rodent brain.

    PubMed

    Gozzi, Alessandro; Schwarz, Adam J

    2016-02-15

    Resting-state functional Magnetic Resonance Imaging (rsfMRI) of the human brain has revealed multiple large-scale neural networks within a hierarchical and complex structure of coordinated functional activity. These distributed neuroanatomical systems provide a sensitive window on brain function and its disruption in a variety of neuropathological conditions. The study of macroscale intrinsic connectivity networks in preclinical species, where genetic and environmental conditions can be controlled and manipulated with high specificity, offers the opportunity to elucidate the biological determinants of these alterations. While rsfMRI methods are now widely used in human connectivity research, these approaches have only relatively recently been back-translated into laboratory animals. Here we review recent progress in the study of functional connectivity in rodent species, emphasising the ability of this approach to resolve large-scale brain networks that recapitulate neuroanatomical features of known functional systems in the human brain. These include, but are not limited to, a distributed set of regions identified in rats and mice that may represent a putative evolutionary precursor of the human default mode network (DMN). The impact and control of potential experimental and methodological confounds are also critically discussed. Finally, we highlight the enormous potential and some initial application of connectivity mapping in transgenic models as a tool to investigate the neuropathological underpinnings of the large-scale connectional alterations associated with human neuropsychiatric and neurological conditions. We conclude by discussing the translational potential of these methods in basic and applied neuroscience. PMID:26706448

  11. Using Agent Base Models to Optimize Large Scale Network for Large System Inventories

    NASA Technical Reports Server (NTRS)

    Shameldin, Ramez Ahmed; Bowling, Shannon R.

    2010-01-01

    The aim of this paper is to use Agent Base Models (ABM) to optimize large scale network handling capabilities for large system inventories and to implement strategies for the purpose of reducing capital expenses. The models used in this paper either use computational algorithms or procedure implementations developed by Matlab to simulate agent based models in a principal programming language and mathematical theory using clusters, these clusters work as a high performance computational performance to run the program in parallel computational. In both cases, a model is defined as compilation of a set of structures and processes assumed to underlie the behavior of a network system.

  12. Large-scale brain networks and psychopathology: a unifying triple network model.

    PubMed

    Menon, Vinod

    2011-10-01

    The science of large-scale brain networks offers a powerful paradigm for investigating cognitive and affective dysfunction in psychiatric and neurological disorders. This review examines recent conceptual and methodological developments which are contributing to a paradigm shift in the study of psychopathology. I summarize methods for characterizing aberrant brain networks and demonstrate how network analysis provides novel insights into dysfunctional brain architecture. Deficits in access, engagement and disengagement of large-scale neurocognitive networks are shown to play a prominent role in several disorders including schizophrenia, depression, anxiety, dementia and autism. Synthesizing recent research, I propose a triple network model of aberrant saliency mapping and cognitive dysfunction in psychopathology, emphasizing the surprising parallels that are beginning to emerge across psychiatric and neurological disorders. PMID:21908230

  13. Think locally, act locally: Detection of small, medium-sized, and large communities in large networks

    NASA Astrophysics Data System (ADS)

    Jeub, Lucas G. S.; Balachandran, Prakash; Porter, Mason A.; Mucha, Peter J.; Mahoney, Michael W.

    2015-01-01

    It is common in the study of networks to investigate intermediate-sized (or "meso-scale") features to try to gain an understanding of network structure and function. For example, numerous algorithms have been developed to try to identify "communities," which are typically construed as sets of nodes with denser connections internally than with the remainder of a network. In this paper, we adopt a complementary perspective that communities are associated with bottlenecks of locally biased dynamical processes that begin at seed sets of nodes, and we employ several different community-identification procedures (using diffusion-based and geodesic-based dynamics) to investigate community quality as a function of community size. Using several empirical and synthetic networks, we identify several distinct scenarios for "size-resolved community structure" that can arise in real (and realistic) networks: (1) the best small groups of nodes can be better than the best large groups (for a given formulation of the idea of a good community); (2) the best small groups can have a quality that is comparable to the best medium-sized and large groups; and (3) the best small groups of nodes can be worse than the best large groups. As we discuss in detail, which of these three cases holds for a given network can make an enormous difference when investigating and making claims about network community structure, and it is important to take this into account to obtain reliable downstream conclusions. Depending on which scenario holds, one may or may not be able to successfully identify "good" communities in a given network (and good communities might not even exist for a given community quality measure), the manner in which different small communities fit together to form meso-scale network structures can be very different, and processes such as viral propagation and information diffusion can exhibit very different dynamics. In addition, our results suggest that, for many large realistic

  14. Do friends share similar body image and eating problems? The role of social networks and peer influences in early adolescence.

    PubMed

    Hutchinson, Delyse M; Rapee, Ronald M

    2007-07-01

    This study examined the role of friendship networks and peer influences in body image concern, dietary restraint, extreme weight loss behaviours (EWLBs) and binge eating in a large community sample of young adolescent females. Based on girls' self-reported friendship groups, social network analysis was used to identify 173 friendship cliques. Results indicated that clique members shared similar scores on measures of dieting, EWLB and binge eating, but not body image concern. Average clique scores for dieting, EWLB and binge eating, were also correlated significantly with clique averages on measures of perceived peer influence, body mass index and psychological variables. Multiple regression analyses indicated that perceived peer influences in weight-related attitudes and behaviours were predictive of individual girls' level of body image concern, dieting, EWLB use and binge eating. Notably, an individual girl's dieting and EWLB use could be predicted from her friends' respective dieting and EWLB scores. Findings highlight the significance of the peer environment in body image and eating problems during early adolescence. PMID:17258173

  15. Hybrid centralized pre-computing/local distributed optimization of shared disjoint-backup path approach to GMPLS optical mesh network intelligent restoration

    NASA Astrophysics Data System (ADS)

    Gong, Qian; Xu, Rong; Lin, Jintong

    2004-04-01

    Wavelength Division Multiplexed (WDM) networks that route optical connections using intelligent optical cross-connects (OXCs) is firmly established as the core constituent of next generation networks. Rapid failure recovery is fundamental to building reliable transport networks. Mesh restoration promises cost effective failure recovery compared with legacy ring networks, and is now seeing large-scale deployment. Many carriers are migrating away from SONET ring restoration for their core transport networks and replacing it with mesh restoration through "intelligent" O-E-O cross-connects (XC). The mesh restoration is typically provided via two fiber-disjoint paths: a service path and a restoration path. this scheme can restore any single link failure or node failure. And by used shared mesh restoration, although every service route is assigned a restoration route, no dedicated capacity needs to be reserved for the restoration route, resulting in capacity savings. The restoration approach we propose is Centralized Pre-computing, Local Distributed Optimization, and Shared Disjoint-backup Path. This approach combines the merits of centralized and distributed solutions. It avoids the scalability issues of centralized solutions by using a distributed control plane for disjoint service path computation and restoration path provisioning. Moreover, if the service routes of two demands are disjoint, no single failure will affect both demands simultaneously. This means that the restoration routes of these two demands can share link capacities, because these two routes will not be activated at the same time. So we can say, this restoration capacity sharing approach achieves low restoration capacity and fast restoration speed, while requiring few control plane changes.

  16. Multiscale analysis of spreading in a large communication network

    NASA Astrophysics Data System (ADS)

    Kivelä, Mikko; Pan, Raj Kumar; Kaski, Kimmo; Kertész, János; Saramäki, Jari; Karsai, Márton

    2012-03-01

    In temporal networks, both the topology of the underlying network and the timings of interaction events can be crucial in determining how a dynamic process mediated by the network unfolds. We have explored the limiting case of the speed of spreading in the SI model, set up such that an event between an infectious and a susceptible individual always transmits the infection. The speed of this process sets an upper bound for the speed of any dynamic process that is mediated through the interaction events of the network. With the help of temporal networks derived from large-scale time-stamped data on mobile phone calls, we extend earlier results that indicate the slowing-down effects of burstiness and temporal inhomogeneities. In such networks, links are not permanently active, but dynamic processes are mediated by recurrent events taking place on the links at specific points in time. We perform a multiscale analysis and pinpoint the importance of the timings of event sequences on individual links, their correlations with neighboring sequences, and the temporal pathways taken by the network-scale spreading process. This is achieved by studying empirically and analytically different characteristic relay times of links, relevant to the respective scales, and a set of temporal reference models that allow for removing selected time-domain correlations one by one. Our analysis shows that for the spreading velocity, time-domain inhomogeneities are as important as the network topology, which indicates the need to take time-domain information into account when studying spreading dynamics. In particular, results for the different characteristic relay times underline the importance of the burstiness of individual links.

  17. An improved unified network protocol framework for large-scale wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Ding, Jin; Sivalingam, Krishna M.

    2004-08-01

    Rapid technological advances in wireless communication have made it possible for networking sensor devices. Given the low computation and battery power capacities of these sensor nodes, the key design factors of network protocols are self-configuring, energy-efficient, adaptive, and scalable. We presented the multi-hop infrastructure network architecture (MINA) for a wireless sensor network consisting of a few hundred sensors that communicate data to a base station (BS). We designed a Unified Network Protocol Framework for MINA that encompasses network organization, medium access control (MAC) and routing protocols. In this paper, we improve it by adaptively varying transmission range to maintain network connectivity. It is a derivative-free optimization algorithm. The BS periodically evaluates the objective function, chooses the appropriate transmission range and broadcasts it to the sensor nodes that then update the transmission range. The advantages are: (i) Avoids the disconnectivity; (ii) Maximizes the number of nodes that can be connected to the BS, (iii) Minimizes the energyxdelay metric and (iv) Avoids the "hot-spot" nodes in the network. The performance in terms of delay, throughput, energy consumption and network lifetimes, is studied in detail using discrete-event simulation compared with other protocol. The results show that it is energy efficient in a large scale network.

  18. The Fermi Large Area Telescope Flare Advocate Program: Rapid Sharing of Results with the Community

    NASA Astrophysics Data System (ADS)

    Thompson, David John; Ciprini, Stefano; Gasparrini, Dario; Fermi Large Area Telescope Collaboration

    2015-01-01

    The Fermi Flare Advocate (also known as Gamma-ray Sky Watcher) program provides a quick look and review of the gamma-ray sky observed daily by the Fermi Large Area Telescope (LAT) through on-duty LAT Flare Advocates and high-level software pipelines like the LAT Automatic Science Processing and the Fermi All-sky Variability Analysis. The FA-GSW service provides rapid alerts and communicates to the external scientific community potentially new gamma-ray sources, interesting transients and flares. News items are regularly posted through the Fermi multiwavelength mailing list, Astronomer's Telegrams and Gamma-ray Coordinates Network notices. A weekly digest containing the highlights about the variable LAT gamma-ray sky at E>100 MeV is published on the web ("Fermi Sky Blog"). From July 2008 to September 2014 more than 290 ATels and 90 GCNs have been published by the Fermi LAT Collaboration. Target of opportunity observing programs with other satellites and telescopes have been triggered by Flare Advocates based on gamma-ray flares from blazars and other kinds of sources.

  19. Shared signaling networks active in B cells isolated from genetically distinct mouse models of lupus

    PubMed Central

    Wu, Tianfu; Qin, Xiangmei; Kurepa, Zoran; Kumar, Kirthi Raman; Liu, Kui; Kanta, Hasna; Zhou, Xin J.; Satterthwaite, Anne B.; Davis, Laurie S.; Mohan, Chandra

    2007-01-01

    Though B cells play key roles in lupus pathogenesis, the molecular circuitry and its dysregulation in these cells as disease evolves remain poorly understood. To address this, a comprehensive scan of multiple signaling axes using multiplexed Western blotting was undertaken in several different murine lupus strains. PI3K/AKT/mTOR (mTOR, mammalian target of rapamycin), MEK1/Erk1/2, p38, NF-κB, multiple Bcl-2 family members, and cell-cycle molecules were observed to be hyperexpressed in lupus B cells in an age-dependent and lupus susceptibility gene–dose–dependent manner. Therapeutic targeting of the AKT/mTOR axis using a rapamycin (sirolimus) derivative ameliorated the serological, cellular, and pathological phenotypes associated with lupus. Surprisingly, the targeting of this axis was associated with the crippling of several other signaling axes. These studies reveal that lupus pathogenesis is contingent upon the activation of an elaborate network of signaling cascades that is shared among genetically distinct mouse models and raise hope that targeting pivotal nodes in these networks may offer therapeutic benefit. PMID:17641780

  20. Mycorrhizal Networks: Common Goods of Plants Shared under Unequal Terms of Trade1[W][OA

    PubMed Central

    Walder, Florian; Niemann, Helge; Natarajan, Mathimaran; Lehmann, Moritz F.; Boller, Thomas; Wiemken, Andres

    2012-01-01

    Plants commonly live in a symbiotic association with arbuscular mycorrhizal fungi (AMF). They invest photosynthetic products to feed their fungal partners, which, in return, provide mineral nutrients foraged in the soil by their intricate hyphal networks. Intriguingly, AMF can link neighboring plants, forming common mycorrhizal networks (CMNs). What are the terms of trade in such CMNs between plants and their shared fungal partners? To address this question, we set up microcosms containing a pair of test plants, interlinked by a CMN of Glomus intraradices or Glomus mosseae. The plants were flax (Linum usitatissimum; a C3 plant) and sorghum (Sorghum bicolor; a C4 plant), which display distinctly different 13C/12C isotope compositions. This allowed us to differentially assess the carbon investment of the two plants into the CMN through stable isotope tracing. In parallel, we determined the plants’ “return of investment” (i.e. the acquisition of nutrients via CMN) using 15N and 33P as tracers. Depending on the AMF species, we found a strong asymmetry in the terms of trade: flax invested little carbon but gained up to 94% of the nitrogen and phosphorus provided by the CMN, which highly facilitated growth, whereas the neighboring sorghum invested massive amounts of carbon with little return but was barely affected in growth. Overall biomass production in the mixed culture surpassed the mean of the two monocultures. Thus, CMNs may contribute to interplant facilitation and the productivity boosts often found with intercropping compared with conventional monocropping. PMID:22517410

  1. Tunable self-seeding Fabry-Pérot laser diode for upstream multiwavelength shared ethernet passive optical network

    NASA Astrophysics Data System (ADS)

    Zhu, Min; Xiao, Shilin; Zhou, Zhao; Bi, Meihua

    2011-03-01

    We present a novel upstream multiwavelength shared ethernet passive optical network architecture, based on a proposed self-seeding Fabry-Pérot laser diode (FP-LD) at the optical network unit. The performances of the wavelength and power stability, side-mode suppression ratio, and tuning range for the proposed tunable self-seeding laser module are experimentally investigated. The bit-error-rate measurement is performed with direct modulation on FP-LD of 1.25 Gbps upstream data. The performance benefits from the upstream wavelengths sharing are showed via simulations.

  2. Complex modular structure of large-scale brain networks

    NASA Astrophysics Data System (ADS)

    Valencia, M.; Pastor, M. A.; Fernández-Seara, M. A.; Artieda, J.; Martinerie, J.; Chavez, M.

    2009-06-01

    Modular structure is ubiquitous among real-world networks from related proteins to social groups. Here we analyze the modular organization of brain networks at a large scale (voxel level) extracted from functional magnetic resonance imaging signals. By using a random-walk-based method, we unveil the modularity of brain webs and show modules with a spatial distribution that matches anatomical structures with functional significance. The functional role of each node in the network is studied by analyzing its patterns of inter- and intramodular connections. Results suggest that the modular architecture constitutes the structural basis for the coexistence of functional integration of distant and specialized brain areas during normal brain activities at rest.

  3. Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

    NASA Technical Reports Server (NTRS)

    Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

    2013-01-01

    A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of

  4. Graph animals, subgraph sampling, and motif search in large networks

    NASA Astrophysics Data System (ADS)

    Baskerville, Kim; Grassberger, Peter; Paczuski, Maya

    2007-09-01

    We generalize a sampling algorithm for lattice animals (connected clusters on a regular lattice) to a Monte Carlo algorithm for “graph animals,” i.e., connected subgraphs in arbitrary networks. As with the algorithm in [N. Kashtan , Bioinformatics 20, 1746 (2004)], it provides a weighted sample, but the computation of the weights is much faster (linear in the size of subgraphs, instead of superexponential). This allows subgraphs with up to ten or more nodes to be sampled with very high statistics, from arbitrarily large networks. Using this together with a heuristic algorithm for rapidly classifying isomorphic graphs, we present results for two protein interaction networks obtained using the tandem affinity purification (TAP) method: one of Escherichia coli with 230 nodes and 695 links, and one for yeast (Saccharomyces cerevisiae) with roughly ten times more nodes and links. We find in both cases that most connected subgraphs are strong motifs ( Z scores >10 ) or antimotifs ( Z scores <-10 ) when the null model is the ensemble of networks with fixed degree sequence. Strong differences appear between the two networks, with dominant motifs in E. coli being (nearly) bipartite graphs and having many pairs of nodes that connect to the same neighbors, while dominant motifs in yeast tend towards completeness or contain large cliques. We also explore a number of methods that do not rely on measurements of Z scores or comparisons with null models. For instance, we discuss the influence of specific complexes like the 26S proteasome in yeast, where a small number of complexes dominate the k cores with large k and have a decisive effect on the strongest motifs with 6-8 nodes. We also present Zipf plots of counts versus rank. They show broad distributions that are not power laws, in contrast to the case when disconnected subgraphs are included.

  5. Large optical 3D MEMS switches in access networks

    NASA Astrophysics Data System (ADS)

    Madamopoulos, Nicholas; Kaman, Volkan; Yuan, Shifu; Jerphagnon, Olivier; Helkey, Roger; Bowers, John E.

    2007-09-01

    Interest is high among residential customers and businesses for advanced, broadband services such as fast Internet access, electronic commerce, video-on-demand, digital broadcasting, teleconferencing and telemedicine. In order to satisfy such growing demand of end-customers, access technologies such as fiber-to-the-home/building (FTTH/B) are increasingly being deployed. Carriers can reduce maintenance costs, minimize technology obsolescence and introduce new services easily by reducing active elements in the fiber access network. However, having a passive optical network (PON) also introduces operational and maintenance challenges. Increased diagnostic monitoring capability of the network becomes a necessity as more and more fibers are provisioned to deliver services to the end-customers. This paper demonstrates the clear advantages that large 3D optical MEMS switches offer in solving these access network problems. The advantages in preventative maintenance, remote monitoring, test and diagnostic capability are highlighted. The low optical insertion loss for all switch optical connections of the switch enables the monitoring, grooming and serving of a large number of PON lines and customers. Furthermore, the 3D MEMS switch is transparent to optical wavelengths and data formats, thus making it easy to incorporate future upgrades, such higher bit rates or DWDM overlay to a PON.

  6. Network for the recognition of a large spoken vocabulary

    SciTech Connect

    De Mori, R.; Mong, Y.; Palakal, M.

    1983-01-01

    A new solution for accessing a large lexicon in continuous speech is proposed. The words of a lexicon and their relations with syllables, acoustic and prosodic cues are represented by a network similar to semantic networks used in artificial intelligence for knowledge representation. The network for lexical representation is generated by a graph grammar in which rules are applied either when suitable acoustic cues are detected in the signal or when model driven predictions are made. The piece of network generated by the application of a set of rules contains nodes and links. Nodes are processes capable of executing algorithms. Links are channels through which messages between processes can be exchanged. The type of a link specifies the type of message that can be exchanged. The model exhibits a high degree of parallelism and allows to efficiently perform intersections of large sets of descriptions. Some nodes correspond to word classes which are hypothesized when some sets of sufficient conditions are detected in the data. These conditions are hypotheses about robust features called primary phonetic features. 11 references.

  7. Large-scale network-level processes during entrainment.

    PubMed

    Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan

    2016-03-15

    Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4-30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band "disconnecting" visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557

  8. Large-scale network-level processes during entrainment

    PubMed Central

    Lithari, Chrysa; Sánchez-García, Carolina; Ruhnau, Philipp; Weisz, Nathan

    2016-01-01

    Visual rhythmic stimulation evokes a robust power increase exactly at the stimulation frequency, the so-called steady-state response (SSR). Localization of visual SSRs normally shows a very focal modulation of power in visual cortex and led to the treatment and interpretation of SSRs as a local phenomenon. Given the brain network dynamics, we hypothesized that SSRs have additional large-scale effects on the brain functional network that can be revealed by means of graph theory. We used rhythmic visual stimulation at a range of frequencies (4–30 Hz), recorded MEG and investigated source level connectivity across the whole brain. Using graph theoretical measures we observed a frequency-unspecific reduction of global density in the alpha band “disconnecting” visual cortex from the rest of the network. Also, a frequency-specific increase of connectivity between occipital cortex and precuneus was found at the stimulation frequency that exhibited the highest resonance (30 Hz). In conclusion, we showed that SSRs dynamically re-organized the brain functional network. These large-scale effects should be taken into account not only when attempting to explain the nature of SSRs, but also when used in various experimental designs. PMID:26835557

  9. Locating inefficient links in a large-scale transportation network

    NASA Astrophysics Data System (ADS)

    Sun, Li; Liu, Like; Xu, Zhongzhi; Jie, Yang; Wei, Dong; Wang, Pu

    2015-02-01

    Based on data from geographical information system (GIS) and daily commuting origin destination (OD) matrices, we estimated the distribution of traffic flow in the San Francisco road network and studied Braess's paradox in a large-scale transportation network with realistic travel demand. We measured the variation of total travel time Δ T when a road segment is closed, and found that | Δ T | follows a power-law distribution if Δ T < 0 or Δ T > 0. This implies that most roads have a negligible effect on the efficiency of the road network, while the failure of a few crucial links would result in severe travel delays, and closure of a few inefficient links would counter-intuitively reduce travel costs considerably. Generating three theoretical networks, we discovered that the heterogeneously distributed travel demand may be the origin of the observed power-law distributions of | Δ T | . Finally, a genetic algorithm was used to pinpoint inefficient link clusters in the road network. We found that closing specific road clusters would further improve the transportation efficiency.

  10. Implementation of Cyberinfrastructure and Data Management Workflow for a Large-Scale Sensor Network

    NASA Astrophysics Data System (ADS)

    Jones, A. S.; Horsburgh, J. S.

    2014-12-01

    Monitoring with in situ environmental sensors and other forms of field-based observation presents many challenges for data management, particularly for large-scale networks consisting of multiple sites, sensors, and personnel. The availability and utility of these data in addressing scientific questions relies on effective cyberinfrastructure that facilitates transformation of raw sensor data into functional data products. It also depends on the ability of researchers to share and access the data in useable formats. In addition to addressing the challenges presented by the quantity of data, monitoring networks need practices to ensure high data quality, including procedures and tools for post processing. Data quality is further enhanced if practitioners are able to track equipment, deployments, calibrations, and other events related to site maintenance and associate these details with observational data. In this presentation we will describe the overall workflow that we have developed for research groups and sites conducting long term monitoring using in situ sensors. Features of the workflow include: software tools to automate the transfer of data from field sites to databases, a Python-based program for data quality control post-processing, a web-based application for online discovery and visualization of data, and a data model and web interface for managing physical infrastructure. By automating the data management workflow, the time from collection to analysis is reduced and sharing and publication is facilitated. The incorporation of metadata standards and descriptions and the use of open-source tools enhances the sustainability and reusability of the data. We will describe the workflow and tools that we have developed in the context of the iUTAH (innovative Urban Transitions and Aridregion Hydrosustainability) monitoring network. The iUTAH network consists of aquatic and climate sensors deployed in three watersheds to monitor Gradients Along Mountain to Urban

  11. Gene-Sharing Networks Reveal Organizing Principles of Transcriptomes in Arabidopsis and Other Multicellular Organisms[W

    PubMed Central

    Li, Song; Pandey, Sona; Gookin, Timothy E.; Zhao, Zhixin; Wilson, Liza; Assmann, Sarah M.

    2012-01-01

    Understanding tissue-related gene expression patterns can provide important insights into gene, tissue, and organ function. Transcriptome analyses often have focused on housekeeping or tissue-specific genes or on gene coexpression. However, by analyzing thousands of single-gene expression distributions in multiple tissues of Arabidopsis thaliana, rice (Oryza sativa), human (Homo sapiens), and mouse (Mus musculus), we found that these organisms primarily operate by gene sharing, a phenomenon where, in each organism, most genes exhibit a high expression level in a few key tissues. We designed an analytical pipeline to characterize this phenomenon and then derived Arabidopsis and human gene-sharing networks, in which tissues are connected solely based on the extent of shared preferentially expressed genes. The results show that tissues or cell types from the same organ system tend to group together to form network modules. Tissues that are in consecutive developmental stages or have common physiological functions are connected in these networks, revealing the importance of shared preferentially expressed genes in conferring specialized functions of each tissue type. The networks provide predictive power for each tissue type regarding gene functions of both known and heretofore unknown genes, as shown by the identification of four new genes with functions in guard cell and abscisic acid response. We provide a Web interface that enables, based on the extent of gene sharing, both prediction of tissue-related functions for any Arabidopsis gene of interest and predictions concerning the relatedness of tissues. Common gene-sharing patterns observed in the four model organisms suggest that gene sharing evolved as a fundamental organizing principle of gene expression in diverse multicellular eukaryotes. PMID:22517316

  12. Supporting large scale applications on networks of workstations

    NASA Technical Reports Server (NTRS)

    Cooper, Robert; Birman, Kenneth P.

    1989-01-01

    Distributed applications on networks of workstations are an increasingly common way to satisfy computing needs. However, existing mechanisms for distributed programming exhibit poor performance and reliability as application size increases. Extension of the ISIS distributed programming system to support large scale distributed applications by providing hierarchical process groups is discussed. Incorporation of hierarchy in the program structure and exploitation of this to limit the communication and storage required in any one component of the distributed system is examined.

  13. Investigating the evolution of Shared Socioeconomic Pathways with a large number of scenarios

    NASA Astrophysics Data System (ADS)

    Schweizer, V. J.; Guivarch, C.; Rozenberg, J.

    2013-12-01

    The new scenario framework for climate change research includes alternative possible trends for socioeconomic development called Shared Socioeconomic Pathways (SSPs). The SSPs bear some similarities to other scenarios used for global change research, but they also have important differences. Like the IPCC Special Report on Emissions Scenarios or the Millennium Ecosystem Assessment, SSPs are defined by a scenario logic consisting of two axes. However, these axes define SSPs with respect to their location in an outcome space for challenges to mitigation and to adaptation rather than by their drivers. Open questions for the SSPs include what their drivers are and how the time dimension could be interpreted with the outcomes space. We present a new analytical approach for addressing both questions by studying large numbers of scenarios produced by an integrated assessment model, IMACLIM-R. We systematically generated 432 scenarios and used the SSP framework to classify them by typology. We then analyzed them dynamically, tracing their evolution through the SSP challenges space at annual time steps over the period 2010-2090. Through this approach, we found that many scenarios do not remain fixed to a particular SSP domain; they drift from one domain to another. In papers describing the framework for new scenarios, SSPs are envisioned as hypothetical (counter-factual) reference scenarios that remain fixed in one domain over some time period of interest. However, we conclude that it may be important to also research scenarios that shift across SSP domains. This is relevant for another open question, which is what scenarios are important to explore given their consequences. Through a data mining technique, we uncovered prominent drivers for scenarios that shift across SSP domains. Scenarios with different challenges for adaptation and mitigation (that is, mitigation and adaptation challenges that are not co-varying) were found to be the least stable, and the following

  14. Lightning Paths in Sky Share Similarities with Channel Networks on Earth

    NASA Astrophysics Data System (ADS)

    Jain, Sharad K.; Singh, Vijay P.

    2004-06-01

    Lightning in the atmosphere is a transient, high current carrying electric discharge. It occurs when some region of the atmosphere reaches an electric charge sufficiently large so that the electric fields associated with the charge cause an electrical breakdown in the air. Lightning is produced in the cumulonimbus clouds; however, it can also occur in snowstorms and sandstorms. The analysis presented in this article demonstrates that there are many similarities between the celestial networks that are formed during a lighting event and the terrestrial channel networks associated with flowing surface waters in drainage basins. It begins with a preliminary analysis of the paths followed by the cloud-to-ground discharge of electric currents generated in the atmosphere during thunderstorms.

  15. Resonant RF network antennas for large-area and large-volume inductively coupled plasma sources

    NASA Astrophysics Data System (ADS)

    Hollenstein, Ch; Guittienne, Ph; Howling, A. A.

    2013-10-01

    Large-area and large-volume radio frequency (RF) plasmas are produced by different arrangements of an elementary electrical mesh consisting of two conductors interconnected by a capacitor at each end. The obtained cylindrical and planar RF networks are resonant and generate very high RF currents. The input impedance of such RF networks shows the behaviour of an RLC parallel resonance equivalent circuit. The real impedance at the resonance frequency is of great advantage for power matching compared with conventional inductive devices. Changes in the RLC equivalent circuit during the observed E-H transition will allow future interpretation of the plasma-antenna coupling. Furthermore, high power transfer efficiencies are found during inductively coupled plasma (ICP) operation. For the planar RF antenna network it is shown that the E-H transition occurs simultaneously over the entire antenna. The underlying physics of these discharges induced by the resonant RF network antenna is found to be identical to that of the conventional ICP devices described in the literature. The resonant RF network antenna is a new versatile plasma source, which can be adapted to applications in industry and research.

  16. Cellular computational networks--a scalable architecture for learning the dynamics of large networked systems.

    PubMed

    Luitel, Bipul; Venayagamoorthy, Ganesh Kumar

    2014-02-01

    Neural networks for implementing large networked systems such as smart electric power grids consist of multiple inputs and outputs. Many outputs lead to a greater number of parameters to be adapted. Each additional variable increases the dimensionality of the problem and hence learning becomes a challenge. Cellular computational networks (CCNs) are a class of sparsely connected dynamic recurrent networks (DRNs). By proper selection of a set of input elements for each output variable in a given application, a DRN can be modified into a CCN which significantly reduces the complexity of the neural network and allows use of simple training methods for independent learning in each cell thus making it scalable. This article demonstrates this concept of developing a CCN using dimensionality reduction in a DRN for scalability and better performance. The concept has been analytically explained and empirically verified through application. PMID:24300549

  17. Geometric origin of scaling in large traffic networks.

    PubMed

    Popović, Marko; Štefančić, Hrvoje; Zlatić, Vinko

    2012-11-16

    Large scale traffic networks are an indispensable part of contemporary human mobility and international trade. Networks of airport travel and cargo ship movements are invaluable for the understanding of human mobility patterns [R. Guimera et al., Proc. Natl. Acad. Sci. U.S.A. 102, 7794 (2005))], epidemic spreading [V. Colizza et al., Proc. Natl. Acad. Sci. U.S.A. 103, 2015 (2006)], global trade [International Maritime Organization, http://www.imo.org/], and spread of invasive species [G. M. Ruiz et al., Nature (London) 408, 49 (2000)]. Different studies [M. Barthelemy, Phys. Rept. 499, 1 (2011)] point to the universal character of some of the exponents measured in such networks. Here we show that exponents which relate (i) the strength of nodes to their degree and (ii) weights of links to degrees of nodes that they connect have a geometric origin. We present a simple robust model which exhibits the observed power laws and relates exponents to the dimensionality of 2D space in which traffic networks are embedded. We show that the relation between weight strength and degree is s(k)~k(3/2), the relation between distance strength and degree is s(d)(k)~k(3/2), and the relation between weight of link and degrees of linked nodes is w(ij)~(k(i)k(j))(1/2) on the plane 2D surface. We further analyze the influence of spherical geometry, relevant for the whole planet, on exact values of these exponents. Our model predicts that these exponents should be found in future studies of port networks and it imposes constraints on more refined models of port networks. PMID:23215527

  18. Identifying Large-Scale Brain Networks in Fragile X Syndrome

    PubMed Central

    Hall, Scott S.; Jiang, Heidi; Reiss, Allan L.; Greicius, Michael D.

    2014-01-01

    IMPORTANCE Fragile X syndrome (FXS) is an X-linked neurogenetic disorder characterized by a cognitive and behavioral phenotype resembling features of autism spectrum disorder. Until now, research has focused largely on identifying regional differences in brain structure and function between individuals with FXS and various control groups. Very little is known about the large-scale brain networks that may underlie the cognitive and behavioral symptoms of FXS. OBJECTIVE To identify large-scale, resting-state networks in FXS that differ from control individuals matched on age, IQ, and severity of behavioral and cognitive symptoms. DESIGN, SETTING, AND PARTICIPANTS Cross-sectional, in vivo neuroimaging study conducted in an academic medical center. Participants (aged 10–23 years) included 17 males and females with FXS and 16 males and females serving as controls. MAIN OUTCOMES AND MEASURES Univariate voxel-based morphometric analyses, fractional amplitude of low-frequency fluctuations (fALFF) analysis, and group-independent component analysis with dual regression. RESULTS Patients with FXS showed decreased functional connectivity in the salience, precuneus, left executive control, language, and visuospatial networks compared with controls. Decreased fALFF in the bilateral insular, precuneus, and anterior cingulate cortices also was found in patients with FXS compared with control participants. Furthermore, fALFF in the left insular cortex was significantly positively correlated with IQ in patients with FXS. Decreased gray matter density, resting-state connectivity, and fALFF converged in the left insular cortex in patients with FXS. CONCLUSIONS AND RELEVANCE Fragile X syndrome results in widespread reductions in functional connectivity across multiple cognitive and affective brain networks. Converging structural and functional abnormalities in the left insular cortex, a region also implicated in individuals diagnosed with autism spectrum disorder, suggests that

  19. High Fidelity Simulations of Large-Scale Wireless Networks

    SciTech Connect

    Onunkwo, Uzoma; Benz, Zachary

    2015-11-01

    The worldwide proliferation of wireless connected devices continues to accelerate. There are 10s of billions of wireless links across the planet with an additional explosion of new wireless usage anticipated as the Internet of Things develops. Wireless technologies do not only provide convenience for mobile applications, but are also extremely cost-effective to deploy. Thus, this trend towards wireless connectivity will only continue and Sandia must develop the necessary simulation technology to proactively analyze the associated emerging vulnerabilities. Wireless networks are marked by mobility and proximity-based connectivity. The de facto standard for exploratory studies of wireless networks is discrete event simulations (DES). However, the simulation of large-scale wireless networks is extremely difficult due to prohibitively large turnaround time. A path forward is to expedite simulations with parallel discrete event simulation (PDES) techniques. The mobility and distance-based connectivity associated with wireless simulations, however, typically doom PDES and fail to scale (e.g., OPNET and ns-3 simulators). We propose a PDES-based tool aimed at reducing the communication overhead between processors. The proposed solution will use light-weight processes to dynamically distribute computation workload while mitigating communication overhead associated with synchronizations. This work is vital to the analytics and validation capabilities of simulation and emulation at Sandia. We have years of experience in Sandia’s simulation and emulation projects (e.g., MINIMEGA and FIREWHEEL). Sandia’s current highly-regarded capabilities in large-scale emulations have focused on wired networks, where two assumptions prevent scalable wireless studies: (a) the connections between objects are mostly static and (b) the nodes have fixed locations.

  20. 76 FR 63811 - Structural Reforms To Improve the Security of Classified Networks and the Responsible Sharing and...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-10-13

    ... agents, or any other person. (Presidential Sig.) THE WHITE HOUSE, October 7, 2011. [FR Doc. 2011-26729... (classified information) on computer networks, it is hereby ordered as follows: Section 1. Policy. Our Nation... world but also requires sophisticated and vigilant means to ensure it is shared securely....

  1. Prekindergarten Teachers' Verbal References to Print during Classroom-Based, Large-Group Shared Reading

    ERIC Educational Resources Information Center

    Zucker, Tricia A.; Justice, Laura M.; Piasta, Shayne B.

    2009-01-01

    Purpose: The frequency with which adults reference print when reading with preschool-age children is associated with growth in children's print knowledge (e.g., L.M. Justice & H.K. Ezell, 2000, 2002). This study examined whether prekindergarten (pre-K) teachers naturally reference print during classroom shared reading and if verbal print…

  2. Share with thy neighbors

    NASA Astrophysics Data System (ADS)

    Chandra, Surendar; Yu, Xuwen

    2007-01-01

    Peer to peer (P2P) systems are traditionally designed to scale to a large number of nodes. However, we focus on scenarios where the sharing is effected only among neighbors. Localized sharing is particularly attractive in scenarios where wide area network connectivity is undesirable, expensive or unavailable. On the other hand, local neighbors may not offer the wide variety of objects possible in a much larger system. The goal of this paper is to investigate a P2P system that shares contents with its neighbors. We analyze the sharing behavior of Apple iTunes users in an University setting. iTunes restricts the sharing of audio and video objects to peers within the same LAN sub-network. We show that users are already making a significant amount of content available for local sharing. We show that these systems are not appropriate for applications that require access to a specific object. We argue that mechanisms that allow the user to specify classes of interesting objects are better suited for these systems. Mechanisms such as bloom filters can allow each peer to summarize the contents available in the neighborhood, reducing network search overhead. This research can form the basis for future storage systems that utilize the shared storage available in neighbors and build a probabilistic storage for local consumption.

  3. Network Lasso: Clustering and Optimization in Large Graphs

    PubMed Central

    Hallac, David; Leskovec, Jure; Boyd, Stephen

    2016-01-01

    Convex optimization is an essential tool for modern data analysis, as it provides a framework to formulate and solve many problems in machine learning and data mining. However, general convex optimization solvers do not scale well, and scalable solvers are often specialized to only work on a narrow class of problems. Therefore, there is a need for simple, scalable algorithms that can solve many common optimization problems. In this paper, we introduce the network lasso, a generalization of the group lasso to a network setting that allows for simultaneous clustering and optimization on graphs. We develop an algorithm based on the Alternating Direction Method of Multipliers (ADMM) to solve this problem in a distributed and scalable manner, which allows for guaranteed global convergence even on large graphs. We also examine a non-convex extension of this approach. We then demonstrate that many types of problems can be expressed in our framework. We focus on three in particular — binary classification, predicting housing prices, and event detection in time series data — comparing the network lasso to baseline approaches and showing that it is both a fast and accurate method of solving large optimization problems. PMID:27398260

  4. High Speed Networking and Large-scale Simulation in Geodynamics

    NASA Technical Reports Server (NTRS)

    Kuang, Weijia; Gary, Patrick; Seablom, Michael; Truszkowski, Walt; Odubiyi, Jide; Jiang, Weiyuan; Liu, Dong

    2004-01-01

    Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.

  5. The Shared Health Research Information Network (SHRINE): a prototype federated query tool for clinical data repositories.

    PubMed

    Weber, Griffin M; Murphy, Shawn N; McMurry, Andrew J; Macfadden, Douglas; Nigrin, Daniel J; Churchill, Susanne; Kohane, Isaac S

    2009-01-01

    The authors developed a prototype Shared Health Research Information Network (SHRINE) to identify the technical, regulatory, and political challenges of creating a federated query tool for clinical data repositories. Separate Institutional Review Boards (IRBs) at Harvard's three largest affiliated health centers approved use of their data, and the Harvard Medical School IRB approved building a Query Aggregator Interface that can simultaneously send queries to each hospital and display aggregate counts of the number of matching patients. Our experience creating three local repositories using the open source Informatics for Integrating Biology and the Bedside (i2b2) platform can be used as a road map for other institutions. The authors are actively working with the IRBs and regulatory groups to develop procedures that will ultimately allow investigators to obtain identified patient data and biomaterials through SHRINE. This will guide us in creating a future technical architecture that is scalable to a national level, compliant with ethical guidelines, and protective of the interests of the participating hospitals. PMID:19567788

  6. Comparative Study of Multicast Protection Algorithms Using Shared Links in 100GET Transport Network

    NASA Astrophysics Data System (ADS)

    Sulaiman, Samer; Haidine, Abdelfattah; Lehnert, Ralf; Tuerk, Stefan

    In recent years new challenges have emerged in the telecommunications market resulting from the increase of network traffic and strong competition. Because of that, service providers feel constrained to replace expensive and complex IP-routers with a cheap and simple solution which guarantees the requested quality of services (QoS) with low cost. One of these solutions is to use the Ethernet technology as a switching layer, which results in using the cheap Ethernet services (E-Line, E-LAN and E-Tree) and to replace the expensive IP-routers. To achieve this migration step, new algorithms that support the available as well as the future services have to be developed. In this paper, we investigate the multicast protection issue. Three multicast protection algorithms based on the shared capacity between primary and backup solutions are proposed and evaluated. The blocking probability is used to evaluate the performance of the proposed algorithms. The sub-path algorithm resulted in a low blocking probability compared with the other algorithms.

  7. An efficient bandwidth sharing strategy through users' cooperation for multirate networks

    NASA Astrophysics Data System (ADS)

    El-Ganainy, Noha O.; El-Khamy, Said E.

    2013-09-01

    This paper adopts an efficient strategy that allocates the network resources to the users according to the transmission rate requirement. Based on cooperation and the use of variable length spreading codes, the terminals requiring high transmission rate are supported by larger bandwidth and power in order to enhance their quality of service. The proposed resource allocation strategy assigns the terminals with low transmission rate to cooperate with those with high transmission rate by dedicating a part of their bandwidth and power to either relay their data or send a part of it. This will result in a slight limitation on the performance of the cooperating terminals (low rate). Two proposed schemes are presented namely the relaying strategy and re-allocation strategy. These strategies are evaluated against the commonly used rate-matching algorithm which constrains the terminals to fairly share the bandwidth regardless of the transmission rate. The proposed receiver is simple and efficient and the utilized spreading codes provide signal separation and limit multiple access interference MAI. In a CDMA-based framework supporting multirate transmissions, a thorough performance assessment in terms of the error probability and the probability of outage is discussed for the considered strategies under different transmission conditions. The proposed strategies enhance the performance of the high rate user compared to the rate-matching algorithm and slightly hold back the low rate user performance. Moreover, the re-allocation strategy enhances the system capability to support higher transmission rate at no additional cost.

  8. Atypical Behavior Identification in Large Scale Network Traffic

    SciTech Connect

    Best, Daniel M.; Hafen, Ryan P.; Olsen, Bryan K.; Pike, William A.

    2011-10-23

    Cyber analysts are faced with the daunting challenge of identifying exploits and threats within potentially billions of daily records of network traffic. Enterprise-wide cyber traffic involves hundreds of millions of distinct IP addresses and results in data sets ranging from terabytes to petabytes of raw data. Creating behavioral models and identifying trends based on those models requires data intensive architectures and techniques that can scale as data volume increases. Analysts need scalable visualization methods that foster interactive exploration of data and enable identification of behavioral anomalies. Developers must carefully consider application design, storage, processing, and display to provide usability and interactivity with large-scale data. We present an application that highlights atypical behavior in enterprise network flow records. This is accomplished by utilizing data intensive architectures to store the data, aggregation techniques to optimize data access, statistical techniques to characterize behavior, and a visual analytic environment to render the behavioral trends, highlight atypical activity, and allow for exploration.

  9. IR wireless cluster synapses of HYDRA very large neural networks

    NASA Astrophysics Data System (ADS)

    Jannson, Tomasz; Forrester, Thomas

    2008-04-01

    RF/IR wireless (virtual) synapses are critical components of HYDRA (Hyper-Distributed Robotic Autonomy) neural networks, already discussed in two earlier papers. The HYDRA network has the potential to be very large, up to 10 11-neurons and 10 18-synapses, based on already established technologies (cellular RF telephony and IR-wireless LANs). It is organized into almost fully connected IR-wireless clusters. The HYDRA neurons and synapses are very flexible, simple, and low-cost. They can be modified into a broad variety of biologically-inspired brain-like computing capabilities. In this third paper, we focus on neural hardware in general, and on IR-wireless synapses in particular. Such synapses, based on LED/LD-connections, dominate the HYDRA neural cluster.

  10. Measuring Large-Scale Social Networks with High Resolution

    PubMed Central

    Stopczynski, Arkadiusz; Sekara, Vedran; Sapiezynski, Piotr; Cuttone, Andrea; Madsen, Mette My; Larsen, Jakob Eg; Lehmann, Sune

    2014-01-01

    This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years—the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection. PMID:24770359

  11. A system for simulating shared memory in heterogeneous distributed-memory networks with specialization for robotics applications

    SciTech Connect

    Jones, J.P.; Bangs, A.L.; Butler, P.L.

    1991-01-01

    Hetero Helix is a programming environment which simulates shared memory on a heterogeneous network of distributed-memory computers. The machines in the network may vary with respect to their native operating systems and internal representation of numbers. Hetero Helix presents a simple programming model to developers, and also considers the needs of designers, system integrators, and maintainers. The key software technology underlying Hetero Helix is the use of a compiler'' which analyzes the data structures in shared memory and automatically generates code which translates data representations from the format native to each machine into a common format, and vice versa. The design of Hetero Helix was motivated in particular by the requirements of robotics applications. Hetero Helix has been used successfully in an integration effort involving 27 CPUs in a heterogeneous network and a body of software totaling roughly 100,00 lines of code. 25 refs., 6 figs.

  12. Foundational perspectives on causality in large-scale brain networks.

    PubMed

    Mannino, Michael; Bressler, Steven L

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  13. Foundational perspectives on causality in large-scale brain networks

    NASA Astrophysics Data System (ADS)

    Mannino, Michael; Bressler, Steven L.

    2015-12-01

    A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical

  14. Dynamical modeling and analysis of large cellular regulatory networks

    NASA Astrophysics Data System (ADS)

    Bérenguier, D.; Chaouiya, C.; Monteiro, P. T.; Naldi, A.; Remy, E.; Thieffry, D.; Tichit, L.

    2013-06-01

    The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

  15. Predicting protein functions from redundancies in large-scale protein interaction networks

    NASA Technical Reports Server (NTRS)

    Samanta, Manoj Pratim; Liang, Shoudan

    2003-01-01

    Interpreting data from large-scale protein interaction experiments has been a challenging task because of the widespread presence of random false positives. Here, we present a network-based statistical algorithm that overcomes this difficulty and allows us to derive functions of unannotated proteins from large-scale interaction data. Our algorithm uses the insight that if two proteins share significantly larger number of common interaction partners than random, they have close functional associations. Analysis of publicly available data from Saccharomyces cerevisiae reveals >2,800 reliable functional associations, 29% of which involve at least one unannotated protein. By further analyzing these associations, we derive tentative functions for 81 unannotated proteins with high certainty. Our method is not overly sensitive to the false positives present in the data. Even after adding 50% randomly generated interactions to the measured data set, we are able to recover almost all (approximately 89%) of the original associations.

  16. Non-immunologic predictors of chronic renal allograft failure: data from the United Network of Organ Sharing.

    PubMed

    Chertow, G M; Brenner, B M; Mackenzie, H S; Milford, E L

    1995-12-01

    Experimental evidence and clinical experience suggest that non-immunologic factors are important predictors of long-term renal allograft survival. It has been suggested that chronic allograft failure may in some cases by mediated by non-immunologic factors implicated in the pathobiology of other forms of progressive renal disease. Donor age, sex, and race may influence the "dose" of nephrons delivered in cadaveric renal transplantation. The United Network of Organ Sharing 1994 Public Use Data Tape was used to evaluate these and other risk factors in more than 31,000 recipients of cadaver allografts followed between 1987 and 1992. Female sex and African American race of the donor were important predictors of allograft failure. There was a markedly increased risk of allograft failure at both extremes of donor age. Recipients of large body size had accelerated graft loss. Stratified analyses suggested an interaction between donor and recipient race; nevertheless, all non-immunologic factors examined expressed independent associations with allograft survival. In sum, antigen-independent factors appear to be important determinants of allograft performance. Additional multivariable analyses are required to assess the relative importance of these factors compared with other known immunologic factors, such as HLA antigen mismatch. These findings may have important biomedical and health care policy implications. PMID:8587283

  17. A sendmail. cf scheme for a large network

    SciTech Connect

    Darmohray, T.M.

    1991-08-14

    Like most large networked sites our users depend heavily on the electronic mail system for both internal and off-site communications. Unfortunately the sendmail.cf file, which is used to control the behavior of the sendmail program, is somewhat cryptic and difficult to decipher for the neophyte. So, on one hand you have a highly visible, frequently used utility, and on the other hand a not-so-easily acquired system administration forte. Here is the sendmail topology of our site, what premises we based it on, and the parts of the sendmail.cf files which support the topology.

  18. The application of artificial intelligence techniques to large distributed networks

    NASA Technical Reports Server (NTRS)

    Dubyah, R.; Smith, T. R.; Star, J. L.

    1985-01-01

    Data accessibility and transfer of information, including the land resources information system pilot, are structured as large computer information networks. These pilot efforts include the reduction of the difficulty to find and use data, reducing processing costs, and minimize incompatibility between data sources. Artificial Intelligence (AI) techniques were suggested to achieve these goals. The applicability of certain AI techniques are explored in the context of distributed problem solving systems and the pilot land data system (PLDS). The topics discussed include: PLDS and its data processing requirements, expert systems and PLDS, distributed problem solving systems, AI problem solving paradigms, query processing, and distributed data bases.

  19. Deep Convolutional Neural Networks for large-scale speech tasks.

    PubMed

    Sainath, Tara N; Kingsbury, Brian; Saon, George; Soltau, Hagen; Mohamed, Abdel-rahman; Dahl, George; Ramabhadran, Bhuvana

    2015-04-01

    Convolutional Neural Networks (CNNs) are an alternative type of neural network that can be used to reduce spectral variations and model spectral correlations which exist in signals. Since speech signals exhibit both of these properties, we hypothesize that CNNs are a more effective model for speech compared to Deep Neural Networks (DNNs). In this paper, we explore applying CNNs to large vocabulary continuous speech recognition (LVCSR) tasks. First, we determine the appropriate architecture to make CNNs effective compared to DNNs for LVCSR tasks. Specifically, we focus on how many convolutional layers are needed, what is an appropriate number of hidden units, what is the best pooling strategy. Second, investigate how to incorporate speaker-adapted features, which cannot directly be modeled by CNNs as they do not obey locality in frequency, into the CNN framework. Third, given the importance of sequence training for speech tasks, we introduce a strategy to use ReLU+dropout during Hessian-free sequence training of CNNs. Experiments on 3 LVCSR tasks indicate that a CNN with the proposed speaker-adapted and ReLU+dropout ideas allow for a 12%-14% relative improvement in WER over a strong DNN system, achieving state-of-the art results in these 3 tasks. PMID:25439765

  20. Large Phased Array Radar Using Networked Small Parabolic Reflectors

    NASA Technical Reports Server (NTRS)

    Amoozegar, Farid

    2006-01-01

    Multifunction phased array systems with radar, telecom, and imaging applications have already been established for flat plate phased arrays of dipoles, or waveguides. In this paper the design trades and candidate options for combining the radar and telecom functions of the Deep Space Network (DSN) into a single large transmit array of small parabolic reflectors will be discussed. In particular the effect of combing the radar and telecom functions on the sizes of individual antenna apertures and the corresponding spacing between the antenna elements of the array will be analyzed. A heterogeneous architecture for the DSN large transmit array is proposed to meet the radar and telecom requirements while considering the budget, scheduling, and strategic planning constrains.

  1. Wavelength and opto-electro-opto sharing and optimization in wavelength division multiplexing mesh networks with path protection

    NASA Astrophysics Data System (ADS)

    Wang, Kefei; Hamza, Haitham S.; Deogun, Jitender S.

    2006-03-01

    Given a physical network topology and a traffic demand, the problem of designing a survivable network with path protection is to select primary and backup paths based on resource optimization. A common approach to minimize resources is sharing. This problem has been investigated with the goal of optimizing the number of channels (i.e., wavelengths) needed for backup paths by imposing capacity sharing. However, because of the need and the cost for other devices, such as opto-electro-opto (OEO) regenerators, network provisioning should also take into consideration such resources in the optimization process. We address the problem of routing and wavelength assignment (RWA) for survivable networks with the objective of simultaneously optimizing wavelength links and OEOs. An integer linear program solution, a tabu search heuristic, and a genetic algorithm are proposed, and their performance is experimentally evaluated through extensive simulation. Our simulation results confirm an average of 30% reduction in the number of OEOs compared to that required with the well known shared-path protection scheme.

  2. 77 FR 58416 - Large Scale Networking (LSN); Middleware and Grid Interagency Coordination (MAGIC) Team

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-09-20

    ... From the Federal Register Online via the Government Publishing Office NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN); Middleware and Grid Interagency Coordination (MAGIC) Team AGENCY: The... to the Large Scale Networking (LSN) Coordinating Group (CG). Public Comments: The government...

  3. 78 FR 7464 - Large Scale Networking (LSN)-Middleware And Grid Interagency Coordination (MAGIC) Team

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-02-01

    ... From the Federal Register Online via the Government Publishing Office NATIONAL SCIENCE FOUNDATION Large Scale Networking (LSN)--Middleware And Grid Interagency Coordination (MAGIC) Team AGENCY: The... Team reports to the Large Scale Networking (LSN) Coordinating Group (CG). Public Comments:...

  4. Effect of diabetes and acute rejection on liver transplant outcomes: An analysis of the organ procurement and transplantation network/united network for organ sharing database.

    PubMed

    Kuo, Hung-Tien; Lum, Erik; Martin, Paul; Bunnapradist, Suphamai

    2016-06-01

    The effects of diabetic status and acute rejection (AR) on liver transplant outcomes are largely unknown. We studied 13,736 liver recipients from the United Network for Organ Sharing/Organ Procurement Transplant Network database who underwent transplantation between 2004 and 2007 with a functioning graft for greater than 1 year. The association of pretransplant diabetes mellitus (PDM), new-onset diabetes after transplant (NODAT), and AR rates on allograft failure, all-cause mortality, and cardiovascular mortality were determined. To determine the differential and joint effects of diabetic status and AR on transplant outcomes, recipients were further stratified into 6 groups: neither (reference, n = 6600); NODAT alone (n = 2054); PDM alone (n = 2414); AR alone (n = 1448); NODAT and AR (n = 707); and PDM and AR (n = 513). An analysis with hepatitis C virus (HCV) serostatus was also performed (HCV recipients, n = 6384; and non-HCV recipient, n = 5934). The median follow-up was 2537 days. The prevalence of PDM was 21.3%. At 1 year after transplant, the rates of NODAT and AR were 25.5% and 19.4%, respectively. Overall, PDM, NODAT, and AR were associated with increased risks for graft failure (PDM, hazard ratio [HR] = 1.31, P < 0.01; NODAT, HR = 1.11, P = 0.02; AR, HR = 1.28, P < 0.01). A multivariate Cox regression analysis of the 6 recipient groups demonstrated that NODAT alone was not significantly associated with any study outcomes. The presence of PDM, AR, NODAT and AR, and PDM and AR were associated with higher overall graft failure risk and mortality risk. The presence of PDM was associated with higher cardiovascular mortality risk. The analyses in both HCV-positive and HCV-negative cohorts showed a similar trend as in the overall cohort. In conclusion, PDM and AR, but not NODAT, is associated with increased mortality and liver allograft failure. Liver Transplantation 22 796-804 2016 AASLD. PMID:26850091

  5. Applying Social Network Analysis to Understand the Knowledge Sharing Behaviour of Practitioners in a Clinical Online Discussion Forum

    PubMed Central

    Abidi, Syed Sibte Raza

    2012-01-01

    Background Knowledge Translation (KT) plays a vital role in the modern health care community, facilitating the incorporation of new evidence into practice. Web 2.0 tools provide a useful mechanism for establishing an online KT environment in which health practitioners share their practice-related knowledge and experiences with an online community of practice. We have implemented a Web 2.0 based KT environment—an online discussion forum—for pediatric pain practitioners across seven different hospitals in Thailand. The online discussion forum enabled the pediatric pain practitioners to share and translate their experiential knowledge to help improve the management of pediatric pain in hospitals. Objective The goal of this research is to investigate the knowledge sharing dynamics of a community of practice through an online discussion forum. We evaluated the communication patterns of the community members using statistical and social network analysis methods in order to better understand how the online community engages to share experiential knowledge. Methods Statistical analyses and visualizations provide a broad overview of the communication patterns within the discussion forum. Social network analysis provides the tools to delve deeper into the social network, identifying the most active members of the community, reporting the overall health of the social network, isolating the potential core members of the social network, and exploring the inter-group relationships that exist across institutions and professions. Results The statistical analyses revealed a network dominated by a single institution and a single profession, and found a varied relationship between reading and posting content to the discussion forum. The social network analysis discovered a healthy network with strong communication patterns, while identifying which users are at the center of the community in terms of facilitating communication. The group-level analysis suggests that there is

  6. Shared end-to-content backup path protection in k-node (edge) content connected elastic optical datacenter networks.

    PubMed

    Li, Xin; Huang, Shanguo; Yin, Shan; Guo, Bingli; Zhao, Yongli; Zhang, Jie; Zhang, Min; Gu, Wanyi

    2016-05-01

    To quantitatively measure content connectivity and provide protection for different kinds of content, the concept of k-node (edge) content connectivity is proposed recently. Based on k-node (edge) content connectivity, k-node (edge) content connected elastic optical datacenter network (KC-EODN) is proposed to design disaster-resilient and spectrum-efficient optical datacenter networks. In KC-EODN, k independent end-to-content paths are established for each request. However, it will consume too much resource to assign dedicated spectrum for each end-to-content path. Spectrum sharing among multiple end-to-content paths of different requests can greatly improve resource efficiency. In this paper, a novel perfect matching based sharing principle among multiple end-to-content paths of different requests is proposed. Based on the new proposed sharing principle, we present the shared end-to-content backup path protection (SEBPP) scheme for KC-EODN. Integer linear program (ILP) model and heuristic algorithms are designed for SEBPP scheme with the objective of minimizing the total of working and backup spectrum resources. Numerical results show that the proposed SEBPP scheme can greatly reduce spectrum consumption while ensuring the survivability against natural disaster and multi-failures. PMID:27137559

  7. Managing Information Sharing within an Organizational Setting: A Social Network Perspective

    ERIC Educational Resources Information Center

    Hatala, John-Paul; Lutta, Joseph George

    2009-01-01

    Information sharing is critical to an organization's competitiveness and requires a free flow of information among members if the organization is to remain competitive. A review of the literature on organizational structure and information sharing was conducted to examine the research in this area. A case example illustrates how a social network…

  8. Relationship Between Large-Scale Functional and Structural Covariance Networks in Idiopathic Generalized Epilepsy

    PubMed Central

    Zhang, Zhiqiang; Mantini, Dante; Xu, Qiang; Wang, Zhengge; Chen, Guanghui; Jiao, Qing; Zang, Yu-Feng

    2013-01-01

    Abstract The human brain can be modeled as a network, whose structure can be revealed by either anatomical or functional connectivity analyses. Little is known, so far, about the topological features of the large-scale interregional functional covariance network (FCN) in the brain. Further, the relationship between the FCN and the structural covariance network (SCN) has not been characterized yet, in the intact as well as in the diseased brain. Here, we studied 59 patients with idiopathic generalized epilepsy characterized by tonic–clonic seizures and 59 healthy controls. We estimated the FCN and the SCN by measuring amplitude of low-frequency fluctuations (ALFF) and gray matter volume (GMV), respectively, and then we conducted graph theoretical analyses. Our ALFF-based FCN and GMV-based results revealed that the normal human brain is characterized by specific topological properties such as small worldness and highly-connected hub regions. The patients had an altered overall topology compared to the controls, suggesting that epilepsy is primarily a disorder of the cerebral network organization. Further, the patients had altered nodal characteristics in the subcortical and medial temporal regions and default-mode regions, for both the FCN and SCN. Importantly, the correspondence between the FCN and SCN was significantly larger in patients than in the controls. These results support the hypothesis that the SCN reflects shared long-term trophic mechanisms within functionally synchronous systems. They can also provide crucial information for understanding the interactions between the whole-brain network organization and pathology in generalized tonic–clonic seizures. PMID:23510272

  9. Peer Support Networks in a Large Introductory Psychology Class.

    ERIC Educational Resources Information Center

    Slotnick, Robert S.; And Others

    Networks have emerged as a major topic of interest in the behavioral sciences, and network concepts have recently been extended by community psychologists to higher education. To examine the effectiveness of peer networks within an introductory psychology class, networks of four students each met weekly in place of a lecture to review material and…

  10. Switch: a planning tool for power systems with large shares of intermittent renewable energy.

    PubMed

    Fripp, Matthias

    2012-06-01

    Wind and solar power are highly variable, so it is it unclear how large a role they can play in future power systems. This work introduces a new open-source electricity planning model--Switch--that identifies the least-cost strategy for using renewable and conventional generators and transmission in a large power system over a multidecade period. Switch includes an unprecedented amount of spatial and temporal detail, making it possible to address a new type of question about the optimal design and operation of power systems with large amounts of renewable power. A case study of California for 2012-2027 finds that there is no maximum possible penetration of wind and solar power--these resources could potentially be used to reduce emissions 90% or more below 1990 levels without reducing reliability or severely raising the cost of electricity. This work also finds that policies that encourage customers to shift electricity demand to times when renewable power is most abundant (e.g., well-timed charging of electric vehicles) could make it possible to achieve radical emission reductions at moderate costs. PMID:22506835