Science.gov

Sample records for distribution networks sistema

  1. Prototyping distributed simulation networks

    NASA Technical Reports Server (NTRS)

    Doubleday, Dennis L.

    1990-01-01

    Durra is a declarative language designed to support application-level programming. The use of Durra is illustrated to describe a simple distributed application: a simulation of a collection of networked vehicle simulators. It is shown how the language is used to describe the application, its components and structure, and how the runtime executive provides for the execution of the application.

  2. Distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Lacoss, Richard T.

    1986-09-01

    The Distributed Sensor Networks (DSN) program was aimed at developing distributed target surveillance and tracking methods for systems employing multiple spatially distributed sensors and processing resources. Such systems would be made up of sensors, data bases, and processors distributed throughout an area and interconnected by an appropriate digital data communication system. The hypothesis of the program was that through netting and distributed processing, the information from many sensors could be combined to yield effective surveillance systems. The overall concept called for a mix of sensor types as well as geographically distributed sensors. Surveillance and tracking of low-flying aircraft with ground-based acoustic and imaging sensors was used to develop and evaluate DSN concepts in the light of a specific problem. An experimental DSN testbed system was developed and has been used to test and demonstrate DSN techniques. Small arrays of microphones providing directional information were employed as acoustic sensors and visible TV cameras were used as imaging sensors in the testbed system. The primary accomplishment during this final report period was the demonstration of distributed real time tracking using both TV and acoustic sensors. Tracking was implemented as a geographically decentralized confederacy of autonomous cooperating nodes. Thus the feasibility of this organization has been established for a DSN system containing multiple sensor types as well as distributed nodes.

  3. Distributed Observer Network

    NASA Technical Reports Server (NTRS)

    2008-01-01

    NASA s advanced visual simulations are essential for analyses associated with life cycle planning, design, training, testing, operations, and evaluation. Kennedy Space Center, in particular, uses simulations for ground services and space exploration planning in an effort to reduce risk and costs while improving safety and performance. However, it has been difficult to circulate and share the results of simulation tools among the field centers, and distance and travel expenses have made timely collaboration even harder. In response, NASA joined with Valador Inc. to develop the Distributed Observer Network (DON), a collaborative environment that leverages game technology to bring 3-D simulations to conventional desktop and laptop computers. DON enables teams of engineers working on design and operations to view and collaborate on 3-D representations of data generated by authoritative tools. DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3-D visual environment. Multiple widely dispersed users, working individually or in groups, can view and analyze simulation results on desktop and laptop computers in real time.

  4. Distributed Observer Network

    NASA Technical Reports Server (NTRS)

    Conroy, Michael; Mazzone, Rebecca; Little, William; Elfrey, Priscilla; Mann, David; Mabie, Kevin; Cuddy, Thomas; Loundermon, Mario; Spiker, Stephen; McArthur, Frank; Srey, Tate; Bonilla, Dennis

    2010-01-01

    The Distributed Observer network (DON) is a NASA-collaborative environment that leverages game technology to bring three-dimensional simulations to conventional desktop and laptop computers in order to allow teams of engineers working on design and operations, either individually or in groups, to view and collaborate on 3D representations of data generated by authoritative tools such as Delmia Envision, Pro/Engineer, or Maya. The DON takes models and telemetry from these sources and, using commercial game engine technology, displays the simulation results in a 3D visual environment. DON has been designed to enhance accessibility and user ability to observe and analyze visual simulations in real time. A variety of NASA mission segment simulations [Synergistic Engineering Environment (SEE) data, NASA Enterprise Visualization Analysis (NEVA) ground processing simulations, the DSS simulation for lunar operations, and the Johnson Space Center (JSC) TRICK tool for guidance, navigation, and control analysis] were experimented with. Desired functionalities, [i.e. Tivo-like functions, the capability to communicate textually or via Voice-over-Internet Protocol (VoIP) among team members, and the ability to write and save notes to be accessed later] were targeted. The resulting DON application was slated for early 2008 release to support simulation use for the Constellation Program and its teams. Those using the DON connect through a client that runs on their PC or Mac. This enables them to observe and analyze the simulation data as their schedule allows, and to review it as frequently as desired. DON team members can move freely within the virtual world. Preset camera points can be established, enabling team members to jump to specific views. This improves opportunities for shared analysis of options, design reviews, tests, operations, training, and evaluations, and improves prospects for verification of requirements, issues, and approaches among dispersed teams.

  5. Distributed semantic networks and CLIPS

    NASA Technical Reports Server (NTRS)

    Snyder, James; Rodriguez, Tony

    1991-01-01

    Semantic networks of frames are commonly used as a method of reasoning in many problems. In most of these applications the semantic network exists as a single entity in a single process environment. Advances in workstation hardware provide support for more sophisticated applications involving multiple processes, interacting in a distributed environment. In these applications the semantic network may well be distributed over several concurrently executing tasks. This paper describes the design and implementation of a frame based, distributed semantic network in which frames are accessed both through C Language Integrated Production System (CLIPS) expert systems and procedural C++ language programs. The application area is a knowledge based, cooperative decision making model utilizing both rule based and procedural experts.

  6. Distributed downhole drilling network

    DOEpatents

    Hall, David R.; Hall, Jr., H. Tracy; Fox, Joe; Pixton, David S.

    2006-11-21

    A high-speed downhole network providing real-time data from downhole components of a drilling strings includes a bottom-hole node interfacing to a bottom-hole assembly located proximate the bottom end of a drill string. A top-hole node is connected proximate the top end of the drill string. One or several intermediate nodes are located along the drill string between the bottom-hole node and the top-hole node. The intermediate nodes are configured to receive and transmit data packets transmitted between the bottom-hole node and the top-hole node. A communications link, integrated into the drill string, is used to operably connect the bottom-hole node, the intermediate nodes, and the top-hole node. In selected embodiments, a personal or other computer may be connected to the top-hole node, to analyze data received from the intermediate and bottom-hole nodes.

  7. Degree distributions of growing networks.

    PubMed

    Krapivsky, P L; Rodgers, G J; Redner, S

    2001-06-01

    The in-degree and out-degree distributions of a growing network model are determined. The in-degree is the number of incoming links to a given node (and vice versa for out-degree). The network is built by (i) creation of new nodes which each immediately attach to a preexisting node, and (ii) creation of new links between preexisting nodes. This process naturally generates correlated in-degree and out-degree distributions. When the node and link creation rates are linear functions of node degree, these distributions exhibit distinct power-law forms. By tuning the parameters in these rates to reasonable values, exponents which agree with those of the web graph are obtained.

  8. Distributed wireless quantum communication networks

    NASA Astrophysics Data System (ADS)

    Yu, Xu-Tao; Xu, Jin; Zhang, Zai-Chen

    2013-09-01

    The distributed wireless quantum communication network (DWQCN) has a distributed network topology and transmits information by quantum states. In this paper, we present the concept of the DWQCN and propose a system scheme to transfer quantum states in the DWQCN. The system scheme for transmitting information between any two nodes in the DWQCN includes a routing protocol and a scheme for transferring quantum states. The routing protocol is on-demand and the routing metric is selected based on the number of entangled particle pairs. After setting up a route, quantum teleportation and entanglement swapping are used for transferring quantum states. Entanglement swapping is achieved along with the process of routing set up and the acknowledgment packet transmission. The measurement results of each entanglement swapping are piggybacked with route reply packets or acknowledgment packets. After entanglement swapping, a direct quantum link between source and destination is set up and quantum states are transferred by quantum teleportation. Adopting this scheme, the measurement results of entanglement swapping do not need to be transmitted specially, which decreases the wireless transmission cost and transmission delay.

  9. Optimal distributions for multiplex logistic networks

    NASA Astrophysics Data System (ADS)

    Solá Conde, Luis E.; Used, Javier; Romance, Miguel

    2016-06-01

    This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates.

  10. Optimal distributions for multiplex logistic networks.

    PubMed

    Solá Conde, Luis E; Used, Javier; Romance, Miguel

    2016-06-01

    This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates.

  11. Optimal distributions for multiplex logistic networks.

    PubMed

    Solá Conde, Luis E; Used, Javier; Romance, Miguel

    2016-06-01

    This paper presents some mathematical models for distribution of goods in logistic networks based on spectral analysis of complex networks. Given a steady distribution of a finished product, some numerical algorithms are presented for computing the weights in a multiplex logistic network that reach the equilibrium dynamics with high convergence rate. As an application, the logistic networks of Germany and Spain are analyzed in terms of their convergence rates. PMID:27368801

  12. Correct degree distribution of apollonian networks

    NASA Astrophysics Data System (ADS)

    Guo, Jin-Li; Wang, Li-Na

    2010-08-01

    In this paper, we point out that there is a shortcoming of the degree distribution and the analyzing approach of the Apollonian network in [Andrade J S, Herrmann H J, Andrade R F S, et al. Phys. Rev. Lett. 94, 018702 (2005).]. Because the Apollonian network is a deterministic network, its degree distribution can be directly calculated. We correct the degree distribution of the Apollonian network. We also give a numerical simulation of network evolution. The analytical result agrees with the simulation well. The results show that there is the shortcoming of the results of Herrmann et al.

  13. Sampling Networks from Their Posterior Predictive Distribution.

    PubMed

    Goyal, Ravi; De Gruttola, Victor; Blitzstein, Joseph

    2014-04-01

    Recent research indicates that knowledge about social networks can be leveraged to increase efficiency of interventions (Valente, 2012). However, in many settings, there exists considerable uncertainty regarding the structure of the network. This can render the estimation of potential effects of network-based interventions difficult, as providing appropriate guidance to select interventions often requires a representation of the whole network. In order to make use of the network property estimates to simulate the effect of interventions, it may be beneficial to sample networks from an estimated posterior predictive distribution, which can be specified using a wide range of models. Sampling networks from a posterior predictive distribution of network properties ensures that the uncertainty about network property parameters is adequately captured. The tendency for relationships among network properties to exhibit sharp thresholds has important implications for understanding global network topology in the presence of uncertainty; therefore, it is essential to account for uncertainty. We provide detail needed to sample networks for the specific network properties of degree distribution, mixing frequency, and clustering. Our methods to generate networks are demonstrated using simulated data and data from the National Longitudinal Study of Adolescent Health.

  14. Distance distribution in configuration-model networks

    NASA Astrophysics Data System (ADS)

    Nitzan, Mor; Katzav, Eytan; Kühn, Reimer; Biham, Ofer

    2016-06-01

    We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical simulations for networks with degenerate, binomial, and power-law degree distributions. The mean, mode, and variance of the distribution of shortest path lengths are also evaluated. These results provide expressions for central measures and dispersion measures of the distribution of shortest path lengths in terms of moments of the degree distribution, illuminating the connection between the two distributions.

  15. Distance distribution in configuration-model networks.

    PubMed

    Nitzan, Mor; Katzav, Eytan; Kühn, Reimer; Biham, Ofer

    2016-06-01

    We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical simulations for networks with degenerate, binomial, and power-law degree distributions. The mean, mode, and variance of the distribution of shortest path lengths are also evaluated. These results provide expressions for central measures and dispersion measures of the distribution of shortest path lengths in terms of moments of the degree distribution, illuminating the connection between the two distributions. PMID:27415282

  16. Distributed intelligence in an astronomical Distributed Sensor Network

    NASA Astrophysics Data System (ADS)

    White, R. R.; Davis, H.; Vestrand, W. T.; Wozniak, P. R.

    2008-03-01

    The Telescope Alert Operations Network System (TALONS) was designed and developed in the year 2000, around the architectural principles of a distributed sensor network. This network supported the original Rapid Telescopes for Optical Response (RAPTOR) project goals; however, only with further development could TALONS meet the goals of the larger Thinking Telescope Project. The complex objectives of the Thinking Telescope project required a paradigm shift in the software architecture - the centralised intelligence merged into the TALONS network operations could no longer meet all of the new requirements. The intelligence needed to be divorced from the network operations and developed as a series of peripheral intelligent agents, distributing the decision making and analytical processes based on the temporal volatility of the data. This paper is presented as only one part of the poster from the workshop and in it we will explore the details of this architecture and how that merges with the current Thinking Telescope system to meet our project goals.

  17. Distributing Executive Information Systems through Networks.

    ERIC Educational Resources Information Center

    Penrod, James I.; And Others

    1993-01-01

    Many colleges and universities will soon adopt distributed systems for executive information and decision support. Distribution of shared information through computer networks will improve decision-making processes dramatically on campuses. Critical success factors include administrative support, favorable organizational climate, ease of use,…

  18. Quantum key distribution networks layer model

    NASA Astrophysics Data System (ADS)

    Wen, Hao; Han, Zheng-fu; Hong, Pei-lin; Guo, Guang-can

    2008-03-01

    Quantum Key Distribution (QKD) networks allow multiple users to generate and share secret quantum keys with unconditional security. Although many schemes of QKD networks have been presented, they are only concentrated on the system realization and physical implementations. For the complete practical quantum network, a succinct theoretic model that systematically describes the working processes from physical schemes to key process protocols, from network topology to key management, and from quantum communication to classical communication is still absent. One would hope that research and experience have shown that there are certain succinct model in the design of communication network. With demonstration of the different QKD links and the four primary types of quantum networks including probability multiplexing, wavelength multiplexing, time multiplexing and quantum multiplexing, we suggest a layer model for QKD networks which will be compatible with different implementations and protocols. We divide it into four main layers by their functional independency while defining each layer's services and responsibilities in detail, orderly named quantum links layer, quantum networks layer, quantum key distribution protocols process layer, and keys management layer. It will be helpful for the systematic design and construction of real QKD networks.

  19. Distributed intelligent control and status networking

    NASA Technical Reports Server (NTRS)

    Fortin, Andre; Patel, Manoj

    1993-01-01

    Over the past two years, the Network Control Systems Branch (Code 532) has been investigating control and status networking technologies. These emerging technologies use distributed processing over a network to accomplish a particular custom task. These networks consist of small intelligent 'nodes' that perform simple tasks. Containing simple, inexpensive hardware and software, these nodes can be easily developed and maintained. Once networked, the nodes can perform a complex operation without a central host. This type of system provides an alternative to more complex control and status systems which require a central computer. This paper will provide some background and discuss some applications of this technology. It will also demonstrate the suitability of one particular technology for the Space Network (SN) and discuss the prototyping activities of Code 532 utilizing this technology.

  20. Benford’s Distribution in Complex Networks

    PubMed Central

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K.

    2016-01-01

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford’s distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford’s law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford’s law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford’s distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford’s law for scalefree networks but only for very narrow range of their parameters. PMID:27748398

  1. Benford’s Distribution in Complex Networks

    NASA Astrophysics Data System (ADS)

    Morzy, Mikołaj; Kajdanowicz, Tomasz; Szymański, Bolesław K.

    2016-10-01

    Many collections of numbers do not have a uniform distribution of the leading digit, but conform to a very particular pattern known as Benford’s distribution. This distribution has been found in numerous areas such as accounting data, voting registers, census data, and even in natural phenomena. Recently it has been reported that Benford’s law applies to online social networks. Here we introduce a set of rigorous tests for adherence to Benford’s law and apply it to verification of this claim, extending the scope of the experiment to various complex networks and to artificial networks created by several popular generative models. Our findings are that neither for real nor for artificial networks there is sufficient evidence for common conformity of network structural properties with Benford’s distribution. We find very weak evidence suggesting that three measures, degree centrality, betweenness centrality and local clustering coefficient, could adhere to Benford’s law for scalefree networks but only for very narrow range of their parameters.

  2. Tie strength distribution in scientific collaboration networks

    NASA Astrophysics Data System (ADS)

    Ke, Qing; Ahn, Yong-Yeol

    2014-09-01

    Science is increasingly dominated by teams. Understanding patterns of scientific collaboration and their impacts on the productivity and evolution of disciplines is crucial to understand scientific processes. Electronic bibliography offers a unique opportunity to map and investigate the nature of scientific collaboration. Recent studies have demonstrated a counterintuitive organizational pattern of scientific collaboration networks: densely interconnected local clusters consist of weak ties, whereas strong ties play the role of connecting different clusters. This pattern contrasts itself from many other types of networks where strong ties form communities while weak ties connect different communities. Although there are many models for collaboration networks, no model reproduces this pattern. In this paper, we present an evolution model of collaboration networks, which reproduces many properties of real-world collaboration networks, including the organization of tie strengths, skewed degree and weight distribution, high clustering, and assortative mixing.

  3. Resilient Core Networks for Energy Distribution

    SciTech Connect

    Kuntze, Nicolai; Rudolph, Carsten; Leivesley, Sally; Manz, David O.; Endicott-Popovsky, Barbara E.

    2014-07-28

    Abstract—Substations and their control are crucial for the availability of electricity in today’s energy distribution. Ad- vanced energy grids with Distributed Energy Resources require higher complexity in substations, distributed functionality and communication between devices inside substations and between substations. Also, substations include more and more intelligent devices and ICT based systems. All these devices are connected to other systems by different types of communication links or are situated in uncontrolled environments. Therefore, the risk of ICT based attacks on energy grids is growing. Consequently, security measures to counter these risks need to be an intrinsic part of energy grids. This paper introduces the concept of a Resilient Core Network to interconnected substations. This core network provides essen- tial security features, enables fast detection of attacks and allows for a distributed and autonomous mitigation of ICT based risks.

  4. Failure monitoring in water distribution networks.

    PubMed

    Misiunas, D; Vítkovský, J; Olsson, G; Lambert, M; Simpson, A

    2006-01-01

    An algorithm for the burst detection and location in water distribution networks based on the continuous monitoring of the flow rate at the entry point of the network and the pressure at a number of points within the network is presented. The approach is designed for medium to large bursts with opening times in the order of a few minutes and is suitable for networks of relatively small size, such as district metered areas (DMAs). The burst-induced increase in the inlet flow rate is detected using the modified cumulative sum (CUSUM) change detection test. Based on parameters obtained from the CUSUM test, the burst is simulated at a number of burst candidate locations. The calculated changes in pressure at the pressure monitoring points are then compared to the measured values and the location resulting in the best fit is selected as the burst location. The EPANET steady-state hydraulic solver is utilised to simulate the flows and pressures in the network. A sensitivity-based sampling design procedure is introduced to find the optimal positions for pressure monitoring points. The proposed algorithm is tested on a case study example network and shows potential for burst detection and location in real water distribution systems.

  5. Robust, Distributed Target Tracking Using Sensor Network

    NASA Astrophysics Data System (ADS)

    Neema, Kartavya

    Distributed target tracking using sensor networks is crucial for supporting a variety of applications such as battlefield monitoring, weather monitoring, and air traffic management. This dissertation presents a problem formulation and solution approach for distributed target tracking, comprising of sensor fusion and sensor target allocation problems, in the presence of faults in the sensor measurements. There are times when an architecture with central node is preferred but other times when distributed is necessary, we seek a distributed case that can approach the attractive features of centralized case. Therefore, we propose that the underlying two-fold goals of the distributed target tracking problem is to: (1) reach a consensus in the allocation decisions across the sensor network, and (2) achieve a consensus in the state estimates across all the sensors in the network. These goals ensure that each sensor node has the same information across the sensor network, and any node can behave as a central node. In the process of achieving our goals, we develop two new algorithms, one for distributed sensor-target allocation and another for distributed sensor fusion. The Dual Phase Consensus Algorithm (DPCA) for distributed sensor target allocation is a real time algorithm that works in two phases. The first phase of DPCA is similar to distributed sequential greedy search that combines the benefits of greedy and consensus algorithms to reach a feasible solution. The second phase iteratively improves the allocation eventually leading toward a global optimum. DPCA converges to a feasible solution at the order of number of sensors, and thus can be useful for implementation in real time systems. For distributed sensor fusion, we extend the state-of-art distributed Kalman filtering technique called Generalized Kalman Consensus Filter (GKCF), and make it robust against faults present in the sensor measurements. We particularly focus on two types of faults: (1) outliers in the

  6. Distributed control network for optogenetic experiments

    NASA Astrophysics Data System (ADS)

    Kasprowicz, G.; Juszczyk, B.; Mankiewicz, L.

    2014-11-01

    Nowadays optogenetic experiments are constructed to examine social behavioural relations in groups of animals. A novel concept of implantable device with distributed control network and advanced positioning capabilities is proposed. It is based on wireless energy transfer technology, micro-power radio interface and advanced signal processing.

  7. Energy distribution in disordered elastic networks

    NASA Astrophysics Data System (ADS)

    Plaza, Gustavo R.

    2010-09-01

    Disordered networks are found in many natural and artificial materials, from gels or cytoskeletal structures to metallic foams or bones. Here, the energy distribution in this type of networks is modeled, taking into account the orientation of the struts. A correlation between the orientation and the energy per unit volume is found and described as a function of the connectivity in the network and the relative bending stiffness of the struts. If one or both parameters have relatively large values, the struts aligned in the loading direction present the highest values of energy. On the contrary, if these have relatively small values, the highest values of energy can be reached in the struts oriented transversally. This result allows explaining in a simple way remodeling processes in biological materials, for example, the remodeling of trabecular bone and the reorganization in the cytoskeleton. Additionally, the correlation between the orientation, the affinity, and the bending-stretching ratio in the network is discussed.

  8. Optimal design of spatial distribution networks

    NASA Astrophysics Data System (ADS)

    Gastner, Michael T.; Newman, M. E. J.

    2006-07-01

    We consider the problem of constructing facilities such as hospitals, airports, or malls in a country with a nonuniform population density, such that the average distance from a person’s home to the nearest facility is minimized. We review some previous approximate treatments of this problem that indicate that the optimal distribution of facilities should have a density that increases with population density, but does so slower than linearly, as the two-thirds power. We confirm this result numerically for the particular case of the United States with recent population data using two independent methods, one a straightforward regression analysis, the other based on density-dependent map projections. We also consider strategies for linking the facilities to form a spatial network, such as a network of flights between airports, so that the combined cost of maintenance of and travel on the network is minimized. We show specific examples of such optimal networks for the case of the United States.

  9. Pruning Neural Networks with Distribution Estimation Algorithms

    SciTech Connect

    Cantu-Paz, E

    2003-01-15

    This paper describes the application of four evolutionary algorithms to the pruning of neural networks used in classification problems. Besides of a simple genetic algorithm (GA), the paper considers three distribution estimation algorithms (DEAs): a compact GA, an extended compact GA, and the Bayesian Optimization Algorithm. The objective is to determine if the DEAs present advantages over the simple GA in terms of accuracy or speed in this problem. The experiments used a feed forward neural network trained with standard back propagation and public-domain and artificial data sets. The pruned networks seemed to have better or equal accuracy than the original fully-connected networks. Only in a few cases, pruning resulted in less accurate networks. We found few differences in the accuracy of the networks pruned by the four EAs, but found important differences in the execution time. The results suggest that a simple GA with a small population might be the best algorithm for pruning networks on the data sets we tested.

  10. Ocean current mapping using networked distributed sensors

    NASA Astrophysics Data System (ADS)

    Huang, Chen-Fen; Yang, T. C.; Liu, Jin-Yuan; Burchfield, Tom; Schindall, Jeff

    2012-11-01

    Distributed underwater sensors are expected to provide environmental (oceanographic) monitoring over large areas. As fabrication technology advances, low cost sensors will be available for many applications. The sensors communicate to each other and are networked using acoustic communications. This paper proposes a method for ocean current tomography using distributed networked sensors and presents preliminary experimental results by this approach. Conventional acoustic tomography uses the acoustic sensors distributed on the periphery of an area of interest. Environmental reconstruction requires solving a challenging high dimensional inverse problem, typically requiring substantial computational effort. Given distributed sensors, currents can be constructed locally based on data from neighboring sensors. It is shown using simulated data that results obtained by the proposed method are similar to those obtained by a conventional tomographic method based on peripheral sensors. In addition, one finds that the distributed sensors consume much less energy than that by the conventional tomographic approach. An acoustic communication and networking experiment was conducted near the Sizihwan Bay in Kaohsiung, Taiwan, in May 2011. The communication signals are analyzed to measure currents as a function of space and time. The procedure is simple and can be implemented in real-time using in-buoy processing.

  11. Distributed intelligence in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Shirgur, Vikram L.; Rao, Vittal S.

    2003-07-01

    With the advent of new wireless standards, faster microprocessors and smart sensors, it has become possible to construct wireless sensor networks with ample processing and communication capability. Our thrust in this paper is toward implementing a collaborative processing system for wireless sensor networks. A number of research groups have developed algorithms for applications such as target tracking and location, environment monitoring, and health monitoring of structures. What has been missing is a distributed sensor processing system which provides a framework for these algorithms to function. The system described here borrows heavily from the parallel processing sphere especially the Parallel Virtual Machine (PVM) system developed by ORNL. To facilitate distribution of computational resources, a new algorithm has been proposed for efficient distribution with the use of minimum system resources, in other words, determining an optimal set of nodes which can handle the distributed computation. For this purpose, we assign costs to the various parameters of interest in the network such as the node energy level, the communication energy cost/complexity and resource availability. We then arrive at a cost function by assigning suitable weights to these costs and choose only those nodes whose cost function evaluates to above a particular threshold value. Implementation of typical feature extraction algorithms such as the Discrete Fourier Transform (DFT) and the Discrete Wavelet Transform (DWT) are discussed.

  12. Self Calibrated Wireless Distributed Environmental Sensory Networks

    NASA Astrophysics Data System (ADS)

    Fishbain, Barak; Moreno-Centeno, Erick

    2016-04-01

    Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art.

  13. Self Calibrated Wireless Distributed Environmental Sensory Networks

    PubMed Central

    Fishbain, Barak; Moreno-Centeno, Erick

    2016-01-01

    Recent advances in sensory and communication technologies have made Wireless Distributed Environmental Sensory Networks (WDESN) technically and economically feasible. WDESNs present an unprecedented tool for studying many environmental processes in a new way. However, the WDESNs’ calibration process is a major obstacle in them becoming the common practice. Here, we present a new, robust and efficient method for aggregating measurements acquired by an uncalibrated WDESN, and producing accurate estimates of the observed environmental variable’s true levels rendering the network as self-calibrated. The suggested method presents novelty both in group-decision-making and in environmental sensing as it offers a most valuable tool for distributed environmental monitoring data aggregation. Applying the method on an extensive real-life air-pollution dataset showed markedly more accurate results than the common practice and the state-of-the-art. PMID:27098279

  14. Structure Learning in Power Distribution Networks

    SciTech Connect

    Deka, Deepjyoti; Chertkov, Michael; Backhaus, Scott N.

    2015-01-13

    Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as these related to demand response, outage detection and management, and improved load-monitoring. Here, inspired by proliferation of the metering technology, we discuss statistical estimation problems in structurally loopy but operationally radial distribution grids consisting in learning operational layout of the network from measurements, e.g. voltage data, which are either already available or can be made available with a relatively minor investment. Our newly suggested algorithms apply to a wide range of realistic scenarios. The algorithms are also computationally efficient – polynomial in time – which is proven theoretically and illustrated computationally on a number of test cases. The technique developed can be applied to detect line failures in real time as well as to understand the scope of possible adversarial attacks on the grid.

  15. Radiation detection with distributed sensor networks

    NASA Astrophysics Data System (ADS)

    Mielke, Angela M.; Smith, Mark C.; Brennan, Sean M.; Torney, David C.; Jackson, Diana; Karlin, Josh F.; Maccabe, Arthur B.

    2005-05-01

    Given the heightened awareness and response to threats posed to national security, it is important to evaluate, and if possible, improve current measures being taken to ensure our nation"s safety. With terrorism so prevalent in our thoughts, the possible risk of nuclear attacks remains a major concern. Portal monitors are one type of technology that may be used to combat this risk. Their purpose is to detect nuclear materials and, if found, alert first responders to such a discovery. Los Alamos National Laboratory (LANL) is currently working on an alternative to these costly portal monitors through the Distributed Sensor Network (DSN) project. In collaboration with the University of New Mexico (UNM), this project aims to develop distributed networks of heterogeneous sensors with the ability to process data in-situ in order to produce real-time decisions regarding the presence of radioactive material within the network. The focus of the work described in this paper has been the evaluation of current commercial products available for application deployments, as well as the development of a sensor network in simulation to reduce key deployment issues.

  16. Using Content Distribution Networks for Astronomy Outreach

    NASA Astrophysics Data System (ADS)

    Jäger, M.; Christiansen, L. L.; André, M.

    2015-09-01

    Thousands of people from all over the world search the internet on a daily basis for the newest discoveries in astronomy: be it in the form of press releases, high resolution images, videos or even planetarium fulldome content. The growing amount of data available, combined with the increasing number of media files and users distributed across the globe, leads to a significant decrease in speed for those users located furthest from the server delivering the content. One solution for bringing astronomical content to users faster is to use a content delivery network.

  17. Fuzzy probabilistic design of water distribution networks

    NASA Astrophysics Data System (ADS)

    Fu, Guangtao; Kapelan, Zoran

    2011-05-01

    The primary aim of this paper is to present a fuzzy probabilistic approach for optimal design and rehabilitation of water distribution systems, combining aleatoric and epistemic uncertainties in a unified framework. The randomness and imprecision in future water consumption are characterized using fuzzy random variables whose realizations are not real but fuzzy numbers, and the nodal head requirements are represented by fuzzy sets, reflecting the imprecision in customers' requirements. The optimal design problem is formulated as a two-objective optimization problem, with minimization of total design cost and maximization of system performance as objectives. The system performance is measured by the fuzzy random reliability, defined as the probability that the fuzzy head requirements are satisfied across all network nodes. The satisfactory degree is represented by necessity measure or belief measure in the sense of the Dempster-Shafer theory of evidence. An efficient algorithm is proposed, within a Monte Carlo procedure, to calculate the fuzzy random system reliability and is effectively combined with the nondominated sorting genetic algorithm II (NSGAII) to derive the Pareto optimal design solutions. The newly proposed methodology is demonstrated with two case studies: the New York tunnels network and Hanoi network. The results from both cases indicate that the new methodology can effectively accommodate and handle various aleatoric and epistemic uncertainty sources arising from the design process and can provide optimal design solutions that are not only cost-effective but also have higher reliability to cope with severe future uncertainties.

  18. Information Weighted Consensus for Distributed Estimation in Vision Networks

    ERIC Educational Resources Information Center

    Kamal, Ahmed Tashrif

    2013-01-01

    Due to their high fault-tolerance, ease of installation and scalability to large networks, distributed algorithms have recently gained immense popularity in the sensor networks community, especially in computer vision. Multi-target tracking in a camera network is one of the fundamental problems in this domain. Distributed estimation algorithms…

  19. Linkage problem, distribution estimation, and Bayesian networks.

    PubMed

    Pelikan, M; Goldberg, D E; Cantú-Paz, E

    2000-01-01

    This paper proposes an algorithm that uses an estimation of the joint distribution of promising solutions in order to generate new candidate solutions. The algorithm is settled into the context of genetic and evolutionary computation and the algorithms based on the estimation of distributions. The proposed algorithm is called the Bayesian Optimization Algorithm (BOA). To estimate the distribution of promising solutions, the techniques for modeling multivariate data by Bayesian networks are used. The BOA identifies, reproduces, and mixes building blocks up to a specified order. It is independent of the ordering of the variables in strings representing the solutions. Moreover, prior information about the problem can be incorporated into the algorithm, but it is not essential. First experiments were done with additively decomposable problems with both nonoverlapping as well as overlapping building blocks. The proposed algorithm is able to solve all but one of the tested problems in linear or close to linear time with respect to the problem size. Except for the maximal order of interactions to be covered, the algorithm does not use any prior knowledge about the problem. The BOA represents a step toward alleviating the problem of identifying and mixing building blocks correctly to obtain good solutions for problems with very limited domain information.

  20. Advanced Energy Storage Management in Distribution Network

    SciTech Connect

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

    2016-01-01

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

  1. Social Networking Adapted for Distributed Scientific Collaboration

    NASA Technical Reports Server (NTRS)

    Karimabadi, Homa

    2012-01-01

    Share is a social networking site with novel, specially designed feature sets to enable simultaneous remote collaboration and sharing of large data sets among scientists. The site will include not only the standard features found on popular consumer-oriented social networking sites such as Facebook and Myspace, but also a number of powerful tools to extend its functionality to a science collaboration site. A Virtual Observatory is a promising technology for making data accessible from various missions and instruments through a Web browser. Sci-Share augments services provided by Virtual Observatories by enabling distributed collaboration and sharing of downloaded and/or processed data among scientists. This will, in turn, increase science returns from NASA missions. Sci-Share also enables better utilization of NASA s high-performance computing resources by providing an easy and central mechanism to access and share large files on users space or those saved on mass storage. The most common means of remote scientific collaboration today remains the trio of e-mail for electronic communication, FTP for file sharing, and personalized Web sites for dissemination of papers and research results. Each of these tools has well-known limitations. Sci-Share transforms the social networking paradigm into a scientific collaboration environment by offering powerful tools for cooperative discourse and digital content sharing. Sci-Share differentiates itself by serving as an online repository for users digital content with the following unique features: a) Sharing of any file type, any size, from anywhere; b) Creation of projects and groups for controlled sharing; c) Module for sharing files on HPC (High Performance Computing) sites; d) Universal accessibility of staged files as embedded links on other sites (e.g. Facebook) and tools (e.g. e-mail); e) Drag-and-drop transfer of large files, replacing awkward e-mail attachments (and file size limitations); f) Enterprise-level data and

  2. Power distribution in two-dimensional optical network channels

    NASA Astrophysics Data System (ADS)

    Wang, Dong-Xue; Karim, Mohammad A.

    1996-04-01

    The power distribution in two-dimensional optical network channels is analyzed. The maximum number of allowable channels as determined by the characteristics of optical detector is identified, in particular, for neural-network and wavelet-transform applications.

  3. Architectures, stability and optimization for clock distribution networks

    NASA Astrophysics Data System (ADS)

    Carareto, Rodrigo; Orsatti, Fernando M.; Piqueira, José Roberto C.

    2012-12-01

    Synchronous telecommunication networks, distributed control systems and integrated circuits have its accuracy of operation dependent on the existence of a reliable time basis signal extracted from the line data stream and acquirable to each node. In this sense, the existence of a sub-network (inside the main network) dedicated to the distribution of the clock signals is crucially important. There are different solutions for the architecture of the time distribution sub-network and choosing one of them depends on cost, precision, reliability and operational security. In this work we expose: (i) the possible time distribution networks and their usual topologies and arrangements. (ii) How parameters of the network nodes can affect the reachability and stability of the synchronous state of a network. (iii) Optimizations methods for synchronous networks which can provide low cost architectures with operational precision, reliability and security.

  4. Distribution of entanglement in large-scale quantum networks.

    PubMed

    Perseguers, S; Lapeyre, G J; Cavalcanti, D; Lewenstein, M; Acín, A

    2013-09-01

    The concentration and distribution of quantum entanglement is an essential ingredient in emerging quantum information technologies. Much theoretical and experimental effort has been expended in understanding how to distribute entanglement in one-dimensional networks. However, as experimental techniques in quantum communication develop, protocols for multi-dimensional systems become essential. Here, we focus on recent theoretical developments in protocols for distributing entanglement in regular and complex networks, with particular attention to percolation theory and network-based error correction.

  5. A Complex Network Approach to Distributional Semantic Models

    PubMed Central

    Utsumi, Akira

    2015-01-01

    A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models. PMID:26295940

  6. Network Capacity Assessment of CHP-based Distributed Generation on Urban Energy Distribution Networks

    NASA Astrophysics Data System (ADS)

    Zhang, Xianjun

    The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy market, considered to be an effective solution to promote energy efficiency. In the urban environment, the electricity, water and natural gas distribution networks are becoming increasingly interconnected with the growing penetration of the CHP-based DG. Subsequently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and siting for a larger test bed with the given information of energy infrastructures. In this context, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The proposed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation performances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electricity, gas, and water system models were developed individually and coupled by the developed CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical

  7. Degree Distribution in Quantum Walks on Complex Networks

    NASA Astrophysics Data System (ADS)

    Faccin, Mauro; Johnson, Tomi; Biamonte, Jacob; Kais, Sabre; Migdał, Piotr

    2013-10-01

    In this theoretical study, we analyze quantum walks on complex networks, which model network-based processes ranging from quantum computing to biology and even sociology. Specifically, we analytically relate the average long-time probability distribution for the location of a unitary quantum walker to that of a corresponding classical walker. The distribution of the classical walker is proportional to the distribution of degrees, which measures the connectivity of the network nodes and underlies many methods for analyzing classical networks, including website ranking. The quantum distribution becomes exactly equal to the classical distribution when the walk has zero energy, and at higher energies, the difference, the so-called quantumness, is bounded by the energy of the initial state. We give an example for which the quantumness equals a Rényi entropy of the normalized weighted degrees, guiding us to regimes for which the classical degree-dependent result is recovered and others for which quantum effects dominate.

  8. New behavior of degree distribution in connected communication networks

    NASA Astrophysics Data System (ADS)

    Benyoussef, Marwa; Ez-Zahraouy, Hamid; Benyoussef, Abdelilah

    2014-03-01

    The behavior of the degree distribution of two interdependent Barabasi-Albert (BA) sub-networks has been investigated numerically. The final complex structure obtained after connection of the two BA subnets exhibits two different kind of degree distribution law, which depends strongly on the manner in which the connection between the two subnets has been made. When connecting two existing BA subnets, the degree distribution follows a Gaussian distribution, while ensuring that the highest frequency level is still around the average degree of the final network. Whereas, when the connection is established progressively at the same time of the formation of the two BA subnets, the degree distribution follows a power-law scaling observed in real networks. It is also found that the evolution of links formed over a time for a specific node follows the same behavior, as the BA networks.

  9. Pain: A Distributed Brain Information Network?

    PubMed Central

    Mano, Hiroaki; Seymour, Ben

    2015-01-01

    Understanding how pain is processed in the brain has been an enduring puzzle, because there doesn't appear to be a single “pain cortex” that directly codes the subjective perception of pain. An emerging concept is that, instead, pain might emerge from the coordinated activity of an integrated brain network. In support of this view, Woo and colleagues present evidence that distinct brain networks support the subjective changes in pain that result from nociceptive input and self-directed cognitive modulation. This evidence for the sensitivity of distinct neural subsystems to different aspects of pain opens up the way to more formal computational network theories of pain. PMID:25562782

  10. Electricity distribution networks: Changing regulatory approaches

    NASA Astrophysics Data System (ADS)

    Cambini, Carlo

    2016-09-01

    Increasing the penetration of distributed generation and smart grid technologies requires substantial investments. A study proposes an innovative approach that combines four regulatory tools to provide economic incentives for distribution system operators to facilitate these innovative practices.

  11. Minimizing communication cost among distributed controllers in software defined networks

    NASA Astrophysics Data System (ADS)

    Arlimatti, Shivaleela; Elbreiki, Walid; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

    2016-08-01

    Software Defined Networking (SDN) is a new paradigm to increase the flexibility of today's network by promising for a programmable network. The fundamental idea behind this new architecture is to simplify network complexity by decoupling control plane and data plane of the network devices, and by making the control plane centralized. Recently controllers have distributed to solve the problem of single point of failure, and to increase scalability and flexibility during workload distribution. Even though, controllers are flexible and scalable to accommodate more number of network switches, yet the problem of intercommunication cost between distributed controllers is still challenging issue in the Software Defined Network environment. This paper, aims to fill the gap by proposing a new mechanism, which minimizes intercommunication cost with graph partitioning algorithm, an NP hard problem. The methodology proposed in this paper is, swapping of network elements between controller domains to minimize communication cost by calculating communication gain. The swapping of elements minimizes inter and intra communication cost among network domains. We validate our work with the OMNeT++ simulation environment tool. Simulation results show that the proposed mechanism minimizes the inter domain communication cost among controllers compared to traditional distributed controllers.

  12. Memory Network For Distributed Data Processors

    NASA Technical Reports Server (NTRS)

    Bolen, David; Jensen, Dean; Millard, ED; Robinson, Dave; Scanlon, George

    1992-01-01

    Universal Memory Network (UMN) is modular, digital data-communication system enabling computers with differing bus architectures to share 32-bit-wide data between locations up to 3 km apart with less than one millisecond of latency. Makes it possible to design sophisticated real-time and near-real-time data-processing systems without data-transfer "bottlenecks". This enterprise network permits transmission of volume of data equivalent to an encyclopedia each second. Facilities benefiting from Universal Memory Network include telemetry stations, simulation facilities, power-plants, and large laboratories or any facility sharing very large volumes of data. Main hub of UMN is reflection center including smaller hubs called Shared Memory Interfaces.

  13. Degree distributions of bipartite networks and their projections

    NASA Astrophysics Data System (ADS)

    Vasques Filho, Demival; O'Neale, Dion

    Bipartite networks play an important role in the analysis of social and economic systems as they explicitly show the conceptual links between different types of entities. As an example, it is possible to build networks to investigate interactions regarding scientific and technological innovation that are well represented by a natural bipartite structure. Since we are often most interested in only one of the node types (e.g. the authors in an author-publication network), it is common to end up working with a projected version of the underlying bipartite network. The topology of projections and the dynamics that take place on it are highly dependent on the probability distribution of nodes degrees. We use the formalism of generating functions to infer how the degree distributions of the original bipartite network affect the distribution in the projected version. Moreover, we create artificial bipartite graphs by arbitrarily choosing degree distributions for the sets of nodes and construct the projection to analyze the resulting probability distribution. Our findings show that when projecting onto a particular set of nodes, the resulting degree distribution follows the behavior of the probability distribution of such nodes, subject, however, to the tail of the opposite distribution.

  14. Flow distributions and spatial correlations in human brain capillary networks

    NASA Astrophysics Data System (ADS)

    Lorthois, Sylvie; Peyrounette, Myriam; Larue, Anne; Le Borgne, Tanguy

    2015-11-01

    The vascular system of the human brain cortex is composed of a space filling mesh-like capillary network connected upstream and downstream to branched quasi-fractal arterioles and venules. The distribution of blood flow rates in these networks may affect the efficiency of oxygen transfer processes. Here, we investigate the distribution and correlation properties of blood flow velocities from numerical simulations in large 3D human intra-cortical vascular network (10000 segments) obtained from an anatomical database. In each segment, flow is solved from a 1D non-linear model taking account of the complex rheological properties of blood flow in microcirculation to deduce blood pressure, blood flow and red blood cell volume fraction distributions throughout the network. The network structural complexity is found to impart broad and spatially correlated Lagrangian velocity distributions, leading to power law transit time distributions. The origins of this behavior (existence of velocity correlations in capillary networks, influence of the coupling with the feeding arterioles and draining veins, topological disorder, complex blood rheology) are studied by comparison with results obtained in various model capillary networks of controlled disorder. ERC BrainMicroFlow GA615102, ERC ReactiveFronts GA648377.

  15. Optimization of an interactive distributive computer network

    NASA Technical Reports Server (NTRS)

    Frederick, V.

    1985-01-01

    The activities under a cooperative agreement for the development of a computer network are briefly summarized. Research activities covered are: computer operating systems optimization and integration; software development and implementation of the IRIS (Infrared Imaging of Shuttle) Experiment; and software design, development, and implementation of the APS (Aerosol Particle System) Experiment.

  16. Organising metabolic networks: Cycles in flux distributions.

    PubMed

    Kritz, Maurício Vieira; Trindade Dos Santos, Marcelo; Urrutia, Sebastián; Schwartz, Jean-Marc

    2010-08-01

    Metabolic networks are among the most widely studied biological systems. The topology and interconnections of metabolic reactions have been well described for many species. This is, however, not sufficient to understand how their activity is regulated in living organisms. These descriptions depict a static set of possible chains of reactions, with no information about the dynamic activity of reaction fluxes. Cyclic structures are thought to play a central role in the homeostasis of biological systems and in their resilience to a changing environment. In this work, we present a methodology to help investigating dynamic fluxes associated to biochemical reactions in metabolic networks. We introduce an algorithm for partitioning fluxes between cyclic and acyclic sub-networks, adapted from an algorithm initially developed to study fluxes in trophic networks. Using this algorithm, we analyse three metabolic systems: the central metabolism of wild type and a deletion mutant of Escherichia coli, erythrocyte metabolism and the central metabolism of the bacterium Methylobacterium extorquens. This methodology unveils the role of cycles in driving and maintaining metabolic fluxes under perturbations in these examples, and may be used to further investigate and understand the organisational invariance of biological systems.

  17. Collaborative Estimation in Distributed Sensor Networks

    ERIC Educational Resources Information Center

    Kar, Swarnendu

    2013-01-01

    Networks of smart ultra-portable devices are already indispensable in our lives, augmenting our senses and connecting our lives through real time processing and communication of sensory (e.g., audio, video, location) inputs. Though usually hidden from the user's sight, the engineering of these devices involves fierce tradeoffs between energy…

  18. Optical Intrabuilding and Interbuilding Distribution Networks.

    ERIC Educational Resources Information Center

    Hull, Joseph A.

    Fiber optics communication technology is a potential competitive alternative to coaxial cable and shielded twisted pairlines as a wide-band communications medium. Pilot demonstrations by public institutions such as the health care delivery system can test the application of this new technology. Fiber optic networks may have the potential to be…

  19. Directed networks' different link formation mechanisms causing degree distribution distinction

    NASA Astrophysics Data System (ADS)

    Behfar, Stefan Kambiz; Turkina, Ekaterina; Cohendet, Patrick; Burger-Helmchen, Thierry

    2016-11-01

    Within undirected networks, scientists have shown much interest in presenting power-law features. For instance, Barabási and Albert (1999) claimed that a common property of many large networks is that vertex connectivity follows scale-free power-law distribution, and in another study Barabási et al. (2002) showed power law evolution in the social network of scientific collaboration. At the same time, Jiang et al. (2011) discussed deviation from power-law distribution; others indicated that size effect (Bagrow et al., 2008), information filtering mechanism (Mossa et al., 2002), and birth and death process (Shi et al., 2005) could account for this deviation. Within directed networks, many authors have considered that outlinks follow a similar mechanism of creation as inlinks' (Faloutsos et al., 1999; Krapivsky et al., 2001; Tanimoto, 2009) with link creation rate being the linear function of node degree, resulting in a power-law shape for both indegree and outdegree distribution. Some other authors have made an assumption that directed networks, such as scientific collaboration or citation, behave as undirected, resulting in a power-law degree distribution accordingly (Barabási et al., 2002). At the same time, we claim (1) Outlinks feature different degree distributions than inlinks; where different link formation mechanisms cause the distribution distinctions, (2) in/outdegree distribution distinction holds for different levels of system decomposition; therefore this distribution distinction is a property of directed networks. First, we emphasize in/outlink formation mechanisms as causal factors for distinction between indegree and outdegree distributions (where this distinction has already been noticed in Barker et al. (2010) and Baxter et al. (2006)) within a sample network of OSS projects as well as Java software corpus as a network. Second, we analyze whether this distribution distinction holds for different levels of system decomposition: open

  20. A distributed framework for inter-domain virtual network embedding

    NASA Astrophysics Data System (ADS)

    Wang, Zihua; Han, Yanni; Lin, Tao; Tang, Hui

    2013-03-01

    Network virtualization has been a promising technology for overcoming the Internet impasse. A main challenge in network virtualization is the efficient assignment of virtual resources. Existing work focused on intra-domain solutions whereas inter-domain situation is more practical in realistic setting. In this paper, we present a distributed inter-domain framework for mapping virtual networks to physical networks which can ameliorate the performance of the virtual network embedding. The distributed framework is based on a Multi-agent approach. A set of messages for information exchange is defined. We design different operations and IPTV use scenarios to validate the advantages of our framework. Use cases shows that our framework can solve the inter-domain problem efficiently.

  1. Timing and time signal distribution in digital communications networks

    NASA Astrophysics Data System (ADS)

    Kihara, Masami; Imaoka, Atushi

    1992-06-01

    The timing signal distribution characteristics of a digital communications network are evaluated to determine the Maximum Time Interval Error (MTIE) of the network; reference is made to the performance of network components such as transmission systems, slave clocks and timing distribution systems in intraoffices. The MTIE of each component is measured and used to determine the allowable MTIE of that component. The maximum number of slave node chains is shown to be 20. Time signal distribution performance is detailed. It is shown that time synchronization accuracy is of the order of submicroseconds between nodes separated by 2400 km over a two year period. For intra-office time signal distribution, the relative time accuracy is less than 3 nanoseconds using an 8 Mb/s round trip digital interface to connect a time signal supply in an office to dispersed equipment.

  2. High Speed Quantum Key Distribution Over Optical Fiber Network System.

    PubMed

    Ma, Lijun; Mink, Alan; Tang, Xiao

    2009-01-01

    The National Institute of Standards and Technology (NIST) has developed a number of complete fiber-based high-speed quantum key distribution (QKD) systems that includes an 850 nm QKD system for a local area network (LAN), a 1310 nm QKD system for a metropolitan area network (MAN), and a 3-node quantum network controlled by a network manager. This paper discusses the key techniques used to implement these systems, which include polarization recovery, noise reduction, frequency up-conversion detection based on a periodically polled lithium nitrate (PPLN) waveguide, custom high-speed data handling boards and quantum network management. Using our quantum network, a QKD secured video surveillance application has been demonstrated. Our intention is to show the feasibility and sophistication of QKD systems based on current technology. PMID:27504218

  3. Department Networks and Distributed Leadership in Schools

    ERIC Educational Resources Information Center

    de Lima, Jorge Avila

    2008-01-01

    Many schools are organised into departments which function as contexts that frame teachers' professional experiences in important ways. Some educational systems have adopted distributed forms of leadership within schools that rely strongly on the departmental structure and on the role of the department coordinator as teacher leader. This paper…

  4. Rewiring dynamical networks with prescribed degree distribution for enhancing synchronizability

    NASA Astrophysics Data System (ADS)

    Dadashi, Majid; Barjasteh, Iman; Jalili, Mahdi

    2010-12-01

    In this paper, we present an algorithm for enhancing synchronizability of dynamical networks with prescribed degree distribution. The algorithm takes an unweighted and undirected network as input and outputs a network with the same node-degree distribution and enhanced synchronization properties. The rewirings are based on the properties of the Laplacian of the connection graph, i.e., the eigenvectors corresponding to the second smallest and the largest eigenvalues of the Laplacian. A term proportional to the eigenvectors is adopted to choose potential edges for rewiring, provided that the node-degree distribution is preserved. The algorithm can be implemented on networks of any sizes as long as their eigenvalues and eigenvectors can be calculated with standard algorithms. The effectiveness of the proposed algorithm in enhancing the network synchronizability is revealed by numerical simulation on a number of sample networks including scale-free, Watts-Strogatz, and Erdős-Rényi graphs. Furthermore, a number of network's structural parameters such as node betweenness centrality, edge betweenness centrality, average path length, clustering coefficient, and degree assortativity are tracked as a function of optimization steps.

  5. LaRC local area networks to support distributed computing

    NASA Technical Reports Server (NTRS)

    Riddle, E. P.

    1984-01-01

    The Langley Research Center's (LaRC) Local Area Network (LAN) effort is discussed. LaRC initiated the development of a LAN to support a growing distributed computing environment at the Center. The purpose of the network is to provide an improved capability (over inteactive and RJE terminal access) for sharing multivendor computer resources. Specifically, the network will provide a data highway for the transfer of files between mainframe computers, minicomputers, work stations, and personal computers. An important influence on the overall network design was the vital need of LaRC researchers to efficiently utilize the large CDC mainframe computers in the central scientific computing facility. Although there was a steady migration from a centralized to a distributed computing environment at LaRC in recent years, the work load on the central resources increased. Major emphasis in the network design was on communication with the central resources within the distributed environment. The network to be implemented will allow researchers to utilize the central resources, distributed minicomputers, work stations, and personal computers to obtain the proper level of computing power to efficiently perform their jobs.

  6. Discriminating topology in galaxy distributions using network analysis

    NASA Astrophysics Data System (ADS)

    Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl

    2016-07-01

    The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.

  7. Distributed fault detection over sensor networks with Markovian switching topologies

    NASA Astrophysics Data System (ADS)

    Ge, Xiaohua; Han, Qing-Long

    2014-05-01

    This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.

  8. Preservation of network degree distributions from non-uniform failures

    NASA Astrophysics Data System (ADS)

    Karrer, B.; Ghoshal, G.

    2008-03-01

    There has been a considerable amount of interest in recent years on the robustness of networks to failures. Many previous studies have concentrated on the effects of node and edge removals on the connectivity structure of a static network; the networks are considered to be static in the sense that no compensatory measures are allowed for recovery of the original structure. Real world networks such as the world wide web, however, are not static and experience a considerable amount of turnover, where nodes and edges are both added and deleted. Considering degree-based node removals, we examine the possibility of preserving networks from these types of disruptions. We recover the original degree distribution by allowing the network to react to the attack by introducing new nodes and attaching their edges via specially tailored schemes. We focus particularly on the case of non-uniform failures, a subject that has received little attention in the context of evolving networks. Using a combination of analytical techniques and numerical simulations, we demonstrate how to preserve the exact degree distribution of the studied networks from various forms of attack.

  9. A distributed name resolution system in information centric networks

    NASA Astrophysics Data System (ADS)

    Elbreiki, Walid; Arlimatti, Shivaleela; Hassan, Suhaidi; Habbal, Adib; Elshaikh, Mohamed

    2016-08-01

    Information Centric Networks (ICN) is the new paradigm that envisages to shift the Internet away from its existing Point-to-Point architecture to a data centric, where communication is based on named hosts rather than the information stored on these hosts. Name Resolution is the center of attraction for ICN, where Named Data Objects (NDO) are used for identifying the information and guiding for routing or forwarding inside ICN. Recently, several researches use distributed NRS to overcome the problem of interest flooding, congestion and overloading. Yet the distribution of NRS is based on random distribution. How to distribute the NRS is still an important and challenging problem. In this work, we address the problem of distribution of NRS by proposing a new mechanism called Distributed Name Resolution System (DNRS), by considering the time of publishing the NDOs in the NRS. This mechanism partitions the network to distribute the workload among NRSs by increasing storage capacity. In addition, partitioning the network increases flexibility and scalability of NRS. We evaluate the effectiveness of our proposed mechanism, which achieves lesser end-to-end delay with more average throughputs compared to random distribution of NRS without disturbing the underlying routing or forwarding strategies.

  10. Exploring empowerment in settings: mapping distributions of network power.

    PubMed

    Neal, Jennifer Watling

    2014-06-01

    This paper brings together two trends in the empowerment literature-understanding empowerment in settings and understanding empowerment as relational-by examining what makes settings empowering from a social network perspective. Specifically, extending Neal and Neal's (Am J Community Psychol 48(3/4):157-167, 2011) conception of network power, an empowering setting is defined as one in which (1) actors have existing relationships that allow for the exchange of resources and (2) the distribution of network power among actors in the setting is roughly equal. The paper includes a description of how researchers can examine distributions of network power in settings. Next, this process is illustrated in both an abstract example and using empirical data on early adolescents' peer relationships in urban classrooms. Finally, implications for theory, methods, and intervention related to understanding empowering settings are explored.

  11. Interconnecting PV on New York City's Secondary Network Distribution System

    SciTech Connect

    Anderson, K; Coddington, M; Burman, K; Hayter, S; Kroposki, B; Watson, and A

    2009-11-01

    The U.S. Department of Energy (DOE) has teamed with cities across the country through the Solar America Cities (SAC) partnership program to help reduce barriers and accelerate implementation of solar energy. The New York City SAC team is a partnership between the City University of New York (CUNY), the New York City Mayor s Office of Long-term Planning and Sustainability, and the New York City Economic Development Corporation (NYCEDC).The New York City SAC team is working with DOE s National Renewable Energy Laboratory (NREL) and Con Edison, the local utility, to develop a roadmap for photovoltaic (PV) installations in the five boroughs. The city set a goal to increase its installed PV capacity from1.1 MW in 2005 to 8.1 MW by 2015 (the maximum allowed in 2005). A key barrier to reaching this goal, however, is the complexity of the interconnection process with the local utility. Unique challenges are associated with connecting distributed PV systems to secondary network distribution systems (simplified to networks in this report). Although most areas of the country use simpler radial distribution systems to distribute electricity, larger metropolitan areas like New York City typically use networks to increase reliability in large load centers. Unlike the radial distribution system, where each customer receives power through a single line, a network uses a grid of interconnected lines to deliver power to each customer through several parallel circuits and sources. This redundancy improves reliability, but it also requires more complicated coordination and protection schemes that can be disrupted by energy exported from distributed PV systems. Currently, Con Edison studies each potential PV system in New York City to evaluate the system s impact on the network, but this is time consuming for utility engineers and may delay the customer s project or add cost for larger installations. City leaders would like to streamline this process to facilitate faster, simpler, and

  12. Degree distribution of random birth-and-death network with network size decline

    NASA Astrophysics Data System (ADS)

    Xiao-Jun, Zhang; Hui-Lan, Yang

    2016-06-01

    In this paper, we provide a general method to obtain the exact solutions of the degree distributions for random birth-and-death network (RBDN) with network size decline. First, by stochastic process rules, the steady state transformation equations and steady state degree distribution equations are given in the case of m ≥ 3 and 0 < p < 1/2, then the average degree of network with n nodes is introduced to calculate the degree distributions. Specifically, taking m = 3 for example, we explain the detailed solving process, in which computer simulation is used to verify our degree distribution solutions. In addition, the tail characteristics of the degree distribution are discussed. Our findings suggest that the degree distributions will exhibit Poisson tail property for the declining RBDN. Project supported by the National Natural Science Foundation of China (Grant No. 61273015) and the Chinese Scholarship Council.

  13. Degree distribution of random birth-and-death network with network size decline

    NASA Astrophysics Data System (ADS)

    Xiao-Jun, Zhang; Hui-Lan, Yang

    2016-06-01

    In this paper, we provide a general method to obtain the exact solutions of the degree distributions for random birth-and-death network (RBDN) with network size decline. First, by stochastic process rules, the steady state transformation equations and steady state degree distribution equations are given in the case of m ≥ 3 and 0 < p < 1/2, then the average degree of network with n nodes is introduced to calculate the degree distributions. Specifically, taking m = 3 for example, we explain the detailed solving process, in which computer simulation is used to verify our degree distribution solutions. In addition, the tail characteristics of the degree distribution are discussed. Our findings suggest that the degree distributions will exhibit Poisson tail property for the declining RBDN. Project supported by the National Natural Science Foundation of China (Grant No. 61273015) and the Chinese Scholarship Council.

  14. Distributed authentication for randomly compromised networks

    NASA Astrophysics Data System (ADS)

    Beals, Travis R.; Hynes, Kevin P.; Sanders, Barry C.

    2009-08-01

    We introduce a simple, practical approach with probabilistic information-theoretic security to solve one of quantum key distribution's major security weaknesses: the requirement of an authenticated classical channel to prevent man-in-the-middle attacks. Our scheme employs classical secret sharing and partially trusted intermediaries to provide arbitrarily high confidence in the security of the protocol. Although certain failures elude detection, we discuss preemptive strategies to reduce the probability of failure to an arbitrarily small level: the probability of such failures is exponentially suppressed with increases in connectivity (i.e. connections per node).

  15. Development of Distributed Generic Simulator (GenSim) through Invention of Simulated Network (simNetwork)

    NASA Astrophysics Data System (ADS)

    Koo, Cheol-Hea; Lee, Hoon-Hee; Cheon, Yee-Jin

    2011-09-01

    A simulated network protocol provides the capability of distributed simulation to a generic simulator. Through this, full coverage of management of data and service handling among separated simulators is achieved. The distributed simulation environment is much more conducive to handling simulation load balancing and hazard treatment than a standalone computer. According to the simulated network protocol, one simulator takes on the role of server and the other simulators take on the role of client, and client is controlled by server. The purpose of the simulated network protocol is to seamlessly connect multiple simulator instances into a single simulation environment. This paper presents the development of a simulated network (simNetwork) that provides the capability of distributed simulation to a generic simulator (GenSim), which is a software simulator of satellites that has been developed by the Korea Aerospace Research Institute since 2010, to use as a flight software! validation bench for future satellite development.

  16. DIVE: a scaleable network architecture for distributed virtual environments

    NASA Astrophysics Data System (ADS)

    Frécon, Emmanuel; Stenius, Mårten

    1998-09-01

    We introduce the network software architecture of the distributed interactive virtual environment platform. The platform is designed to scale with a large number of simultaneous participants, while ensuring maximum interaction at each site. Scalability is achieved by making extensive use of multicast techniques and by partitioning the virtual space into smaller regions. We also present an application-level backbone that can connect islands of multicast-aware networks together.

  17. A Scalable Distribution Network Risk Evaluation Framework via Symbolic Dynamics

    PubMed Central

    Yuan, Kai; Liu, Jian; Liu, Kaipei; Tan, Tianyuan

    2015-01-01

    Background Evaluations of electric power distribution network risks must address the problems of incomplete information and changing dynamics. A risk evaluation framework should be adaptable to a specific situation and an evolving understanding of risk. Methods This study investigates the use of symbolic dynamics to abstract raw data. After introducing symbolic dynamics operators, Kolmogorov-Sinai entropy and Kullback-Leibler relative entropy are used to quantitatively evaluate relationships between risk sub-factors and main factors. For layered risk indicators, where the factors are categorized into four main factors – device, structure, load and special operation – a merging algorithm using operators to calculate the risk factors is discussed. Finally, an example from the Sanya Power Company is given to demonstrate the feasibility of the proposed method. Conclusion Distribution networks are exposed and can be affected by many things. The topology and the operating mode of a distribution network are dynamic, so the faults and their consequences are probabilistic. PMID:25789859

  18. [Distribution and taxonomy of Pyrgophorus platyrachis (Caenogastropoda: Hydrobiidae) in the Sistema de Maracaibo, Venezuela].

    PubMed

    Nava, Mario; Severeyn, Héctor; Machado, Nakary

    2011-09-01

    The presence of a microgastropod identified as Potamopyrgus sp. was detected previously in the Maracaibo System; nevertheless, a detailed morphological analysis identified this snail in other genera. The objective of this work is to update the distribution and taxonomy of Pyrgophorus platyrachis in the Maracaibo System, Venezuela in samples obtained between 2001 and 2009. The presence of hundreds of individuals of P. platyrachis were observed in the estuary, indeed in the localities of the Gran Eneal lagoon (4 111 snails), Peonías lagoon (229 snails), Punta Capitán Chico (758 snails), San Francisco (2 517 snails), Curarire (240 snails), Apon River mouth (173 snails), Ojeda City (240 snails), Bachaquero (128 snails) and Tomoporo de Agua (385 snails). We performed a taxonomical analysis, and emphasized in ecological aspects, such as the distribution of the species and habitat features, as near vegetation and type of associated sediment. We found three morphotypes of the species, one smooth, another with spiral striations and the other with spines. Smooth morphotype was exclusive of the Gran Eneal lagoon, Peonías lagoon, Punta Capitan Chico and Apon River mouth localities, whereas the other two morphotypes were found together in the remaining localities. According to our detailed anatomical and taxonomical analysis we propose a synonymy between P. platyrachis and the other species described like Pyrgophorus parvulus and Pyrgophorus spinosus.

  19. Evolution of the statistical distribution in a topological defect network

    NASA Astrophysics Data System (ADS)

    Xue, Fei; Wang, Xueyun; Socolenco, Ion; Gu, Yijia; Chen, Long-Qing; Cheong, Sang-Wook

    2015-11-01

    The complex networks of numerous topological defects in hexagonal manganites are highly relevant to vastly different phenomena from the birth of our cosmos to superfluidity transition. The topological defects in hexagonal manganites form two types of domain networks: type-I without and type-II with electric self-poling. A combined phase-field simulations and experimental study shows that the frequencies of domains with N-sides, i.e. of N-gons, in a type-I network are fitted by a lognormal distribution, whereas those in type-II display a scale-free power-law distribution with exponent ∼2. A preferential attachment process that N-gons with a larger N have higher probability of coalescence is responsible for the emergence of the scale-free networks. Since the domain networks can be observed, analyzed, and manipulated at room temperature, hexagonal manganites provide a unique opportunity to explore how the statistical distribution of a topological defect network evolves with an external electric field.

  20. Experimental and computational studies of fatty acid distribution networks.

    PubMed

    Liu, Yong; Buendía-Rodríguez, Germán; Peñuelas-Rívas, Claudia Giovanna; Tan, Zhiliang; Rívas-Guevara, María; Tenorio-Borroto, Esvieta; Munteanu, Cristian R; Pazos, Alejandro; González-Díaz, Humberto

    2015-11-01

    Unbalanced uptake of Omega 6/Omega 3 (ω-6/ω-3) ratios could increase chronic disease occurrences, such as inflammation, atherosclerosis, or tumor proliferation, and methylation methods for measuring the ruminal microbiome fatty acid (FA) composition/distribution play a vital role in discovering the contribution of food components to ruminant products (e.g., meat and milk) when pursuing a healthy diet. Hansch's models based on Linear Free Energy Relationships (LFERs) using physicochemical parameters, such as partition coefficients, molar refractivity, and polarizability, as input variables (Vk) are advocated. In this work, a new combined experimental and theoretical strategy was proposed to study the effect of ω-6/ω-3 ratios, FA chemical structure, and other factors over FA distribution networks in the ruminal microbiome. In step 1, experiments were carried out to measure long chain fatty acid (LCFA) profiles in the rumen microbiome (bacterial and protozoan), and volatile fatty acids (VFAs) in fermentation media. In step 2, the proportions and physicochemical parameter values of LCFAs and VFAs were calculated under different boundary conditions (cj) like c1 = acid and/or base methylation treatments, c2 = with/without fermentation, c3 = FA distribution phase (media, bacterial, or protozoan microbiome), etc. In step 3, Perturbation Theory (PT) and LFER ideas were combined to develop a PT-LFER model of a FA distribution network using physicochemical parameters (V(k)), the corresponding Box-Jenkins (ΔV(kj)) and PT operators (ΔΔV(kj)) in statistical analysis. The best PT-LFER model found predicted the effects of perturbations over the FA distribution network with sensitivity, specificity, and accuracy > 80% for 407 655 cases in training + external validation series. In step 4, alternative PT-LFER and PT-NLFER models were tested for training Linear and Non-Linear Artificial Neural Networks (ANNs). PT-NLFER models based on ANNs presented better performance but are

  1. Multiplexed Signal Distribution Using Fiber Network For Radar Applications

    NASA Astrophysics Data System (ADS)

    Meena, D.; Prakasam, L. G. M.; Pandey, D. C.; Shivaleela, E. S.; Srinivas, T.

    2011-10-01

    Most of the modern Active phased Array Radars consist of multiple receive modules in an Antenna array. This demands the distribution of various Local Oscillator Signals (LOs) for the down conversion of received signals to the Intermediate Frequency (IF) band signals. This is normally achieved through Radio Frequency (RF) cables with Complex distribution networks which adds additional weight to the Arrays. Similarly these kinds of receivers require Control/Clock signals which are digital in nature, for the synchronization of all receive modules of the radar system which are also distributed through electrical cables. In addition some of the control messages (Digital in nature) are distributed through Optical interfaces. During Transmit operation, the RF transmit Signal is also distributed through the same receiver modules which will in turn distribute to all the elements of the Array which require RF cables which are bulky in nature. So it is very essential to have a multiplexed Signal distribution scheme through the existing Optical Interface for distribution of these signals which are RF and Digital in nature. This paper discusses about various distribution schemes for the realization in detail. We propose a distribution network architecture where existing fibers can be further extended for the distribution of other types of signals also. In addition, it also briefs about a comparative analysis done on these schemes by considering the complexity and space constraint factors. Thus we bring out an optimum scheme which will lead to the reduction in both hardware complexity and weight of the array systems. In addition, being an Optical network it is free from Electromagnetic interference which is a crucial requirement in an array environment.

  2. Universal scaling of optimal current distribution in transportation networks.

    PubMed

    Simini, Filippo; Rinaldo, Andrea; Maritan, Amos

    2009-04-01

    Transportation networks are inevitably selected with reference to their global cost which depends on the strengths and the distribution of the embedded currents. We prove that optimal current distributions for a uniformly injected d -dimensional network exhibit robust scale-invariance properties, independently of the particular cost function considered, as long as it is convex. We find that, in the limit of large currents, the distribution decays as a power law with an exponent equal to (2d-1)/(d-1). The current distribution can be exactly calculated in d=2 for all values of the current. Numerical simulations further suggest that the scaling properties remain unchanged for both random injections and by randomizing the convex cost functions. PMID:19518304

  3. Universal scaling of optimal current distribution in transportation networks.

    PubMed

    Simini, Filippo; Rinaldo, Andrea; Maritan, Amos

    2009-04-01

    Transportation networks are inevitably selected with reference to their global cost which depends on the strengths and the distribution of the embedded currents. We prove that optimal current distributions for a uniformly injected d -dimensional network exhibit robust scale-invariance properties, independently of the particular cost function considered, as long as it is convex. We find that, in the limit of large currents, the distribution decays as a power law with an exponent equal to (2d-1)/(d-1). The current distribution can be exactly calculated in d=2 for all values of the current. Numerical simulations further suggest that the scaling properties remain unchanged for both random injections and by randomizing the convex cost functions.

  4. EDONIO: Extended distributed object network I/O library

    SciTech Connect

    D`Azevedo, E.F.; Romine, C.H.

    1995-03-01

    This report describes EDONIO (Extended Distributed Object Network I/O), an enhanced version of DONIO (Distributed Object Network I/O Library) optimized for the Intel Paragon Systems using the new M-ASYNC access mode. DONIO provided fast file I/O capabilities in the Intel iPSC/860 and Paragon distributed memory parallel environments by caching a copy of the entire file in memory distributed across all processors. EDONIO is more memory efficient by caching only a subset of the disk file at a time. DONIO was restricted by the high memory requirements and use of 32-bit integer indexing to handle files no larger than 2 Gigabytes. EDONIO overcomes this barrier by using the extended integer library routines provided by Intel`s NX operating system. For certain applications, EDONIO may show a ten-fold improvement in performance over the native NX I/O routines.

  5. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

    PubMed

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA.

  6. Distribution feeder loss computation by artificial neural network

    SciTech Connect

    Kau, S.W.; Cho, M.Y.

    1995-12-31

    This paper proposes an artificial neural network (ANN) based feeder loss calculation model for distribution system analysis. In this paper, the functional-link network model is examined to form the artificial neural network architecture to derive the various loss calculation models for feeders with different configuration. Such artificial neural network is a feedforward network that uses standard back-propagation algorithm to adjust weights on the connection path between any two processing elements (PEs). Feeder daily load curve on each season are derived by field test data. Three-phase load flow program is executed to create the training sets with exact loss calculation results. A sensitivity analysis is executed to determine the key factors included power factor, feeder loading, primary conductors, secondary conductors, and transformer capacity as the variables for components located at input layer. By artificial neural network with the pattern recognition ability, this study has developed seasonal and yearly loss calculation models for overhead and underground feeder configuration. Two practical feeders with both overhead and underground configuration in Taiwan Power Company (TPC or Taipower) distribution system are selected for computer simulation to demonstrate the effectiveness and accuracy of the proposed models. As comparing with models derived by the conventional regression technique, results indicate that the proposed models provide more efficient tool to District engineer for feeder loss calculation.

  7. Distributed wireless quantum communication networks with partially entangled pairs

    NASA Astrophysics Data System (ADS)

    Yu, Xu-Tao; Zhang, Zai-Chen; Xu, Jin

    2014-01-01

    Wireless quantum communication networks transfer quantum state by teleportation. Existing research focuses on maximal entangled pairs. In this paper, we analyse the distributed wireless quantum communication networks with partially entangled pairs. A quantum routing scheme with multi-hop teleportation is proposed. With the proposed scheme, is not necessary for the quantum path to be consistent with the classical path. The quantum path and its associated classical path are established in a distributed way. Direct multi-hop teleportation is conducted on the selected path to transfer a quantum state from the source to the destination. Based on the feature of multi-hop teleportation using partially entangled pairs, if the node number of the quantum path is even, the destination node will add another teleportation at itself. We simulated the performance of distributed wireless quantum communication networks with a partially entangled state. The probability of transferring the quantum state successfully is statistically analyzed. Our work shows that multi-hop teleportation on distributed wireless quantum networks with partially entangled pairs is feasible.

  8. Exploration of Heterogeneity in Distributed Research Network Drug Safety Analyses

    ERIC Educational Resources Information Center

    Hansen, Richard A.; Zeng, Peng; Ryan, Patrick; Gao, Juan; Sonawane, Kalyani; Teeter, Benjamin; Westrich, Kimberly; Dubois, Robert W.

    2014-01-01

    Distributed data networks representing large diverse populations are an expanding focus of drug safety research. However, interpreting results is difficult when treatment effect estimates vary across datasets (i.e., heterogeneity). In a previous study, risk estimates were generated for selected drugs and potential adverse outcomes. Analyses were…

  9. 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.

  10. Social Networks and Performance in Distributed Learning Communities

    ERIC Educational Resources Information Center

    Cadima, Rita; Ojeda, Jordi; Monguet, Josep M.

    2012-01-01

    Social networks play an essential role in learning environments as a key channel for knowledge sharing and students' support. In distributed learning communities, knowledge sharing does not occur as spontaneously as when a working group shares the same physical space; knowledge sharing depends even more on student informal connections. In this…

  11. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    SciTech Connect

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinate with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.

  12. Distributed Coordinated Control of Large-Scale Nonlinear Networks

    DOE PAGES

    Kundu, Soumya; Anghel, Marian

    2015-11-08

    We provide a distributed coordinated approach to the stability analysis and control design of largescale nonlinear dynamical systems by using a vector Lyapunov functions approach. In this formulation the large-scale system is decomposed into a network of interacting subsystems and the stability of the system is analyzed through a comparison system. However finding such comparison system is not trivial. In this work, we propose a sum-of-squares based completely decentralized approach for computing the comparison systems for networks of nonlinear systems. Moreover, based on the comparison systems, we introduce a distributed optimal control strategy in which the individual subsystems (agents) coordinatemore » with their immediate neighbors to design local control policies that can exponentially stabilize the full system under initial disturbances.We illustrate the control algorithm on a network of interacting Van der Pol systems.« less

  13. Reliable distribution networks design with nonlinear fortification function

    NASA Astrophysics Data System (ADS)

    Li, Qingwei; Savachkin, Alex

    2016-03-01

    Distribution networks have been facing an increased exposure to the risk of unpredicted disruptions causing significant economic losses. The current literature features a limited number of studies considering fortification of network facilities. In this paper, we develop a reliable uncapacitated fixed-charge location model with fortification to support the design of distribution networks. The model considers heterogeneous facility failure probabilities, one layer of supplier backup, and facility fortification within a finite budget. Facility reliability improvement is modelled as a nonlinear function of fortification investment. The problem is formulated as a nonlinear mixed integer programming model proven to be ?-hard. A Lagrangian relaxation-based heuristic algorithm is developed and its computational efficiency for solving large-scale problems is demonstrated.

  14. Distributed Detection of Wormhole Attacks in Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    de Graaf, Rennie; Hegazy, Islam; Horton, Jeffrey; Safavi-Naini, Reihaneh

    Sensors in a wireless sensor network depend on their neighbours to route their messages. Yet, routing protocols in wireless sensor network are vulnerable to different types of attacks. In this paper, we consider the wormhole attack in which the adversary diverts traffic from one part of the network to another part by introducing a low cost tunnel between the two parts. We introduce a distributed intrusion detection system that monitors the communication in the network and propose a criterion for the placement of intrusion detection nodes. The intrusion detection system searches for violations of that criterion to detect wormholes of length above a certain minimum value. We evaluate the effectiveness of our system in a simulated environment. The experiments show that our system can detect 100% of the wormholes that are beyond the communication range of the intrusion detection nodes. Finally, we discuss our results and show directions for future work.

  15. Joint physical and numerical modeling of water distribution networks.

    SciTech Connect

    Zimmerman, Adam; O'Hern, Timothy John; Orear, Leslie Jr.; Kajder, Karen C.; Webb, Stephen Walter; Cappelle, Malynda A.; Khalsa, Siri Sahib; Wright, Jerome L.; Sun, Amy Cha-Tien; Chwirka, J. Benjamin; Hartenberger, Joel David; McKenna, Sean Andrew; van Bloemen Waanders, Bart Gustaaf; McGrath, Lucas K.; Ho, Clifford Kuofei

    2009-01-01

    This report summarizes the experimental and modeling effort undertaken to understand solute mixing in a water distribution network conducted during the last year of a 3-year project. The experimental effort involves measurement of extent of mixing within different configurations of pipe networks, measurement of dynamic mixing in a single mixing tank, and measurement of dynamic solute mixing in a combined network-tank configuration. High resolution analysis of turbulence mixing is carried out via high speed photography as well as 3D finite-volume based Large Eddy Simulation turbulence models. Macroscopic mixing rules based on flow momentum balance are also explored, and in some cases, implemented in EPANET. A new version EPANET code was developed to yield better mixing predictions. The impact of a storage tank on pipe mixing in a combined pipe-tank network during diurnal fill-and-drain cycles is assessed. Preliminary comparison between dynamic pilot data and EPANET-BAM is also reported.

  16. Dense distributed processing in a hindlimb scratch motor network.

    PubMed

    Guzulaitis, Robertas; Alaburda, Aidas; Hounsgaard, Jorn

    2014-08-01

    In reduced preparations, hindlimb movements can be generated by a minimal network of neurons in the limb innervating spinal segments. The network of neurons that generates real movements is less well delineated. In an ex vivo carapace-spinal cord preparation from adult turtles (Trachemys scripta elegans), we show that ventral horn interneurons in mid-thoracic spinal segments are functionally integrated in the hindlimb scratch network. First, mid-thoracic interneurons receive intense synaptic input during scratching and behave like neurons in the hindlimb enlargement. Second, some mid-thoracic interneurons activated during scratching project descending axons toward the hindlimb enlargement. Third, elimination of mid-thoracic segments leads to a weakening of scratch rhythmicity. We conclude that densely innervated interneurons in mid-thoracic segments contribute to hindlimb scratching and may be part of a distributed motor network that secures motor coherence.

  17. 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.

  18. Distributed Computing and MEMS Accelerometers: The Quake Catcher Network

    NASA Astrophysics Data System (ADS)

    Lawrence, J. F.; Cochran, E. S.; Christensen, C.; Jakka, R. S.

    2008-12-01

    Recent advances in distributed computing provide exciting opportunities for seismic data collection. We are in the early stages of implementing a high density, low cost strong-motion network for rapid response and early warning by placing accelerometers in schools, homes, offices, government buildings, fire houses and more. The Quake Catcher Network (QCN) employs existing networked laptops and desktops to form a dense, distributed computing seismic network. Costs for this network are minimal because the QCN uses 1) strong motion sensors (accelerometers) already internal to many laptops and 2) low-cost universal serial bus (USB) accelerometers for use with desktops. The Berkeley Open Infrastructure for Network Computing (BOINC!) provides a free, proven paradigm for involving the public in large-scale computational research projects. The QCN leverages public participation to fully implement the seismic network. As such engaging the public to participate in seismic data collection is not only an integral part of the project, but an added value to the QCN. The software provides the client-user with a screen-saver displaying seismic data recorded on their laptop or recently detected earthquakes. Furthermore, this project installs sensors in K-12 classrooms as an educational tool for teaching science. Through a variety of interactive experiments students can learn about earthquakes and the hazards earthquakes pose. In the first six months of limited release of the QCN software, we successfully received triggers and waveforms from laptops near the M 4.7 April 25, 2008 earthquake in Reno, Nevada and the M 5.4 July 29, 2008 earthquake in Chino, California (as well as a few 3.6 and higher events). This fall we continued to expand the network further by installing seismometers in K-12 schools, museums, and government buildings in the greater Los Angeles basin and the San Francisco Bay Area. By summer 2009 we expect to have 1000 USB sensors deployed in California, in addition

  19. Distributed fault detection and isolation resilient to network model uncertainties.

    PubMed

    Teixeira, Andre; Shames, Iman; Sandberg, Henrik; Johansson, Karl H

    2014-11-01

    The ability to maintain state awareness in the face of unexpected and unmodeled errors and threats is a defining feature of a resilient control system. Therefore, in this paper, we study the problem of distributed fault detection and isolation (FDI) in large networked systems with uncertain system models. The linear networked system is composed of interconnected subsystems and may be represented as a graph. The subsystems are represented by nodes, while the edges correspond to the interconnections between subsystems. Considering faults that may occur on the interconnections and subsystems, as our first contribution, we propose a distributed scheme to jointly detect and isolate faults occurring in nodes and edges of the system. As our second contribution, we analyze the behavior of the proposed scheme under model uncertainties caused by the addition or removal of edges. Additionally, we propose a novel distributed FDI scheme based on local models and measurements that is resilient to changes outside of the local subsystem and achieves FDI. Our third contribution addresses the complexity reduction of the distributed FDI method, by characterizing the minimum amount of model information and measurements needed to achieve FDI and by reducing the number of monitoring nodes. The proposed methods can be fused to design a scalable and resilient distributed FDI architecture that achieves local FDI despite unknown changes outside the local subsystem. The proposed approach is illustrated by numerical experiments on the IEEE 118-bus power network benchmark.

  20. Cluster-based distributed face tracking in camera networks.

    PubMed

    Yoder, Josiah; Medeiros, Henry; Park, Johnny; Kak, Avinash C

    2010-10-01

    In this paper, we present a distributed multicamera face tracking system suitable for large wired camera networks. Unlike previous multicamera face tracking systems, our system does not require a central server to coordinate the entire tracking effort. Instead, an efficient camera clustering protocol is used to dynamically form groups of cameras for in-network tracking of individual faces. The clustering protocol includes cluster propagation mechanisms that allow the computational load of face tracking to be transferred to different cameras as the target objects move. Furthermore, the dynamic election of cluster leaders provides robustness against system failures. Our experimental results show that our cluster-based distributed face tracker is capable of accurately tracking multiple faces in real-time. The overall performance of the distributed system is comparable to that of a centralized face tracker, while presenting the advantages of scalability and robustness. PMID:20423804

  1. A distributed data base management system. [for Deep Space Network

    NASA Technical Reports Server (NTRS)

    Bryan, A. I.

    1975-01-01

    Major system design features of a distributed data management system for the NASA Deep Space Network (DSN) designed for continuous two-way deep space communications are described. The reasons for which the distributed data base utilizing third-generation minicomputers is selected as the optimum approach for the DSN are threefold: (1) with a distributed master data base, valid data is available in real-time to support DSN management activities at each location; (2) data base integrity is the responsibility of local management; and (3) the data acquisition/distribution and processing power of a third-generation computer enables the computer to function successfully as a data handler or as an on-line process controller. The concept of the distributed data base is discussed along with the software, data base integrity, and hardware used. The data analysis/update constraint is examined.

  2. Distributed Relay Selection for MIMO-SDM Cooperative Networks

    NASA Astrophysics Data System (ADS)

    Tran, Xuan Nam; Nguyen, Vinh Hanh; Bui, Thanh Tam; Dinh, The Cuong; Karasawa, Yoshio

    In this paper, we consider an amplify-and-forward cooperative wireless network in which network nodes use multiple input multiple output (MIMO) spatial division multiplexing (SDM) to communicate with one another. We examine the problem of distributed cooperative relay selection and signal combining at the destination. First, we propose three distributed relay selection algorithms based on the maximum channel gains, the maximum harmonic mean of the channel gains, and the minimum mean squared error (MSE) of the signal estimation. Second, we propose a minimum mean square error (MMSE) signal combining scheme which jointly serves as the optimal signal combiner and interference canceler. It is shown that the MSE selection together with the MMSE combining achieves the maximal diversity gain. We also show that in MIMO-SDM cooperative networks increasing the number of candidate nodes does not help to improve the BER performance as opposed to the cooperative networks where each node is equipped with only single antenna. A practical approach to implementation of the combiner based on the current wireless access network protocols will also be presented.

  3. Tracking and activity recognition through consensus in distributed camera networks.

    PubMed

    Song, Bi; Kamal, Ahmed T; Soto, Cristian; Ding, Chong; Farrell, Jay A; Roy-Chowdhury, Amit K

    2010-10-01

    Camera networks are being deployed for various applications like security and surveillance, disaster response and environmental modeling. However, there is little automated processing of the data. Moreover, most methods for multicamera analysis are centralized schemes that require the data to be present at a central server. In many applications, this is prohibitively expensive, both technically and economically. In this paper, we investigate distributed scene analysis algorithms by leveraging upon concepts of consensus that have been studied in the context of multiagent systems, but have had little applications in video analysis. Each camera estimates certain parameters based upon its own sensed data which is then shared locally with the neighboring cameras in an iterative fashion, and a final estimate is arrived at in the network using consensus algorithms. We specifically focus on two basic problems-tracking and activity recognition. For multitarget tracking in a distributed camera network, we show how the Kalman-Consensus algorithm can be adapted to take into account the directional nature of video sensors and the network topology. For the activity recognition problem, we derive a probabilistic consensus scheme that combines the similarity scores of neighboring cameras to come up with a probability for each action at the network level. Thorough experimental results are shown on real data along with a quantitative analysis.

  4. Towards the distribution network of time and frequency

    NASA Astrophysics Data System (ADS)

    Lipiński, M.; Krehlik, P.; Śliwczyński, Ł.; Buczek, Ł.; Kołodziej, J.; Nawrocki, J.; Nogaś, P.; Dunst, P.; Lemański, D.; Czubla, A.; Pieczerak, J.; Adamowicz, W.; Pawszak, T.; Igalson, J.; Binczewski, A.; Bogacki, W.; Ostapowicz, P.; Stroiński, M.; Turza, K.

    2014-05-01

    In the paper the genesis, current stage and perspectives of the OPTIME project are described. The main goal of the project is to demonstrate that the newdeveloped at AGH technology of fiber optic transfer of the atomic clocks reference signals is ready to be used in building the domestic Time and Frequency distribution network. In the first part we summarize the two-year continuous operation of 420 kmlong link connecting the Laboratory of Time and Frequency at Central Office of Measures GUM in Warsaw and Time Service Laboratory at Astrogeodynamic Obserwatory AOS in Borowiec near Poznan. For the first time, we are reporting the two year comparison of UTC(PL) and UTC(AOS) atomic timescales with this link, and we refer it to the results of comparisons performed by GPS-based methods. We also address some practical aspects of maintaining time and frequency dissemination over fiber optical network. In the second part of the paper the concept of the general architecture of the distribution network with two Reference Time and Frequency Laboratories and local repositories is proposed. Moreover the brief project of the second branch connecting repositories in Poznan Polish Supercomputing and Networking Center and Torun Nicolaus Copernicus University with the first end-users in Torun such as National Laboratory of Atomic, Molecular and Optical Physics and Nicolaus Copernicus Astronomical Center is described. In the final part the perspective of developing the network both in the domestic range as far as extention with the international connections possibilities are presented.

  5. Distributed policy based access to networked heterogeneous ISR data sources

    NASA Astrophysics Data System (ADS)

    Bent, G.; Vyvyan, D.; Wood, David; Zerfos, Petros; Calo, Seraphin

    2010-04-01

    Within a coalition environment, ad hoc Communities of Interest (CoI's) come together, perhaps for only a short time, with different sensors, sensor platforms, data fusion elements, and networks to conduct a task (or set of tasks) with different coalition members taking different roles. In such a coalition, each organization will have its own inherent restrictions on how it will interact with the others. These are usually stated as a set of policies, including security and privacy policies. The capability that we want to enable for a coalition operation is to provide access to information from any coalition partner in conformance with the policies of all. One of the challenges in supporting such ad-hoc coalition operations is that of providing efficient access to distributed sources of data, where the applications requiring the data do not have knowledge of the location of the data within the network. To address this challenge the International Technology Alliance (ITA) program has been developing the concept of a Dynamic Distributed Federated Database (DDFD), also know as a Gaian Database. This type of database provides a means for accessing data across a network of distributed heterogeneous data sources where access to the information is controlled by a mixture of local and global policies. We describe how a network of disparate ISR elements can be expressed as a DDFD and how this approach enables sensor and other information sources to be discovered autonomously or semi-autonomously and/or combined, fused formally defined local and global policies.

  6. Distributed networks enable advances in US space weather operations

    NASA Astrophysics Data System (ADS)

    Tobiska, W. Kent; Bouwer, S. Dave

    2011-06-01

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

  7. Hadoop neural network for parallel and distributed feature selection.

    PubMed

    Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

    2016-06-01

    In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop. PMID:26403824

  8. Hadoop neural network for parallel and distributed feature selection.

    PubMed

    Hodge, Victoria J; O'Keefe, Simon; Austin, Jim

    2016-06-01

    In this paper, we introduce a theoretical basis for a Hadoop-based neural network for parallel and distributed feature selection in Big Data sets. It is underpinned by an associative memory (binary) neural network which is highly amenable to parallel and distributed processing and fits with the Hadoop paradigm. There are many feature selectors described in the literature which all have various strengths and weaknesses. We present the implementation details of five feature selection algorithms constructed using our artificial neural network framework embedded in Hadoop YARN. Hadoop allows parallel and distributed processing. Each feature selector can be divided into subtasks and the subtasks can then be processed in parallel. Multiple feature selectors can also be processed simultaneously (in parallel) allowing multiple feature selectors to be compared. We identify commonalities among the five features selectors. All can be processed in the framework using a single representation and the overall processing can also be greatly reduced by only processing the common aspects of the feature selectors once and propagating these aspects across all five feature selectors as necessary. This allows the best feature selector and the actual features to select to be identified for large and high dimensional data sets through exploiting the efficiency and flexibility of embedding the binary associative-memory neural network in Hadoop.

  9. Efficient server selection system for widely distributed multiserver networks

    NASA Astrophysics Data System (ADS)

    Lee, Hyun-pyo; Park, Sung-sik; Lee, Kyoon-Ha

    2001-07-01

    In order to providing more improved quality of Internet service, the access speed to a subscriber's network and a server which is the Internet access device was rapidly enhanced by traffic distribution and installation of high-performance server. But the Internet access quality and the content for a speed were remained out of satisfaction. With such a hazard, an extended node at Internet access device has a limitation for coping with growing network traffic, and the root cause is located in the Middle-mile node between a CP (Content Provider) server and a user node. For such a problem, this paper proposes a new method to select a effective server to a client as minimizing the number of node between the server and the client while keeping the load balance among servers which is clustered by the client's location on the physically distributed multi-site environments. The proposed method use a NSP (Network Status Prober) and a contents server manager so as to get a status of each servers and distributed network, a new architecture will be shown for the server selecting algorithm and the implementation for the algorithm. And also, this paper shows the parameters selecting a best service providing server for client and that the grantor will be confirmed by the experiment over the proposed architectures.

  10. Physical Modeling of Scaled Water Distribution System Networks.

    SciTech Connect

    O'Hern, Timothy J.; Hammond, Glenn Edward; Orear, Leslie ,; van Bloemen Waanders, Bart G.; Paul Molina; Ross Johnson

    2005-10-01

    Threats to water distribution systems include release of contaminants and Denial of Service (DoS) attacks. A better understanding, and validated computational models, of the flow in water distribution systems would enable determination of sensor placement in real water distribution networks, allow source identification, and guide mitigation/minimization efforts. Validation data are needed to evaluate numerical models of network operations. Some data can be acquired in real-world tests, but these are limited by 1) unknown demand, 2) lack of repeatability, 3) too many sources of uncertainty (demand, friction factors, etc.), and 4) expense. In addition, real-world tests have limited numbers of network access points. A scale-model water distribution system was fabricated, and validation data were acquired over a range of flow (demand) conditions. Standard operating variables included system layout, demand at various nodes in the system, and pressure drop across various pipe sections. In addition, the location of contaminant (salt or dye) introduction was varied. Measurements of pressure, flowrate, and concentration at a large number of points, and overall visualization of dye transport through the flow network were completed. Scale-up issues that that were incorporated in the experiment design include Reynolds number, pressure drop across nodes, and pipe friction and roughness. The scale was chosen to be 20:1, so the 10 inch main was modeled with a 0.5 inch pipe in the physical model. Controlled validation tracer tests were run to provide validation to flow and transport models, especially of the degree of mixing at pipe junctions. Results of the pipe mixing experiments showed large deviations from predicted behavior and these have a large impact on standard network operations models.3

  11. Fast Distributed Dynamics of Semantic Networks via Social Media

    PubMed Central

    Carrillo, Facundo; Cecchi, Guillermo A.; Sigman, Mariano; Fernández Slezak, Diego

    2015-01-01

    We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network. PMID:26074953

  12. Fast Distributed Dynamics of Semantic Networks via Social Media.

    PubMed

    Carrillo, Facundo; Cecchi, Guillermo A; Sigman, Mariano; Slezak, Diego Fernández

    2015-01-01

    We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network.

  13. Fast Distributed Dynamics of Semantic Networks via Social Media.

    PubMed

    Carrillo, Facundo; Cecchi, Guillermo A; Sigman, Mariano; Slezak, Diego Fernández

    2015-01-01

    We investigate the dynamics of semantic organization using social media, a collective expression of human thought. We propose a novel, time-dependent semantic similarity measure (TSS), based on the social network Twitter. We show that TSS is consistent with static measures of similarity but provides high temporal resolution for the identification of real-world events and induced changes in the distributed structure of semantic relationships across the entire lexicon. Using TSS, we measured the evolution of a concept and its movement along the semantic neighborhood, driven by specific news/events. Finally, we showed that particular events may trigger a temporary reorganization of elements in the semantic network. PMID:26074953

  14. Distributed dictionary learning for sparse representation in sensor networks.

    PubMed

    Liang, Junli; Zhang, Miaohua; Zeng, Xianyu; Yu, Guoyang

    2014-06-01

    This paper develops a distributed dictionary learning algorithm for sparse representation of the data distributed across nodes of sensor networks, where the sensitive or private data are stored or there is no fusion center or there exists a big data application. The main contributions of this paper are: 1) we decouple the combined dictionary atom update and nonzero coefficient revision procedure into two-stage operations to facilitate distributed computations, first updating the dictionary atom in terms of the eigenvalue decomposition of the sum of the residual (correlation) matrices across the nodes then implementing a local projection operation to obtain the related representation coefficients for each node; 2) we cast the aforementioned atom update problem as a set of decentralized optimization subproblems with consensus constraints. Then, we simplify the multiplier update for the symmetry undirected graphs in sensor networks and minimize the separable subproblems to attain the consistent estimates iteratively; and 3) dictionary atoms are typically constrained to be of unit norm in order to avoid the scaling ambiguity. We efficiently solve the resultant hidden convex subproblems by determining the optimal Lagrange multiplier. Some experiments are given to show that the proposed algorithm is an alternative distributed dictionary learning approach, and is suitable for the sensor network environment. PMID:24733009

  15. Distributed dictionary learning for sparse representation in sensor networks.

    PubMed

    Liang, Junli; Zhang, Miaohua; Zeng, Xianyu; Yu, Guoyang

    2014-06-01

    This paper develops a distributed dictionary learning algorithm for sparse representation of the data distributed across nodes of sensor networks, where the sensitive or private data are stored or there is no fusion center or there exists a big data application. The main contributions of this paper are: 1) we decouple the combined dictionary atom update and nonzero coefficient revision procedure into two-stage operations to facilitate distributed computations, first updating the dictionary atom in terms of the eigenvalue decomposition of the sum of the residual (correlation) matrices across the nodes then implementing a local projection operation to obtain the related representation coefficients for each node; 2) we cast the aforementioned atom update problem as a set of decentralized optimization subproblems with consensus constraints. Then, we simplify the multiplier update for the symmetry undirected graphs in sensor networks and minimize the separable subproblems to attain the consistent estimates iteratively; and 3) dictionary atoms are typically constrained to be of unit norm in order to avoid the scaling ambiguity. We efficiently solve the resultant hidden convex subproblems by determining the optimal Lagrange multiplier. Some experiments are given to show that the proposed algorithm is an alternative distributed dictionary learning approach, and is suitable for the sensor network environment.

  16. A Distributed Network Mobility Management Scheme for Hierarchical Mobile IPv6 Networks

    NASA Astrophysics Data System (ADS)

    Kawano, Keita; Kinoshita, Kazuhiko; Yamai, Nariyoshi

    Route optimization for network mobility is a key technique for providing a node in a mobile network (Mobile Network Node or MNN) with high quality broadband communications. Many schemes adding route optimization function to Network Mobility (NEMO) Basic Support protocol, the standardized network mobility management protocol from the IETF nemo working group, have already been proposed in recent years. One such scheme, a scheme using Hierarchical Mobile IPv6 (HMIPv6) aims to overcome micromobility management issues as well by applying a mechanism based on HMIPv6. The traditional scheme, however, suffers from a significant number of signaling messages as the number of MNNs and/or the number of their Correspondent Nodes (CNs) increase, because many messages notifying the MNNs' Home Agents (HAMNNs) and the CNs of the mobile network's movement are generated simultaneously each time the mobile network moves to the domain of another micromobility management router (Mobility Anchor Point or MAP). This paper proposes a scheme to overcome this problem. Our scheme reduces the number of signaling messages generated at the same time by managing the mobility of MNNs using multiple MAPs distributed within a network for load sharing. The results of simulation experiments show that our scheme works efficiently compared to the traditional scheme when a mobile network has many MNNs and/or these MNNs communicate with many CNs.

  17. S-curve networks and an approximate method for estimating degree distributions of complex networks

    NASA Astrophysics Data System (ADS)

    Guo, Jin-Li

    2010-12-01

    In the study of complex networks almost all theoretical models have the property of infinite growth, but the size of actual networks is finite. According to statistics from the China Internet IPv4 (Internet Protocol version 4) addresses, this paper proposes a forecasting model by using S curve (logistic curve). The growing trend of IPv4 addresses in China is forecasted. There are some reference values for optimizing the distribution of IPv4 address resource and the development of IPv6. Based on the laws of IPv4 growth, that is, the bulk growth and the finitely growing limit, it proposes a finite network model with a bulk growth. The model is said to be an S-curve network. Analysis demonstrates that the analytic method based on uniform distributions (i.e., Barabási-Albert method) is not suitable for the network. It develops an approximate method to predict the growth dynamics of the individual nodes, and uses this to calculate analytically the degree distribution and the scaling exponents. The analytical result agrees with the simulation well, obeying an approximately power-law form. This method can overcome a shortcoming of Barabási-Albert method commonly used in current network research.

  18. A precise clock distribution network for MRPC-based experiments

    NASA Astrophysics Data System (ADS)

    Wang, S.; Cao, P.; Shang, L.; An, Q.

    2016-06-01

    In high energy physics experiments, the MRPC (Multi-Gap Resistive Plate Chamber) detectors are widely used recently which can provide higher-resolution measurement for particle identification. However, the application of MRPC detectors leads to a series of challenges in electronics design with large number of front-end electronic channels, especially for distributing clock precisely. To deal with these challenges, this paper presents a universal scheme of clock transmission network for MRPC-based experiments with advantages of both precise clock distribution and global command synchronization. For precise clock distributing, the clock network is designed into a tree architecture with two stages: the first one has a point-to-multipoint long range bidirectional distribution with optical channels and the second one has a fan-out structure with copper link inside readout crates. To guarantee the precision of clock frequency or phase, the r-PTP (reduced Precision Time Protocol) and the DDMTD (digital Dual Mixer Time Difference) methods are used for frequency synthesis, phase measurement and adjustment, which is implemented by FPGA (Field Programmable Gate Array) in real-time. In addition, to synchronize global command execution, based upon this clock distribution network, synchronous signals are coded with clock for transmission. With technique of encoding/decoding and clock data recovery, signals such as global triggers or system control commands, can be distributed to all front-end channels synchronously, which greatly simplifies the system design. The experimental results show that both the clock jitter (RMS) and the clock skew can be less than 100 ps.

  19. Direct broadcast satellite receiver system with optical distribution network

    NASA Astrophysics Data System (ADS)

    Kemery, S. M.; Daryoush, A. S.; Herczfeld, P. R.

    1986-01-01

    With recent developments in fiber optic communications and optical distribution networks, short haul optical communications becomes an economical alternative to conventional cable TV systems. This paper presents a system design for a direct broadcast satellite receiver system with a fiber optic distribution network based on the reception of Ku-band signals from ANIK C2, a Canadian direct broadcast satellite. Such a system is proposed for the first time and can address small communities in remote areas. Theoretical power budget calculations predict that 37 subscribers can access 128 television channels using a 3 ft reflector dish antenna. To implement such a design, a number of components that are not commercially available are custom designed.

  20. Mapping distributed brain function and networks with diffuse optical tomography

    NASA Astrophysics Data System (ADS)

    Eggebrecht, Adam T.; Ferradal, Silvina L.; Robichaux-Viehoever, Amy; Hassanpour, Mahlega S.; Dehghani, Hamid; Snyder, Abraham Z.; Hershey, Tamara; Culver, Joseph P.

    2014-06-01

    Mapping of human brain function has revolutionized systems neuroscience. However, traditional functional neuroimaging by positron emission tomography or functional magnetic resonance imaging cannot be used when applications require portability, or are contraindicated because of ionizing radiation (positron emission tomography) or implanted metal (functional magnetic resonance imaging). Optical neuroimaging offers a non-invasive alternative that is radiation free and compatible with implanted metal and electronic devices (for example, pacemakers). However, optical imaging technology has heretofore lacked the combination of spatial resolution and wide field of view sufficient to map distributed brain functions. Here, we present a high-density diffuse optical tomography imaging array that can map higher-order, distributed brain function. The system was tested by imaging four hierarchical language tasks and multiple resting-state networks including the dorsal attention and default mode networks. Finally, we imaged brain function in patients with Parkinson's disease and implanted deep brain stimulators that preclude functional magnetic resonance imaging.

  1. Biometrics based novel key distribution solution for body sensor networks.

    PubMed

    Miao, Fen; Jiang, Lei; Li, Ye; Zhang, Yuan-Ting

    2009-01-01

    The security of wireless body sensor network (BSN) is very important to telemedicine and m-healthcare, and it still remains a critical challenge. This paper presents a novel key distribution solution which allows two sensors in one BSN to agree on a changeable cryptographic key. A previously published scheme, fuzzy vault, is firstly applied to secure the random cryptographic key generated from electrocardiographic (ECG) signals. Simulations based on ECG data from MIT PhysioBank database, produce a minimum half total error rate (HTER) of 0.65%, which demonstrates our key distribution solution is promising compared with previous method, with HTER of 4.26%. PMID:19964960

  2. Biometrics based novel key distribution solution for body sensor networks.

    PubMed

    Miao, Fen; Jiang, Lei; Li, Ye; Zhang, Yuan-Ting

    2009-01-01

    The security of wireless body sensor network (BSN) is very important to telemedicine and m-healthcare, and it still remains a critical challenge. This paper presents a novel key distribution solution which allows two sensors in one BSN to agree on a changeable cryptographic key. A previously published scheme, fuzzy vault, is firstly applied to secure the random cryptographic key generated from electrocardiographic (ECG) signals. Simulations based on ECG data from MIT PhysioBank database, produce a minimum half total error rate (HTER) of 0.65%, which demonstrates our key distribution solution is promising compared with previous method, with HTER of 4.26%.

  3. Distributed Signal Processing for Wireless EEG Sensor Networks.

    PubMed

    Bertrand, Alexander

    2015-11-01

    Inspired by ongoing evolutions in the field of wireless body area networks (WBANs), this tutorial paper presents a conceptual and exploratory study of wireless electroencephalography (EEG) sensor networks (WESNs), with an emphasis on distributed signal processing aspects. A WESN is conceived as a modular neuromonitoring platform for high-density EEG recordings, in which each node is equipped with an electrode array, a signal processing unit, and facilities for wireless communication. We first address the advantages of such a modular approach, and we explain how distributed signal processing algorithms make WESNs more power-efficient, in particular by avoiding data centralization. We provide an overview of distributed signal processing algorithms that are potentially applicable in WESNs, and for illustration purposes, we also provide a more detailed case study of a distributed eye blink artifact removal algorithm. Finally, we study the power efficiency of these distributed algorithms in comparison to their centralized counterparts in which all the raw sensor signals are centralized in a near-end or far-end fusion center.

  4. Automatic analysis of attack data from distributed honeypot network

    NASA Astrophysics Data System (ADS)

    Safarik, Jakub; Voznak, MIroslav; Rezac, Filip; Partila, Pavol; Tomala, Karel

    2013-05-01

    There are many ways of getting real data about malicious activity in a network. One of them relies on masquerading monitoring servers as a production one. These servers are called honeypots and data about attacks on them brings us valuable information about actual attacks and techniques used by hackers. The article describes distributed topology of honeypots, which was developed with a strong orientation on monitoring of IP telephony traffic. IP telephony servers can be easily exposed to various types of attacks, and without protection, this situation can lead to loss of money and other unpleasant consequences. Using a distributed topology with honeypots placed in different geological locations and networks provides more valuable and independent results. With automatic system of gathering information from all honeypots, it is possible to work with all information on one centralized point. Communication between honeypots and centralized data store use secure SSH tunnels and server communicates only with authorized honeypots. The centralized server also automatically analyses data from each honeypot. Results of this analysis and also other statistical data about malicious activity are simply accessible through a built-in web server. All statistical and analysis reports serve as information basis for an algorithm which classifies different types of used VoIP attacks. The web interface then brings a tool for quick comparison and evaluation of actual attacks in all monitored networks. The article describes both, the honeypots nodes in distributed architecture, which monitor suspicious activity, and also methods and algorithms used on the server side for analysis of gathered data.

  5. Distributed communications and control network for robotic mining

    NASA Technical Reports Server (NTRS)

    Schiffbauer, William H.

    1989-01-01

    The application of robotics to coal mining machines is one approach pursued to increase productivity while providing enhanced safety for the coal miner. Toward that end, a network composed of microcontrollers, computers, expert systems, real time operating systems, and a variety of program languages are being integrated that will act as the backbone for intelligent machine operation. Actual mining machines, including a few customized ones, have been given telerobotic semiautonomous capabilities by applying the described network. Control devices, intelligent sensors and computers onboard these machines are showing promise of achieving improved mining productivity and safety benefits. Current research using these machines involves navigation, multiple machine interaction, machine diagnostics, mineral detection, and graphical machine representation. Guidance sensors and systems employed include: sonar, laser rangers, gyroscopes, magnetometers, clinometers, and accelerometers. Information on the network of hardware/software and its implementation on mining machines are presented. Anticipated coal production operations using the network are discussed. A parallelism is also drawn between the direction of present day underground coal mining research to how the lunar soil (regolith) may be mined. A conceptual lunar mining operation that employs a distributed communication and control network is detailed.

  6. Biological Instability in a Chlorinated Drinking Water Distribution Network

    PubMed Central

    Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

    2014-01-01

    The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×103 cells mL−1 to 4.66×105 cells mL−1 in the network. While this parameter did not exceed 2.1×104 cells mL−1 in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×105 cells mL−1. This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability. PMID:24796923

  7. Biological instability in a chlorinated drinking water distribution network.

    PubMed

    Nescerecka, Alina; Rubulis, Janis; Vital, Marius; Juhna, Talis; Hammes, Frederik

    2014-01-01

    The purpose of a drinking water distribution system is to deliver drinking water to the consumer, preferably with the same quality as when it left the treatment plant. In this context, the maintenance of good microbiological quality is often referred to as biological stability, and the addition of sufficient chlorine residuals is regarded as one way to achieve this. The full-scale drinking water distribution system of Riga (Latvia) was investigated with respect to biological stability in chlorinated drinking water. Flow cytometric (FCM) intact cell concentrations, intracellular adenosine tri-phosphate (ATP), heterotrophic plate counts and residual chlorine measurements were performed to evaluate the drinking water quality and stability at 49 sampling points throughout the distribution network. Cell viability methods were compared and the importance of extracellular ATP measurements was examined as well. FCM intact cell concentrations varied from 5×10(3) cells mL(-1) to 4.66×10(5) cells mL(-1) in the network. While this parameter did not exceed 2.1×10(4) cells mL(-1) in the effluent from any water treatment plant, 50% of all the network samples contained more than 1.06×10(5) cells mL(-1). This indisputably demonstrates biological instability in this particular drinking water distribution system, which was ascribed to a loss of disinfectant residuals and concomitant bacterial growth. The study highlights the potential of using cultivation-independent methods for the assessment of chlorinated water samples. In addition, it underlines the complexity of full-scale drinking water distribution systems, and the resulting challenges to establish the causes of biological instability.

  8. Distributed game-theoretic topology control in cognitive networks

    NASA Astrophysics Data System (ADS)

    van den Berg, Eric; Fecko, Mariusz A.; Samtani, Sunil; Lacatus, Catalin; Patel, Mitesh

    2010-04-01

    Existing distributed approaches to topology control are poor at exploiting the large configuration space of cognitive radios and use extensive inter-node synchronization to aim at optimality. We have created a framework to design and study distributed topology control algorithms that combine network-formation games with machine learning. In our approach, carefully designed incentive mechanisms drive distributed autonomous agents towards a pre-determined system-wide optimum. The algorithms rely on game players to pursue selfish actions through low-complexity greedy algorithms with low or no signaling overhead. Convergence and stability are ensured through proper mechanism design that eliminates infinite adaptation process. The framework also includes game-theoretic extensions to influence behavior such as fragment merging and preferring links to weakly connected neighbors. Learning allows adaptations that prevent node starvation, reduce link flapping, and minimize routing disruptions by incorporating network layer feedback in cost/utility tradeoffs. The algorithms are implemented in Telcordia Wireless IP Scalable Network Emulator. Using greedy utility maximization as a benchmark, we show improvements of 13-40% for metrics such as the numbers of disconnected fragments and weakly connected nodes, topology stability, and disruption to user flows. The proposed framework is particularly suitable to cognitive radio networks because it can be extended to handle heterogeneous users with different utility functions and conflicting objectives. Desired outcome is then achieved by application of standard cooperation techniques such as utility transfer (payments). Additional cross-layer optimizations are possible by playing games at multiple layers in a highly scalable manner.

  9. Distributed fault estimation with randomly occurring uncertainties over sensor networks

    NASA Astrophysics Data System (ADS)

    Dong, Hongli; Wang, Zidong; Bu, Xianye; Alsaadi, Fuad E.

    2016-07-01

    This paper is concerned with the distributed fault estimation problem for a class of uncertain stochastic systems over sensor networks. The norm-bounded uncertainty enters into the system in a random way governed by a set of Bernoulli distributed white sequence. The purpose of the addressed problem is to design distributed fault estimators, via available output measurements from not only the individual sensor, but also its neighbouring sensors, such that the fault estimation error converges to zero exponentially in the mean square while the disturbance rejection attenuation is constrained to a give level by means of the ? performance index. Intensive stochastic analysis is carried out to obtain sufficient conditions for ensuring the exponential stability as well as prescribed ? performance for the overall estimation error dynamics. Simulation results are provided to demonstrate the effectiveness of the proposed fault estimation technique in this paper.

  10. Patch Network for Power Allocation and Distribution in Smart Materials

    NASA Technical Reports Server (NTRS)

    Golembiewski, Walter T.

    2000-01-01

    The power allocation and distribution (PAD) circuitry is capable of allocating and distributing a single or multiple sources of power over multi-elements of a power user grid system. The purpose of this invention is to allocate and distribute power that is collected by individual patch rectennas to a region of specific power-user devices, such as actuators. The patch rectenna converts microwave power into DC power. Then this DC power is used to drive actuator devices. However, the power from patch rectennas is not sufficient to drive actuators unless all the collected power is effectively used to drive another group by allocation and distribution. The power allocation and distribution (PAD) circuitry solves the shortfall of power for devices in a large array. The PAD concept is based on the networked power control in which power collected over the whole array of rectennas is allocated to a sub domain where a group of devices is required to be activated for operation. Then the allocated power is distributed to individual element of power-devices in the sub domain according to a selected run-mode.

  11. DataONE: A Distributed Earth Science Data Network

    NASA Astrophysics Data System (ADS)

    Cook, R. B.; DataONE Leadership Team

    2011-12-01

    Addressing the Earth's environmental problems requires that we change the ways that we harness existing data and develop new methods to combine, analyze, and visualize diverse data resources. DataONE (Observation Network for Earth) represents a virtual organization whose goal is to enable new science and knowledge creation through universal access to data about life on Earth and the environment that sustains it. DataONE is designed to be the foundation of innovative environmental science through a distributed framework and sustainable cyberinfrastructure that meets the needs of science and society for open, persistent, robust, and secure access to easily discovered Earth observational data. DataONE is interdisciplinary, making disparate biological and environmental data available and engaging scientists, land-managers, policy makers, students, educators, and the public through logical access and intuitive visualizations. The foundation of DataONE is the established collaboration among participating organizations that have multi-decadal expertise in a wide range of fields that includes: existing archive initiatives, libraries, environmental observing systems and research networks, data and information management, science synthesis centers, and professional societies. Most importantly, DataONE will serve a broad range of science domains both directly and through the interoperability with the DataONE distributed network.

  12. Non-coding RNAs and complex distributed genetic networks

    NASA Astrophysics Data System (ADS)

    Zhdanov, Vladimir

    2011-08-01

    In eukaryotic cells, the mRNA-protein interplay can be dramatically influenced by non-coding RNAs (ncRNAs). Although this new paradigm is now widely accepted, an understanding of the effect of ncRNAs on complex genetic networks is lacking. To clarify what may happen in this case, we propose a mean-field kinetic model describing the influence of ncRNA on a complex genetic network with a distributed architecture including mutual protein-mediated regulation of many genes transcribed into mRNAs. ncRNA is considered to associate with mRNAs and inhibit their translation and/or facilitate degradation. Our results are indicative of the richness of the kinetics under consideration. The main complex features are found to be bistability and oscillations. One could expect to find kinetic chaos as well. The latter feature has however not been observed in our calculations. In addition, we illustrate the difference in the regulation of distributed networks by mRNA and ncRNA.

  13. Distributed System Intruder Tools, Trinoo and Tribe Flood Network

    SciTech Connect

    Criscuolo, P.J.; Rathbun, T

    1999-12-21

    Trinoo and Tribe Flood Network (TFN) are new forms of denial of Service (DOS) attacks. attacks are designed to bring down a computer or network by overloading it with a large amount of network traffic using TCP, UDP, or ICMP. In the past, these attacks came from a single location and were easy to detect. Trinoo and TFN are distributed system intruder tools. These tools launch DoS attacks from multiple computer systems at a target system simultaneously. This makes the assault hard to detect and almost impossible to track to the original attacker. Because these attacks can be launched from hundreds of computers under the command of a single attacker, they are far more dangerous than any DoS attack launched from a single location. These distributed tools have only been seen on Solaris and Linux machines, but there is no reason why they could not be modified for UNIX machines. The target system can also be of any type because the attack is based on the TCP/IP architecture, not a flaw in any particular operating system (OS). CIAC considers the risks presented by these DoS tools to be high.

  14. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  15. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation

    PubMed Central

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

  16. Improved Quantum Artificial Fish Algorithm Application to Distributed Network Considering Distributed Generation.

    PubMed

    Du, Tingsong; Hu, Yang; Ke, Xianting

    2015-01-01

    An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantum artificial fish to update the artificial fish for searching for optimal value. Then, we apply the proposed new algorithm, the quantum artificial fish swarm algorithm (QAFSA), the basic artificial fish swarm algorithm (BAFSA), and the global edition artificial fish swarm algorithm (GAFSA) to the simulation experiments for some typical test functions, respectively. The simulation results demonstrate that the proposed algorithm can escape from the local extremum effectively and has higher convergence speed and better accuracy. Finally, applying IQAFSA to distributed network problems and the simulation results for 33-bus radial distribution network system show that IQAFSA can get the minimum power loss after comparing with BAFSA, GAFSA, and QAFSA. PMID:26447713

  17. The evolution of distributed association networks in the human brain.

    PubMed

    Buckner, Randy L; Krienen, Fenna M

    2013-12-01

    The human cerebral cortex is vastly expanded relative to other primates and disproportionately occupied by distributed association regions. Here we offer a hypothesis about how association networks evolved their prominence and came to possess circuit properties vital to human cognition. The rapid expansion of the cortical mantle may have untethered large portions of the cortex from strong constraints of molecular gradients and early activity cascades that lead to sensory hierarchies. What fill the gaps between these hierarchies are densely interconnected networks that widely span the cortex and mature late into development. Limitations of the tethering hypothesis are discussed as well as its broad implications for understanding critical features of the human brain as a byproduct of size scaling.

  18. Exploration of heterogeneity in distributed research network drug safety analyses.

    PubMed

    Hansen, Richard A; Zeng, Peng; Ryan, Patrick; Gao, Juan; Sonawane, Kalyani; Teeter, Benjamin; Westrich, Kimberly; Dubois, Robert W

    2014-12-01

    Distributed data networks representing large diverse populations are an expanding focus of drug safety research. However, interpreting results is difficult when treatment effect estimates vary across datasets (i.e., heterogeneity). In a previous study, risk estimates were generated for selected drugs and potential adverse outcomes. Analyses were replicated across eight distributed data sources using an identical analytic structure. To evaluate heterogeneity of risk estimates across data sources, the estimates were combined with summary-level data characterizing the population of each data source. Meta-analysis, meta-regression, and plots of the influence on overall results versus contribution to heterogeneity were examined and used to illustrate an approach to heterogeneity assessment. Heterogeneity, as measured by the I-squared statistic, was high with variability across outcomes. Plots of the relationship between influence on overall results and contribution to heterogeneity suggest that certain datasets and characteristics were influential but there was variability dependent on the drug and outcome being assessed. Exploratory meta-regression identified many possible influential factors, but may be subject to ecological bias and false positive conclusions. Distributed data network drug safety analyses can produce heterogeneous risk estimates that may not be easily explained. Approaches illustrated here can be useful for research that is subject to similar problems with heterogeneity. PMID:26052957

  19. Exploration of heterogeneity in distributed research network drug safety analyses.

    PubMed

    Hansen, Richard A; Zeng, Peng; Ryan, Patrick; Gao, Juan; Sonawane, Kalyani; Teeter, Benjamin; Westrich, Kimberly; Dubois, Robert W

    2014-12-01

    Distributed data networks representing large diverse populations are an expanding focus of drug safety research. However, interpreting results is difficult when treatment effect estimates vary across datasets (i.e., heterogeneity). In a previous study, risk estimates were generated for selected drugs and potential adverse outcomes. Analyses were replicated across eight distributed data sources using an identical analytic structure. To evaluate heterogeneity of risk estimates across data sources, the estimates were combined with summary-level data characterizing the population of each data source. Meta-analysis, meta-regression, and plots of the influence on overall results versus contribution to heterogeneity were examined and used to illustrate an approach to heterogeneity assessment. Heterogeneity, as measured by the I-squared statistic, was high with variability across outcomes. Plots of the relationship between influence on overall results and contribution to heterogeneity suggest that certain datasets and characteristics were influential but there was variability dependent on the drug and outcome being assessed. Exploratory meta-regression identified many possible influential factors, but may be subject to ecological bias and false positive conclusions. Distributed data network drug safety analyses can produce heterogeneous risk estimates that may not be easily explained. Approaches illustrated here can be useful for research that is subject to similar problems with heterogeneity.

  20. Logical Graphics Design Technique for Drawing Distribution Networks

    NASA Astrophysics Data System (ADS)

    Al-A`Ali, Mansoor

    Electricity distribution networks normally consist of tens of primary feeders, thousands of substations and switching stations spread over large geographical areas and thus require a complex system in order to manage them properly from within the distribution control centre. We show techniques for using Delphi Object Oriented components to automatically generate, display and manage graphically and logically the circuits of the network. The graphics components are dynamically interactive and thus the system allows switching operations as well as displays. The object oriented approach was developed to replace an older system, which used Microstation with MDL as the programming language and ORACLE as the DBMS. Before this, the circuits could only be displayed schematically, which has many inherent problems in speed and readability of large displays. Schematic graphics displays were cumbersome when adding or deleting stations; this problem is now resolved using our approach by logically generating the graphics from the database connectivity information. This paper demonstrates the method of designing these Object Oriented components and how they can be used in specially created algorithms to generate the necessary interactive graphics. Four different logical display algorithms were created and in this study we present samples of the four different outputs of these algorithms which prove that distribution engineers can work with logical display of the circuits which are aimed to speed up the switching operations and for better clarity of the display.

  1. A Rawlsian Approach to Distribute Responsibilities in Networks

    PubMed Central

    2009-01-01

    Due to their non-hierarchical structure, socio-technical networks are prone to the occurrence of the problem of many hands. In the present paper an approach is introduced in which people’s opinions on responsibility are empirically traced. The approach is based on the Rawlsian concept of Wide Reflective Equilibrium (WRE) in which people’s considered judgments on a case are reflectively weighed against moral principles and background theories, ideally leading to a state of equilibrium. Application of the method to a hypothetical case with an artificially constructed network showed that it is possible to uncover the relevant data to assess a consensus amongst people in terms of their individual WRE. It appeared that the moral background theories people endorse are not predictive for their actual distribution of responsibilities but that they indicate ways of reasoning and justifying outcomes. Two ways of ascribing responsibilities were discerned, corresponding to two requirements of a desirable responsibility distribution: fairness and completeness. Applying the method triggered learning effects, both with regard to conceptual clarification and moral considerations, and in the sense that it led to some convergence of opinions. It is recommended to apply the method to a real engineering case in order to see whether this approach leads to an overlapping consensus on a responsibility distribution which is justifiable to all and in which no responsibilities are left unfulfilled, therewith trying to contribute to the solution of the problem of many hands. PMID:19626463

  2. The SECOQC quantum key distribution network in Vienna

    NASA Astrophysics Data System (ADS)

    Peev, M.; Pacher, C.; Alléaume, R.; Barreiro, C.; Bouda, J.; Boxleitner, W.; Debuisschert, T.; Diamanti, E.; Dianati, M.; Dynes, J. F.; Fasel, S.; Fossier, S.; Fürst, M.; Gautier, J.-D.; Gay, O.; Gisin, N.; Grangier, P.; Happe, A.; Hasani, Y.; Hentschel, M.; Hübel, H.; Humer, G.; Länger, T.; Legré, M.; Lieger, R.; Lodewyck, J.; Lorünser, T.; Lütkenhaus, N.; Marhold, A.; Matyus, T.; Maurhart, O.; Monat, L.; Nauerth, S.; Page, J.-B.; Poppe, A.; Querasser, E.; Ribordy, G.; Robyr, S.; Salvail, L.; Sharpe, A. W.; Shields, A. J.; Stucki, D.; Suda, M.; Tamas, C.; Themel, T.; Thew, R. T.; Thoma, Y.; Treiber, A.; Trinkler, P.; Tualle-Brouri, R.; Vannel, F.; Walenta, N.; Weier, H.; Weinfurter, H.; Wimberger, I.; Yuan, Z. L.; Zbinden, H.; Zeilinger, A.

    2009-07-01

    In this paper, we present the quantum key distribution (QKD) network designed and implemented by the European project SEcure COmmunication based on Quantum Cryptography (SECOQC) (2004-2008), unifying the efforts of 41 research and industrial organizations. The paper summarizes the SECOQC approach to QKD networks with a focus on the trusted repeater paradigm. It discusses the architecture and functionality of the SECOQC trusted repeater prototype, which has been put into operation in Vienna in 2008 and publicly demonstrated in the framework of a SECOQC QKD conference held from October 8 to 10, 2008. The demonstration involved one-time pad encrypted telephone communication, a secure (AES encryption protected) video-conference with all deployed nodes and a number of rerouting experiments, highlighting basic mechanisms of the SECOQC network functionality. The paper gives an overview of the eight point-to-point network links in the prototype and their underlying technology: three plug and play systems by id Quantique, a one way weak pulse system from Toshiba Research in the UK, a coherent one-way system by GAP Optique with the participation of id Quantique and the AIT Austrian Institute of Technology (formerly ARCAustrian Research Centers GmbH—ARC is now operating under the new name AIT Austrian Institute of Technology GmbH following a restructuring initiative.), an entangled photons system by the University of Vienna and the AIT, a continuous-variables system by Centre National de la Recherche Scientifique (CNRS) and THALES Research and Technology with the participation of Université Libre de Bruxelles, and a free space link by the Ludwig Maximillians University in Munich connecting two nodes situated in adjacent buildings (line of sight 80 m). The average link length is between 20 and 30 km, the longest link being 83 km. The paper presents the architecture and functionality of the principal networking agent—the SECOQC node module, which enables the authentic

  3. Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

    USGS Publications Warehouse

    Torgersen, Christian E.; Gresswell, Robert E.; Bateman, Doug

    2004-01-01

    Biological and physical properties of rivers and streams are inherently difficult to sample and visualize at the resolution and extent necessary to detect fine-scale distributional patterns over large areas. Satellite imagery and broad-scale fish survey methods are effective for quantifying spatial variability in biological and physical variables over a range of scales in marine environments but are often too coarse in resolution to address conservation needs in inland fisheries management. We present methods for sampling and analyzing multiscale, spatially continuous patterns of stream fishes and physical habitat in small- to medium-size watersheds (500–1000 hectares). Geospatial tools, including geographic information system (GIS) software such as ArcInfo dynamic segmentation and ArcScene 3D analyst modules, were used to display complex biological and physical datasets. These tools also provided spatial referencing information (e.g. Cartesian and route-measure coordinates) necessary for conducting geostatistical analyses of spatial patterns (empirical semivariograms and wavelet analysis) in linear stream networks. Graphical depiction of fish distribution along a one-dimensional longitudinal profile and throughout the stream network (superimposed on a 10-metre digital elevation model) provided the spatial context necessary for describing and interpreting the relationship between landscape pattern and the distribution of coastal cutthroat trout (Oncorhynchus clarki clarki) in western Oregon, U.S.A. The distribution of coastal cutthroat trout was highly autocorrelated and exhibited a spherical semivariogram with a defined nugget, sill, and range. Wavelet analysis of the main-stem longitudinal profile revealed periodicity in trout distribution at three nested spatial scales corresponding ostensibly to landscape disturbances and the spacing of tributary junctions.

  4. Time Synchronization and Distribution Mechanisms for Space Networks

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Gao, Jay L.; Clare, Loren P.; Mills, David L.

    2011-01-01

    This work discusses research on the problems of synchronizing and distributing time information between spacecraft based on the Network Time Protocol (NTP), where NTP is a standard time synchronization protocol widely used in the terrestrial network. The Proximity-1 Space Link Interleaved Time Synchronization (PITS) Protocol was designed and developed for synchronizing spacecraft that are in proximity where proximity is less than 100,000 km distant. A particular application is synchronization between a Mars orbiter and rover. Lunar scenarios as well as outer-planet deep space mother-ship-probe missions may also apply. Spacecraft with more accurate time information functions as a time-server, and the other spacecraft functions as a time-client. PITS can be easily integrated and adaptable to the CCSDS Proximity-1 Space Link Protocol with minor modifications. In particular, PITS can take advantage of the timestamping strategy that underlying link layer functionality provides for accurate time offset calculation. The PITS algorithm achieves time synchronization with eight consecutive space network time packet exchanges between two spacecraft. PITS can detect and avoid possible errors from receiving duplicate and out-of-order packets by comparing with the current state variables and timestamps. Further, PITS is able to detect error events and autonomously recover from unexpected events that can possibly occur during the time synchronization and distribution process. This capability achieves an additional level of protocol protection on top of CRC or Error Correction Codes. PITS is a lightweight and efficient protocol, eliminating the needs for explicit frame sequence number and long buffer storage. The PITS protocol is capable of providing time synchronization and distribution services for a more general domain where multiple entities need to achieve time synchronization using a single point-to-point link.

  5. Distributed high-precision time transfer through passive optical networks

    NASA Astrophysics Data System (ADS)

    Wu, Guiling; Hu, Liang; Zhang, Hao; Chen, Jianping

    2014-09-01

    We propose a one-point to multipoint distributed time transfer through passive optical networks using a time division multiple access (TDMA) based two-way time transfer. The clock at each clock user node is, in turn, compared with the high-precision reference clock at a master node by a two-way time transfer during assigned subperiods. The corresponding TDMA control protocol and time transfer units for the proposed scheme are designed and implemented. A 1×8 experimental system with a 20 km single-mode fiber in each subpath is demonstrated. The results show that a standard deviation of <60 ps can be reached in each comparison subperiod.

  6. Optimal Voltage Regulation for Unbalanced Distribution Networks Considering Distributed Energy Resources

    SciTech Connect

    Xu, Yan; Tomsovic, Kevin

    2015-01-01

    With increasing penetration of distributed generation in the distribution networks (DN), the secure and optimal operation of DN has become an important concern. In this paper, an iterative quadratic constrained quadratic programming model to minimize voltage deviations and maximize distributed energy resource (DER) active power output in a three phase unbalanced distribution system is developed. The optimization model is based on the linearized sensitivity coefficients between controlled variables (e.g., node voltages) and control variables (e.g., real and reactive power injections of DERs). To avoid the oscillation of solution when it is close to the optimum, a golden search method is introduced to control the step size. Numerical simulations on modified IEEE 13 nodes test feeders show the efficiency of the proposed model. Compared to the results solved by heuristic search (harmony algorithm), the proposed model converges quickly to the global optimum.

  7. Simulating the Household Plug-in Hybrid Electric Vehicle Distribution and its Electric Distribution Network Impacts

    SciTech Connect

    Cui, Xiaohui; Kim, Hoe Kyoung; Liu, Cheng; Kao, Shih-Chieh; Bhaduri, Budhendra L

    2012-01-01

    This paper presents a multi agent-based simulation framework for modeling spatial distribution of plug-in hybrid electric vehicle ownership at local residential level, discovering plug-in hybrid electric vehicle hot zones where ownership may quickly increase in the near future, and estimating the impacts of the increasing plug-in hybrid electric vehicle ownership on the local electric distribution network with different charging strategies. We use Knox County, Tennessee as a case study to highlight the simulation results of the agent-based simulation framework.

  8. Distributed estimation for adaptive sensor selection in wireless sensor networks

    NASA Astrophysics Data System (ADS)

    Mahmoud, Magdi S.; Hassan Hamid, Matasm M.

    2014-05-01

    Wireless sensor networks (WSNs) are usually deployed for monitoring systems with the distributed detection and estimation of sensors. Sensor selection in WSNs is considered for target tracking. A distributed estimation scenario is considered based on the extended information filter. A cost function using the geometrical dilution of precision measure is derived for active sensor selection. A consensus-based estimation method is proposed in this paper for heterogeneous WSNs with two types of sensors. The convergence properties of the proposed estimators are analyzed under time-varying inputs. Accordingly, a new adaptive sensor selection (ASS) algorithm is presented in which the number of active sensors is adaptively determined based on the absolute local innovations vector. Simulation results show that the tracking accuracy of the ASS is comparable to that of the other algorithms.

  9. ESIM_DSN Web-Enabled Distributed Simulation Network

    NASA Technical Reports Server (NTRS)

    Bedrossian, Nazareth; Novotny, John

    2002-01-01

    In this paper, the eSim(sup DSN) approach to achieve distributed simulation capability using the Internet is presented. With this approach a complete simulation can be assembled from component subsystems that run on different computers. The subsystems interact with each other via the Internet The distributed simulation uses a hub-and-spoke type network topology. It provides the ability to dynamically link simulation subsystem models to different computers as well as the ability to assign a particular model to each computer. A proof-of-concept demonstrator is also presented. The eSim(sup DSN) demonstrator can be accessed at http://www.jsc.draper.com/esim which hosts various examples of Web enabled simulations.

  10. Distributed Observer Network (DON), Version 3.0, User's Guide

    NASA Technical Reports Server (NTRS)

    Mazzone, Rebecca A.; Conroy, Michael P.

    2015-01-01

    The Distributed Observer Network (DON) is a data presentation tool developed by the National Aeronautics and Space Administration (NASA) to distribute and publish simulation results. Leveraging the display capabilities inherent in modern gaming technology, DON places users in a fully navigable 3-D environment containing graphical models and allows the users to observe how those models evolve and interact over time in a given scenario. Each scenario is driven with data that has been generated by authoritative NASA simulation tools and exported in accordance with a published data interface specification. This decoupling of the data from the source tool enables DON to faithfully display a simulator's results and ensure that every simulation stakeholder will view the exact same information every time.

  11. Microwave circuit analysis and design by a massively distributed computing network

    NASA Astrophysics Data System (ADS)

    Vai, Mankuan; Prasad, Sheila

    1995-05-01

    The advances in microelectronic engineering have rendered massively distributed computing networks practical and affordable. This paper describes one application of this distributed computing paradigm to the analysis and design of microwave circuits. A distributed computing network, constructed in the form of a neural network, is developed to automate the operations typically performed on a normalized Smith chart. Examples showing the use of this computing network for impedance matching and stabilizing are provided.

  12. Distributed user-centric scheduling for visible light communication networks.

    PubMed

    Chen, Lingjiao; Wang, Jiaheng; Zhou, Jiantao; Ng, Derrick Wing Kwan; Schober, Robert; Zhao, Chunming

    2016-07-11

    Visible light communication (VLC) networks, consisting of multiple light-emitting diodes (LEDs) acting as optical access points (APs), can provide low-cost high-rate data transmission to multiple users simultaneously in indoor environments. However, the performance of VLC networks is severely limited by the interference between different users. In this paper, we establish a distributed user-centric scheduling framework based on stable marriage theory, and propose a novel decentralized scheduling method to manage interference by forming flexible amorphous cells for all users. The proposed scheduling method has provable low computational complexity and requires only the exchange of a few 1-bit messages between the APs and the users but not the feedback of the channel state information of the entire network. We further show that the proposed method can achieve both user-wise and system-wise optimality as well as a certain level of fairness. Simulation results indicate that our decentralized user-centric scheduling method outperforms existing centralized approaches in terms of throughput, fairness, and computational complexity.

  13. Distributed user-centric scheduling for visible light communication networks.

    PubMed

    Chen, Lingjiao; Wang, Jiaheng; Zhou, Jiantao; Ng, Derrick Wing Kwan; Schober, Robert; Zhao, Chunming

    2016-07-11

    Visible light communication (VLC) networks, consisting of multiple light-emitting diodes (LEDs) acting as optical access points (APs), can provide low-cost high-rate data transmission to multiple users simultaneously in indoor environments. However, the performance of VLC networks is severely limited by the interference between different users. In this paper, we establish a distributed user-centric scheduling framework based on stable marriage theory, and propose a novel decentralized scheduling method to manage interference by forming flexible amorphous cells for all users. The proposed scheduling method has provable low computational complexity and requires only the exchange of a few 1-bit messages between the APs and the users but not the feedback of the channel state information of the entire network. We further show that the proposed method can achieve both user-wise and system-wise optimality as well as a certain level of fairness. Simulation results indicate that our decentralized user-centric scheduling method outperforms existing centralized approaches in terms of throughput, fairness, and computational complexity. PMID:27410830

  14. Real-time hierarchically distributed processing network interaction simulation

    NASA Technical Reports Server (NTRS)

    Zimmerman, W. F.; Wu, C.

    1987-01-01

    The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

  15. Gestalt-based integrity of distributed networked systems

    NASA Astrophysics Data System (ADS)

    Sapaty, Peter

    2009-09-01

    The project aims at obtaining high integrity and goal orientation of distributed dynamic systems, which may include multiple wireless sensors and mobile robots, as well as humans. The technology developed is based on the ideology of gestalt, where the whole is considered first, dominating over parts and dynamically defining their role and even existence in the context of changing goals and states of environment. Spatial mission scenarios, which may be created on the fly, are represented in a compact non-agents form collectively executed by the intelligent network of interpreters embedded into sensitive points of the system to be managed. The approach allows us to provide effective asymmetric runtime solutions to complex asymmetric problems and fulfill objectives in unpredictable environments, paving the way to massive robotization of advanced civil and military systems. The paper covers a broad spectrum of topics from philosophy and ideology to system management, to novel distributed control technology and its implementation, and to a variety of important applications. The paradigm described may be considered as the first implementation of the idea of gestalt to management of open distributed systems, as well as the first globally programmable universal super-machine dynamically covering distributed worlds and operating with both information and matter without any central resources.

  16. Voltage management of distribution networks with high penetration of distributed photovoltaic generation sources

    NASA Astrophysics Data System (ADS)

    Alyami, Saeed

    Installation of photovoltaic (PV) units could lead to great challenges to the existing electrical systems. Issues such as voltage rise, protection coordination, islanding detection, harmonics, increased or changed short-circuit levels, etc., need to be carefully addressed before we can see a wide adoption of this environmentally friendly technology. Voltage rise or overvoltage issues are of particular importance to be addressed for deploying more PV systems to distribution networks. This dissertation proposes a comprehensive solution to deal with the voltage violations in distribution networks, from controlling PV power outputs and electricity consumption of smart appliances in real time to optimal placement of PVs at the planning stage. The dissertation is composed of three parts: the literature review, the work that has already been done and the future research tasks. An overview on renewable energy generation and its challenges are given in Chapter 1. The overall literature survey, motivation and the scope of study are also outlined in the chapter. Detailed literature reviews are given in the rest of chapters. The overvoltage and undervoltage phenomena in typical distribution networks with integration of PVs are further explained in Chapter 2. Possible approaches for voltage quality control are also discussed in this chapter, followed by the discussion on the importance of the load management for PHEVs and appliances and its benefits to electric utilities and end users. A new real power capping method is presented in Chapter 3 to prevent overvoltage by adaptively setting the power caps for PV inverters in real time. The proposed method can maintain voltage profiles below a pre-set upper limit while maximizing the PV generation and fairly distributing the real power curtailments among all the PV systems in the network. As a result, each of the PV systems in the network has equal opportunity to generate electricity and shares the responsibility of voltage

  17. Radiation detection and situation management by distributed sensor networks

    SciTech Connect

    Jan, Frigo; Mielke, Angela; Cai, D Michael

    2009-01-01

    Detection of radioactive materials in an urban environment usually requires large, portal-monitor-style radiation detectors. However, this may not be a practical solution in many transport scenarios. Alternatively, a distributed sensor network (DSN) could complement portal-style detection of radiological materials through the implementation of arrays of low cost, small heterogeneous sensors with the ability to detect the presence of radioactive materials in a moving vehicle over a specific region. In this paper, we report on the use of a heterogeneous, wireless, distributed sensor network for traffic monitoring in a field demonstration. Through wireless communications, the energy spectra from different radiation detectors are combined to improve the detection confidence. In addition, the DSN exploits other sensor technologies and algorithms to provide additional information about the vehicle, such as its speed, location, class (e.g. car, truck), and license plate number. The sensors are in-situ and data is processed in real-time at each node. Relevant information from each node is sent to a base station computer which is used to assess the movement of radioactive materials.

  18. Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network

    PubMed Central

    Schilling, Lisa M.; Kwan, Bethany M.; Drolshagen, Charles T.; Hosokawa, Patrick W.; Brandt, Elias; Pace, Wilson D.; Uhrich, Christopher; Kamerick, Michael; Bunting, Aidan; Payne, Philip R.O.; Stephens, William E.; George, Joseph M.; Vance, Mark; Giacomini, Kelli; Braddy, Jason; Green, Mika K.; Kahn, Michael G.

    2013-01-01

    Introduction: Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA. Methods: The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets. Discussion: SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions. PMID:25848567

  19. Distributed Clone Detection in Static Wireless Sensor Networks: Random Walk with Network Division

    PubMed Central

    Khan, Wazir Zada; Aalsalem, Mohammed Y.; Saad, N. M.

    2015-01-01

    Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads. PMID:25992913

  20. Distributed clone detection in static wireless sensor networks: random walk with network division.

    PubMed

    Khan, Wazir Zada; Aalsalem, Mohammed Y; Saad, N M

    2015-01-01

    Wireless Sensor Networks (WSNs) are vulnerable to clone attacks or node replication attacks as they are deployed in hostile and unattended environments where they are deprived of physical protection, lacking physical tamper-resistance of sensor nodes. As a result, an adversary can easily capture and compromise sensor nodes and after replicating them, he inserts arbitrary number of clones/replicas into the network. If these clones are not efficiently detected, an adversary can be further capable to mount a wide variety of internal attacks which can emasculate the various protocols and sensor applications. Several solutions have been proposed in the literature to address the crucial problem of clone detection, which are not satisfactory as they suffer from some serious drawbacks. In this paper we propose a novel distributed solution called Random Walk with Network Division (RWND) for the detection of node replication attack in static WSNs which is based on claimer-reporter-witness framework and combines a simple random walk with network division. RWND detects clone(s) by following a claimer-reporter-witness framework and a random walk is employed within each area for the selection of witness nodes. Splitting the network into levels and areas makes clone detection more efficient and the high security of witness nodes is ensured with moderate communication and memory overheads. Our simulation results show that RWND outperforms the existing witness node based strategies with moderate communication and memory overheads.

  1. C+L band wavelength division multiplexing access network with distributed-controlled protection architecture

    NASA Astrophysics Data System (ADS)

    Yeh, Chien Hung; Chow, Chi Wai

    2011-12-01

    In this work, we propose and experimentally demonstrate a novel distributed-controlled protection architecture for automatic and fast network restoration in wavelength division multiplexing-passive optical network (WDM-PON). The proposed scheme can support both C and L bands. Besides, duplication of network equipments, such as optical networking unit (ONU) or optical line terminal, is not required. In this distributed-controlled system, each ONU can always keep track of the network status. Hence, this can facilitate the network manage by removing the work loads from the central office. Besides, the proposed scheme can tolerate simultaneous fiber cuts in the feeder and distributed fibers.

  2. 75 FR 9343 - Nomenclature Change Relating to the Network Distribution Center Transition

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-02

    ... 111 and 121 Nomenclature Change Relating to the Network Distribution Center Transition AGENCY: Postal... to the ongoing transition of USPS bulk mail centers (BMC) to network distribution centers (NDC), by... Gambhir at 202-268-6256. SUPPLEMENTARY INFORMATION: Background: The BMC network was established in...

  3. Distributed Regional Aerosol Gridded Observation Network (DRAGON) - Korea 2012 campaign

    NASA Astrophysics Data System (ADS)

    Kim, J.; Holben, B. N.; Eck, T. F.; Jeong, U.; Kim, W. V.; Choi, M.; Kim, D. S.; Kim, B.; Kim, S.; Ghim, Y.; Kim, Y. J.; Kim, J. H.; Park, R.; Seo, M.; Song, C.; Yum, S.; Woo, J.; Yoon, S.; Lee, K.; Lee, M.; Lim, J.; Chang, I.; Jeong, M. J.; Bae, M.; Sorokin, M.; Giles, D. M.; Schafer, J.; Herman, J. R.

    2013-12-01

    One of the main objectives of Distributed Regional Aerosol Gridded Observation Network (DRAGON) campaign in Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) mission is to understand the relationship between the column optical properties of the atmosphere and the surface level air quality in terms of aerosols and gases. Recently, with the cooperative efforts with NASA (National Aeronautics and Space Administration) / GSFC (Goddard Space Flight Center), Korean University research groups, and KME (Korea Ministry of Environment) / NIER (National Institute of Environmental Research), DRAGON-Korea 2012 campaign was successfully performed from March to May 2012. The campaign sites were divided into two groups, the National scale sites and Seoul metropolitan sites. Thirteen Cimel sunphotometers were distributed at National scale sites including two metropolitan cities and several remote sites. Nine Cimel sunphotometers were distributed at Seoul Metropolitan sites including several residential sites and traffic source areas. The measured datasets are being analyzed in diverse fields of air quality communities including in-situ measurement groups, satellite remote sensing groups, chemical modeling groups, and airplane measurement groups. We will introduce several preliminary results of the analysis and discuss the future planes and corporations in Korea.

  4. Multi-scale modularity and motif distributional effect in metabolic networks.

    PubMed

    Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui

    2016-01-01

    Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.

  5. Biology, Methodology or Chance? The Degree Distributions of Bipartite Ecological Networks

    PubMed Central

    Williams, Richard J.

    2011-01-01

    The distribution of the number of links per species, or degree distribution, is widely used as a summary of the topology of complex networks. Degree distributions have been studied in a range of ecological networks, including both mutualistic bipartite networks of plants and pollinators or seed dispersers and antagonistic bipartite networks of plants and their consumers. The shape of a degree distribution, for example whether it follows an exponential or power-law form, is typically taken to be indicative of the processes structuring the network. The skewed degree distributions of bipartite mutualistic and antagonistic networks are usually assumed to show that ecological or co-evolutionary processes constrain the relative numbers of specialists and generalists in the network. I show that a simple null model based on the principle of maximum entropy cannot be rejected as a model for the degree distributions in most of the 115 bipartite ecological networks tested here. The model requires knowledge of the number of nodes and links in the network, but needs no other ecological information. The model cannot be rejected for 159 (69%) of the 230 degree distributions of the 115 networks tested. It performed equally well on the plant and animal degree distributions, and cannot be rejected for 81 (70%) of the 115 plant distributions and 78 (68%) of the animal distributions. There are consistent differences between the degree distributions of mutualistic and antagonistic networks, suggesting that different processes are constraining these two classes of networks. Fit to the MaxEnt null model is consistently poor among the largest mutualistic networks. Potential ecological and methodological explanations for deviations from the model suggest that spatial and temporal heterogeneity are important drivers of the structure of these large networks. PMID:21390231

  6. A Partially Distributed Intrusion Detection System for Wireless Sensor Networks

    PubMed Central

    Cho, Eung Jun; Hong, Choong Seon; Lee, Sungwon; Jeon, Seokhee

    2013-01-01

    The increasing use of wireless sensor networks, which normally comprise several very small sensor nodes, makes their security an increasingly important issue. They can be practically and efficiently secured using intrusion detection systems. Conventional security mechanisms are not usually applicable due to the sensor nodes having limitations of computational power, memory capacity, and battery power. Therefore, specific security systems should be designed to function under constraints of energy or memory. A partially distributed intrusion detection system with low memory and power demands is proposed here. It employs a Bloom filter, which allows reduced signature code size. Multiple Bloom filters can be combined to reduce the signature code for each Bloom filter array. The mechanism could then cope with potential denial of service attacks, unlike many previous detection systems with Bloom filters. The mechanism was evaluated and validated through analysis and simulation.

  7. Distributed Efficient Similarity Search Mechanism in Wireless Sensor Networks

    PubMed Central

    Ahmed, Khandakar; Gregory, Mark A.

    2015-01-01

    The Wireless Sensor Network similarity search problem has received considerable research attention due to sensor hardware imprecision and environmental parameter variations. Most of the state-of-the-art distributed data centric storage (DCS) schemes lack optimization for similarity queries of events. In this paper, a DCS scheme with metric based similarity searching (DCSMSS) is proposed. DCSMSS takes motivation from vector distance index, called iDistance, in order to transform the issue of similarity searching into the problem of an interval search in one dimension. In addition, a sector based distance routing algorithm is used to efficiently route messages. Extensive simulation results reveal that DCSMSS is highly efficient and significantly outperforms previous approaches in processing similarity search queries. PMID:25751081

  8. Classification of moving targets by a distributed sensor network

    NASA Astrophysics Data System (ADS)

    Khatri, Hiralal C.; Kirose, Getachew; Ranney, Kenneth; Innocenti, Roberto

    2004-09-01

    We present a procedure for classification of targets by a network of distributed radar sensors deployed to detect, locate and track moving targets. Estimated sensor positions and selected positions of a target under track are used to obtain the target aspect angle as seen by the sensors. This data is used to create a multi-angle profile of the target. Stored target templates are then matched in the least mean square sense with the target profile. These templates were generated from radar return signals collected from selected targets on a turntable. Probabilities of correct classification obtained by a simulation of the classification procedure are given as functions of signal-to-noise ratios and errors in estimates of target and sensor locations.

  9. Water losses dynamic modelling in water distribution networks

    NASA Astrophysics Data System (ADS)

    Puleo, Valeria; Milici, Barbara

    2015-12-01

    In the last decades, one of the main concerns of the water system managers have been the minimisation of water losses, that frequently reach values of 30% or even 70% of the volume supplying the water distribution network. The economic and social costs associated with water losses in modern water supply systems are rapidly rising to unacceptably high levels. Furthermore, the problem of the water losses assumes more and more importance mainly when periods of water scarcity occur or when not sufficient water supply takes part in areas with fast growth. In the present analysis, a dynamic model was used for estimating real and apparent losses of a real case study. A specific nodal demand model reflecting the user's tank installation and a specific apparent losses module were implemented. The results from the dynamic model were compared with the modelling estimation based on a steady-state approach.

  10. AGN Spectral Energy Distributions of GLAST Telescope Network Program Objects

    NASA Astrophysics Data System (ADS)

    Adkins, Jeff; Lacy, Mark; Daou, Doris; Rapp, Steve; Stefaniak, Linda

    2005-03-01

    The Gamma-Ray Large Area Space Telescope (GLAST) has a proposed observing list that includes AGNs and Polars bright enough to be observed optically by amateurs and students. This observing list is maintained by the "GLAST Telescope Network" (GTN) and includes a number of objects that have yet to be observed by the Spitzer Space Telescope. Our project will observe one of these objects with the Spitzer MIPS and the IRAC instruments to determine their Spectral Energy Distribution (SED), which will be compared to a computer model of disk emission in order to determine what component of the SED is due to the disk and what component is due to synchrotron radiation induced by the jets. In addition we will observe our program objects prior to, simultaneously with, and after Spitzer observes them. This gives a direct connection from Spitzer research to student activities in the classroom.

  11. Acquisition of causal models for local distributions in Bayesian networks.

    PubMed

    Xiang, Yang; Truong, Minh

    2014-09-01

    To specify a Bayesian network, a local distribution in the form of a conditional probability table, often of an effect conditioned on its n causes, needs to be acquired, one for each non-root node. Since the number of parameters to be assessed is generally exponential in n , improving the efficiency is an important concern in knowledge engineering. Non-impeding noisy-AND (NIN-AND) tree causal models reduce the number of parameters to being linear in n , while explicitly expressing both reinforcing and undermining interactions among causes. The key challenge in NIN-AND tree modeling is the acquisition of the NIN-AND tree structure. In this paper, we formulate a concise structure representation and an expressive causal interaction function of NIN-AND trees. Building on these representations, we propose two structural acquisition methods, which are applicable to both elicitation-based and machine learning-based acquisitions. Their accuracy is demonstrated through experimental evaluations.

  12. Distributed Prognostics and Health Management with a Wireless Network Architecture

    NASA Technical Reports Server (NTRS)

    Goebel, Kai; Saha, Sankalita; Sha, Bhaskar

    2013-01-01

    A heterogeneous set of system components monitored by a varied suite of sensors and a particle-filtering (PF) framework, with the power and the flexibility to adapt to the different diagnostic and prognostic needs, has been developed. Both the diagnostic and prognostic tasks are formulated as a particle-filtering problem in order to explicitly represent and manage uncertainties in state estimation and remaining life estimation. Current state-of-the-art prognostic health management (PHM) systems are mostly centralized in nature, where all the processing is reliant on a single processor. This can lead to a loss in functionality in case of a crash of the central processor or monitor. Furthermore, with increases in the volume of sensor data as well as the complexity of algorithms, traditional centralized systems become for a number of reasons somewhat ungainly for successful deployment, and efficient distributed architectures can be more beneficial. The distributed health management architecture is comprised of a network of smart sensor devices. These devices monitor the health of various subsystems or modules. They perform diagnostics operations and trigger prognostics operations based on user-defined thresholds and rules. The sensor devices, called computing elements (CEs), consist of a sensor, or set of sensors, and a communication device (i.e., a wireless transceiver beside an embedded processing element). The CE runs in either a diagnostic or prognostic operating mode. The diagnostic mode is the default mode where a CE monitors a given subsystem or component through a low-weight diagnostic algorithm. If a CE detects a critical condition during monitoring, it raises a flag. Depending on availability of resources, a networked local cluster of CEs is formed that then carries out prognostics and fault mitigation by efficient distribution of the tasks. It should be noted that the CEs are expected not to suspend their previous tasks in the prognostic mode. When the

  13. Hierarchical Data Distribution Scheme for Peer-to-Peer Networks

    NASA Astrophysics Data System (ADS)

    Bhushan, Shashi; Dave, M.; Patel, R. B.

    2010-11-01

    In the past few years, peer-to-peer (P2P) networks have become an extremely popular mechanism for large-scale content sharing. P2P systems have focused on specific application domains (e.g. music files, video files) or on providing file system like capabilities. P2P is a powerful paradigm, which provides a large-scale and cost-effective mechanism for data sharing. P2P system may be used for storing data globally. Can we implement a conventional database on P2P system? But successful implementation of conventional databases on the P2P systems is yet to be reported. In this paper we have presented the mathematical model for the replication of the partitions and presented a hierarchical based data distribution scheme for the P2P networks. We have also analyzed the resource utilization and throughput of the P2P system with respect to the availability, when a conventional database is implemented over the P2P system with variable query rate. Simulation results show that database partitions placed on the peers with higher availability factor perform better. Degradation index, throughput, resource utilization are the parameters evaluated with respect to the availability factor.

  14. Distributed Sensor Network With Collective Computation For Situational Awareness

    NASA Astrophysics Data System (ADS)

    Dreicer, Jared S.; Jorgensen, Anders M.; Dors, Eric E.

    2002-10-01

    Initiated under Laboratory Directed R&D funding we have engaged in empirical studies, theory development, and initial hardware development for a ground-based Distributed Sensor Network with Collective Computation (DSN-CC). A DSN-CC is a network that uses node-to-node communication and on-board processing to achieve gains in response time, power usage, communication bandwidth, detection resolution, and robustness. DSN-CCs are applicable to both military and civilian problems where massive amounts of data gathered over a large area must be processed to yield timely conclusions. We have built prototype hardware DSN-CC nodes. Each node has self-contained power and is 6"×10"×2". Each node contains a battery pack with power feed from a solar panel that forms the lid, a central processing board, a GPS card, and radio card. Further system properties will be discussed, as will scenarios in which the system might be used to counter Nuclear/Biological/Chemical (NBC) threats of unconventional warfare. Mid-year in FY02 this DSN-CC research project received funding from the Office of Nonproliferation Research and Engineering (NA-22), NNSA to support nuclear proliferation technology development.

  15. Distributed Sensible Heat Flux Measurements for Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Huwald, H.; Brauchli, T.; Lehning, M.; Higgins, C. W.

    2015-12-01

    The sensible heat flux component of the surface energy balance is typically computed using eddy covariance or two point profile measurements while alternative approaches such as the flux variance method based on convective scaling has been much less explored and applied. Flux variance (FV) certainly has a few limitations and constraints but may be an interesting and competitive method in low-cost and power limited wireless sensor networks (WSN) with the advantage of providing spatio-temporal sensible heat flux over the domain of the network. In a first step, parameters such as sampling frequency, sensor response time, and averaging interval are investigated. Then we explore the applicability and the potential of the FV method for use in WSN in a field experiment. Low-cost sensor systems are tested and compared against reference instruments (3D sonic anemometers) to evaluate the performance and limitations of the sensors as well as the method with respect to the standard calculations. Comparison experiments were carried out at several sites to gauge the flux measurements over different surface types (gravel, grass, water) from the low-cost systems. This study should also serve as an example of spatially distributed sensible heat flux measurements.

  16. On Improving the Reliability of Distribution Networks Based on Investment Scenarios Using Reference Networks

    NASA Astrophysics Data System (ADS)

    Kawahara, Koji

    Distribution systems are inherent monopolies and therefore these have generally been regulated in order to protect customers and to ensure cost-effective operation. In the UK this is one of the functions of OFGEM (Office of Gas and Electricity Markets). Initially the regulation was based on the value of assets but there is a trend nowadays towards performance-based regulation. In order to achieve this, a methodology is needed that enables the reliability performance associated with alternative investment strategies to be compared with the investment cost of these strategies. At present there is no accepted approach for such assessments. Building on the concept of reference networks proposed in Refs. (1), (2), this paper describes how these networks can be used to assess the impact that performance driven investment strategies will have on the improvement in reliability indices. The method has been tested using the underground and overhead part of a real system.

  17. Structure Learning and Statistical Estimation in Distribution Networks - Part I

    SciTech Connect

    Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

    2015-02-13

    Traditionally power distribution networks are either not observable or only partially observable. This complicates development and implementation of new smart grid technologies, such as those related to demand response, outage detection and management, and improved load-monitoring. In this two part paper, inspired by proliferation of the metering technology, we discuss estimation problems in structurally loopy but operationally radial distribution grids from measurements, e.g. voltage data, which are either already available or can be made available with a relatively minor investment. In Part I, the objective is to learn the operational layout of the grid. Part II of this paper presents algorithms that estimate load statistics or line parameters in addition to learning the grid structure. Further, Part II discusses the problem of structure estimation for systems with incomplete measurement sets. Our newly suggested algorithms apply to a wide range of realistic scenarios. The algorithms are also computationally efficient – polynomial in time– which is proven theoretically and illustrated computationally on a number of test cases. The technique developed can be applied to detect line failures in real time as well as to understand the scope of possible adversarial attacks on the grid.

  18. Distributed visual-target-surveillance system in wireless sensor networks.

    PubMed

    Wang, Xue; Wang, Sheng; Bi, Daowei

    2009-10-01

    A wireless sensor network (WSN) is a powerful unattended distributed measurement system, which is widely used in target surveillance because of its outstanding performance in distributed sensing and signal processing. This paper introduces a multiview visual-target-surveillance system in WSN, which can autonomously implement target classification and tracking with collaborative online learning and localization. The proposed system is a hybrid system of single-node and multinode fusion. It is constructed on a peer-to-peer (P2P)-based computing paradigm and consists of some simple but feasible methods for target detection and feature extraction. Importantly, a support-vector-machine-based semisupervised learning method is used to achieve online classifier learning with only unlabeled samples. To reduce the energy consumption and increase the accuracy, a novel progressive data-fusion paradigm is proposed for online learning and localization, where a feasible routing method is adopted to implement information transmission with the tradeoff between performance and cost. Experiment results verify that the proposed surveillance system is an effective, energy-efficient, and robust system for real-world application. Furthermore, the P2P-based progressive data-fusion paradigm can improve the energy efficiency and robustness of target surveillance.

  19. Distributed Denial of Service Tools, Trin00, Tribe Flood Network, Tribe Flood Network 2000 and Stacheldraht.

    SciTech Connect

    Criscuolo, P. J.

    2000-02-14

    One type of attack on computer systems is know as a Denial of Service (DoS) attack. A DoS attack is designed to prevent legitimate users from using a system. Traditional Denial of Service attacks are done by exploiting a buffer overflow, exhausting system resources, or exploiting a system bug that results in a system that is no longer functional. In the summer of 1999, a new breed of attack has been developed called Distributed Denial of Service (DDoS) attack. Several educational and high capacity commercial sites have been affected by these DDoS attacks. A DDoS attack uses multiple machines operating in concert to attack a network or site. There is very little that can be done if you are the target of a DDoS. The nature of these attacks cause so much extra network traffic that it is difficult for legitimate traffic to reach your site while blocking the forged attacking packets. The intent of this paper is to help sites not be involved in a DDoS attack. The first tools developed to perpetrate the DDoS attack were Trin00 and Tribe Flood Network (TFN). They spawned the next generation of tools called Tribe Flood Network 2000 (TFN2K) and Stacheldraht (German for Barb Wire). These DDoS attack tools are designed to bring one or more sites down by flooding the victim with large amounts of network traffic originating at multiple locations and remotely controlled by a single client. This paper discusses how these DDoS tools work, how to detect them, and specific technical information on each individual tool. It is written with the system administrator in mind. It assumes that the reader has basic knowledge of the TCP/IP Protocol.

  20. 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

  1. 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

  2. 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).

  3. 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

    2016-07-01

    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).

  4. Statistics of modifier distributions in mixed network glasses.

    PubMed

    Mauro, John C

    2013-03-28

    The constituents of any network glass can be broadly classified as either network formers or network modifiers. Network formers, such as SiO2, Al2O3, B2O3, P2O5, etc., provide the backbone of the glass network and are the primary source of its rigid constraints. Network modifiers play a supporting role, such as charge stabilization of the network formers or alteration of the network topology through rupture of bridging bonds and introduction of floppy modes. The specific role of the modifiers depends on which network formers are present in the glass and the relative free energies of modifier interactions with each type of network former site. This variation of free energy with modifier speciation is responsible for the so-called mixed network former effect, i.e., the nonlinear scaling of property values in glasses having fixed modifier concentration but a varying ratio of network formers. In this paper, a general theoretical framework is presented describing the statistical mechanics of modifier speciation in mixed network glasses. The model provides a natural explanation for the mixed network former effect and also accounts for the impact of thermal history and relaxation on glass network topology. PMID:23556773

  5. Geosciences Information Network (GIN): A modular, distributed, interoperable data network for the geosciences

    NASA Astrophysics Data System (ADS)

    Allison, M.; Gundersen, L. C.; Richard, S. M.; Dickinson, T. L.

    2008-12-01

    A coalition of the state geological surveys (AASG), the U.S. Geological Survey (USGS), and partners will receive NSF funding over 3 years under the INTEROP solicitation to start building the Geoscience Information Network (www.geoinformatics.info/gin) a distributed, interoperable data network. The GIN project will develop standardized services to link existing and in-progress components using a few standards and protocols, and work with data providers to implement these services. The key components of this network are 1) catalog system(s) for data discovery; 2) service definitions for interfaces for searching catalogs and accessing resources; 3) shared interchange formats to encode information for transmission (e.g. various XML markup languages); 4) data providers that publish information using standardized services defined by the network; and 5) client applications adapted to use information resources provided by the network. The GIN will integrate and use catalog resources that currently exist or are in development. We are working with the USGS National Geologic Map Database's existing map catalog, with the USGS National Geological and Geophysical Data Preservation Program, which is developing a metadata catalog (National Digital Catalog) for geoscience information resource discovery, and with the GEON catalog. Existing interchange formats will be used, such as GeoSciML, ChemML, and Open Geospatial Consortium sensor, observation and measurement MLs. Client application development will be fostered by collaboration with industry and academic partners. The GIN project will focus on the remaining aspects of the system -- service definitions and assistance to data providers to implement the services and bring content online - and on system integration of the modules. Initial formal collaborators include the OneGeology-Europe consortium of 27 nations that is building a comparable network under the EU INSPIRE initiative, GEON, Earthchem, and GIS software company ESRI

  6. Enhancements for distributed certificate authority approaches for mobile wireless ad hoc networks.

    SciTech Connect

    Van Leeuwen, Brian P.; Michalski, John T.; Anderson, William Erik

    2003-12-01

    Mobile wireless ad hoc networks that are resistant to adversarial manipulation are necessary for distributed systems used in military and security applications. Critical to the successful operation of these networks, which operate in the presence of adversarial stressors, are robust and efficient information assurance methods. In this report we describe necessary enhancements for a distributed certificate authority (CA) used in secure wireless network architectures. Necessary cryptographic algorithms used in distributed CAs are described and implementation enhancements of these algorithms in mobile wireless ad hoc networks are developed. The enhancements support a network's ability to detect compromised nodes and facilitate distributed CA services. We provide insights to the impacts the enhancements will have on network performance with timing diagrams and preliminary network simulation studies.

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

    PubMed Central

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

    2016-01-01

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

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

    PubMed

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

    2016-01-01

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

  9. An Open Distributed Architecture for Sensor Networks for Risk Management

    PubMed Central

    Douglas, John; Usländer, Thomas; Schimak, Gerald; Esteban, J. Fernando; Denzer, Ralf

    2008-01-01

    , http://www.eu-orchestra.org/) and ‘Sensors Anywhere’ (SANY, http://sany-ip.eu/) are discussed in this article. These projects have developed an open distributed information technology architecture and have implemented web services for the accessing and using data emanating, for example, from sensor networks. These developments are based on existing data and service standards proposed by international organizations. The projects seek to develop the ideals of the EC directive INSPIRE (http://inspire.jrc.it), which was launched in 2001 and whose implementation began this year (2007), into the risk management domain. Thanks to the open nature of the architecture and services being developed within these projects, they can be implemented by any interested party and can be accessed by all potential users. The architecture is based around a service-oriented approach that makes use of Internet-based applications (web services) whose inputs and outputs conform to standards. The benefit of this philosophy is that it is expected to favor the emergence of an operational market for risk management services in Europe, it eliminates the need to replace or radically alter the hundreds of already operational IT systems in Europe (drastically lowering costs for users), and it allows users and stakeholders to achieve interoperability while using the system most adequate to their needs, budgets, culture etc. (i.e. it has flexibility).

  10. Synchronization-desynchronization transitions in complex networks: an interplay of distributed time delay and inhibitory nodes.

    PubMed

    Wille, Carolin; Lehnert, Judith; Schöll, Eckehard

    2014-09-01

    We investigate the combined effects of distributed delay and the balance between excitatory and inhibitory nodes on the stability of synchronous oscillations in a network of coupled Stuart-Landau oscillators. To this end a symmetric network model is proposed for which the stability can be investigated analytically. It is found that beyond a critical inhibition ratio, synchronization tends to be unstable. However, increasing distributional widths can counteract this trend, leading to multiple resynchronization transitions at relatively high inhibition ratios. The extended applicability of the results is confirmed by numerical studies on asymmetrically perturbed network topologies. All investigations are performed on two distribution types, a uniform distribution and a Γ distribution.

  11. Reduction of chemical reaction networks through delay distributions.

    PubMed

    Barrio, Manuel; Leier, André; Marquez-Lago, Tatiana T

    2013-03-14

    Accurate modelling and simulation of dynamic cellular events require two main ingredients: an adequate description of key chemical reactions and simulation of such chemical events in reasonable time spans. Quite logically, posing the right model is a crucial step for any endeavour in Computational Biology. However, more often than not, it is the associated computational costs which actually limit our capabilities of representing complex cellular behaviour. In this paper, we propose a methodology aimed at representing chains of chemical reactions by much simpler, reduced models. The abridgement is achieved by generation of model-specific delay distribution functions, consecutively fed to a delay stochastic simulation algorithm. We show how such delay distributions can be analytically described whenever the system is solely composed of consecutive first-order reactions, with or without additional "backward" bypass reactions, yielding an exact reduction. For models including other types of monomolecular reactions (constitutive synthesis, degradation, or "forward" bypass reactions), we discuss why one must adopt a numerical approach for its accurate stochastic representation, and propose two alternatives for this. In these cases, the accuracy depends on the respective numerical sample size. Our model reduction methodology yields significantly lower computational costs while retaining accuracy. Quite naturally, computational costs increase alongside network size and separation of time scales. Thus, we expect our model reduction methodologies to significantly decrease computational costs in these instances. We anticipate the use of delays in model reduction will greatly alleviate some of the current restrictions in simulating large sets of chemical reactions, largely applicable in pharmaceutical and biological research.

  12. Reduction of chemical reaction networks through delay distributions

    NASA Astrophysics Data System (ADS)

    Barrio, Manuel; Leier, André; Marquez-Lago, Tatiana T.

    2013-03-01

    Accurate modelling and simulation of dynamic cellular events require two main ingredients: an adequate description of key chemical reactions and simulation of such chemical events in reasonable time spans. Quite logically, posing the right model is a crucial step for any endeavour in Computational Biology. However, more often than not, it is the associated computational costs which actually limit our capabilities of representing complex cellular behaviour. In this paper, we propose a methodology aimed at representing chains of chemical reactions by much simpler, reduced models. The abridgement is achieved by generation of model-specific delay distribution functions, consecutively fed to a delay stochastic simulation algorithm. We show how such delay distributions can be analytically described whenever the system is solely composed of consecutive first-order reactions, with or without additional "backward" bypass reactions, yielding an exact reduction. For models including other types of monomolecular reactions (constitutive synthesis, degradation, or "forward" bypass reactions), we discuss why one must adopt a numerical approach for its accurate stochastic representation, and propose two alternatives for this. In these cases, the accuracy depends on the respective numerical sample size. Our model reduction methodology yields significantly lower computational costs while retaining accuracy. Quite naturally, computational costs increase alongside network size and separation of time scales. Thus, we expect our model reduction methodologies to significantly decrease computational costs in these instances. We anticipate the use of delays in model reduction will greatly alleviate some of the current restrictions in simulating large sets of chemical reactions, largely applicable in pharmaceutical and biological research.

  13. Degree Distributions in Sexual Networks: A Framework for Evaluating Evidence

    PubMed Central

    Hamilton, Deven T.; Handcock, Mark S.; Morris, Martina

    2015-01-01

    Objective We present a likelihood based statistical framework to test the fit of power-law and alternative social process models for the degree distribution, and derive the sexually transmitted infection epidemic predictions from each model. Study Design Five surveys from the United States are analyzed. Model fit is formally compared via Akaike Information Criterion and Bayesian Information Criterion, and substantively assessed via the prediction of a generalized epidemic. Results Formal goodness-of-fit tests do not consistently identify any model as the best all around fit to the US data. Power-law models predict a generalized sexually transmitted infection epidemic in the United States, while most alternative models do not. Conclusions Power-law models do not fit the data better than alternative models, and they consistently make inaccurate epidemic predictions. Better models are needed to represent the behavioral basis of sexual networks and the structures that result, if these data are to be used for disease transmission modeling. PMID:18217224

  14. Distributed reinforcement learning for adaptive and robust network intrusion response

    NASA Astrophysics Data System (ADS)

    Malialis, Kleanthis; Devlin, Sam; Kudenko, Daniel

    2015-07-01

    Distributed denial of service (DDoS) attacks constitute a rapidly evolving threat in the current Internet. Multiagent Router Throttling is a novel approach to defend against DDoS attacks where multiple reinforcement learning agents are installed on a set of routers and learn to rate-limit or throttle traffic towards a victim server. The focus of this paper is on online learning and scalability. We propose an approach that incorporates task decomposition, team rewards and a form of reward shaping called difference rewards. One of the novel characteristics of the proposed system is that it provides a decentralised coordinated response to the DDoS problem, thus being resilient to DDoS attacks themselves. The proposed system learns remarkably fast, thus being suitable for online learning. Furthermore, its scalability is successfully demonstrated in experiments involving 1000 learning agents. We compare our approach against a baseline and a popular state-of-the-art throttling technique from the network security literature and show that the proposed approach is more effective, adaptive to sophisticated attack rate dynamics and robust to agent failures.

  15. A Distributed Network for Social Cognition Enriched for Oxytocin Receptors

    PubMed Central

    Mitre, Mariela; Marlin, Bianca J.; Schiavo, Jennifer K.; Morina, Egzona; Norden, Samantha E.; Hackett, Troy A.; Aoki, Chiye J.

    2016-01-01

    Oxytocin is a neuropeptide important for social behaviors such as maternal care and parent–infant bonding. It is believed that oxytocin receptor signaling in the brain is critical for these behaviors, but it is unknown precisely when and where oxytocin receptors are expressed or which neural circuits are directly sensitive to oxytocin. To overcome this challenge, we generated specific antibodies to the mouse oxytocin receptor and examined receptor expression throughout the brain. We identified a distributed network of female mouse brain regions for maternal behaviors that are especially enriched for oxytocin receptors, including the piriform cortex, the left auditory cortex, and CA2 of the hippocampus. Electron microscopic analysis of the cerebral cortex revealed that oxytocin receptors were mainly expressed at synapses, as well as on axons and glial processes. Functionally, oxytocin transiently reduced synaptic inhibition in multiple brain regions and enabled long-term synaptic plasticity in the auditory cortex. Thus modulation of inhibition may be a general mechanism by which oxytocin can act throughout the brain to regulate parental behaviors and social cognition. SIGNIFICANCE STATEMENT Oxytocin is an important peptide hormone involved in maternal behavior and social cognition, but it has been unclear what elements of neural circuits express oxytocin receptors due to the paucity of suitable antibodies. Here, we developed new antibodies to the mouse oxytocin receptor. Oxytocin receptors were found in discrete brain regions and at cortical synapses for modulating excitatory-inhibitory balance and plasticity. These antibodies should be useful for future studies of oxytocin and social behavior. PMID:26911697

  16. Distributed Network and Multiprocessing Minicomputer State-of-the-Art Capabilities.

    ERIC Educational Resources Information Center

    Theis, Douglas J.

    An examination of the capabilities of minicomputers and midicomputers now on the market reveals two basic items which users should evaluate when selecting computers for their own applications: distributed networking systems and multiprocessing architectures. Variables which should be considered in evaluating a distributed networking system…

  17. Distributed data fusion over an ad hoc network

    NASA Astrophysics Data System (ADS)

    Anderson, Sean; Binns, Lewis A.; Collins, Peter R. C.; Cooke, Andrew; Greenway, Phil; Valachis, Dimitris

    2002-08-01

    We have been developing a decentralised architecture for data fusion for several years. In this architecture, sensing nodes, each with their own processing, are networked together. Previously, we have researched fully connected networks, tree-connected networks, and networks with loops, and have developed a range of theoretical and empirical results for dynamic networks. Here we report the results obtained from building and demonstrating a decentralised data fusion system in which the nodes are connected via an ad hoc network. Several vision based tracking nodes are linked via a wireless LAN. We use UDP to establish local routing tables within the network whenever a node joins, and TCP/IP to provide point to point communications within the network. We show that the resulting data fusion system is modular, scalable and fault tolerant. In particular, we demonstrate robustness to nodes joining and leaving the network, either by choice or as a result of link drop-out. In addition to experimental results from the project, we present some thoughts on how the technology could be applied to large scale, heterogeneous sensor networks.

  18. Software-Enabled Distributed Network Governance: The PopMedNet Experience

    PubMed Central

    Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

    2016-01-01

    Introduction: The expanded availability of electronic health information has led to increased interest in distributed health data research networks. Distributed Research Network Model: The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. Software Enabled Governance: PopMedNet: The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Selected Case Studies: Four case studies describe how PopMedNet is used to enforce network governance models. Issues and Challenges: Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. Conclusions: The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders. PMID:27141522

  19. Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

    NASA Astrophysics Data System (ADS)

    Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

    2011-06-01

    For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

  20. Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

    NASA Technical Reports Server (NTRS)

    Wang, Shin-Ywan

    2012-01-01

    The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

  1. A decentralized mechanism for improving the functional robustness of distribution networks.

    PubMed

    Shi, Benyun; Liu, Jiming

    2012-10-01

    Most real-world distribution systems can be modeled as distribution networks, where a commodity can flow from source nodes to sink nodes through junction nodes. One of the fundamental characteristics of distribution networks is the functional robustness, which reflects the ability of maintaining its function in the face of internal or external disruptions. In view of the fact that most distribution networks do not have any centralized control mechanisms, we consider the problem of how to improve the functional robustness in a decentralized way. To achieve this goal, we study two important problems: 1) how to formally measure the functional robustness, and 2) how to improve the functional robustness of a network based on the local interaction of its nodes. First, we derive a utility function in terms of network entropy to characterize the functional robustness of a distribution network. Second, we propose a decentralized network pricing mechanism, where each node need only communicate with its distribution neighbors by sending a "price" signal to its upstream neighbors and receiving "price" signals from its downstream neighbors. By doing so, each node can determine its outflows by maximizing its own payoff function. Our mathematical analysis shows that the decentralized pricing mechanism can produce results equivalent to those of an ideal centralized maximization with complete information. Finally, to demonstrate the properties of our mechanism, we carry out a case study on the U.S. natural gas distribution network. The results validate the convergence and effectiveness of our mechanism when comparing it with an existing algorithm. PMID:22547458

  2. Extracting Hidden Hierarchies in 3D Distribution Networks

    NASA Astrophysics Data System (ADS)

    Modes, Carl; Magnasco, Marcelo; Katifori, Eleni

    2015-03-01

    Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks - the topology and edge weights - determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, we have developed a new algorithm that rests on an abstraction of the physical `tiling' in the case of a two dimensional network to an effective tiling of an abstract surface in space that the network may be thought to sit in. Generically these abstract surfaces are richer than the plane and upon sequential removal of the weakest links by edge weight, neighboring tiles merge and a tree characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models. This new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as mammalian vasculature in the organs, the root networks of clonal colonies like quaking aspen, or the force networks in jammed granular matter.

  3. Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks

    ERIC Educational Resources Information Center

    Yu, Chao

    2013-01-01

    In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…

  4. Empirical study on dyad act-degree distribution in some collaboration networks

    NASA Astrophysics Data System (ADS)

    Chang, Hui; Zhang, Pei-Pei; He, Yue; He, Da-Ren

    2006-03-01

    We (and cooperators) suggest studying the evolution of the extended collaboration networks by a dyad-act organizing model. The analytic and numeric studies of the model lead to a conclusion that most of the collaboration networks should show a dyad act-degree distribution (how many acts a dyad belongs to) between a power law and an exponential function, which can be described by a shifted power law. We have done an empirical study on dyad act-degree distribution in some collaboration networks. They are: the train networks in China, the bus network of Beijing, and traditional Chinese medical prescription formulation network. The results show good agreement with this conclusion. We also discuss what dyad act-degree implies in these networks and what are the possible applications of the study. The details will be published elsewhere.

  5. Decreasing-Rate Pruning Optimizes the Construction of Efficient and Robust Distributed Networks

    PubMed Central

    Navlakha, Saket; Barth, Alison L.; Bar-Joseph, Ziv

    2015-01-01

    Robust, efficient, and low-cost networks are advantageous in both biological and engineered systems. During neural network development in the brain, synapses are massively over-produced and then pruned-back over time. This strategy is not commonly used when designing engineered networks, since adding connections that will soon be removed is considered wasteful. Here, we show that for large distributed routing networks, network function is markedly enhanced by hyper-connectivity followed by aggressive pruning and that the global rate of pruning, a developmental parameter not previously studied by experimentalists, plays a critical role in optimizing network structure. We first used high-throughput image analysis techniques to quantify the rate of pruning in the mammalian neocortex across a broad developmental time window and found that the rate is decreasing over time. Based on these results, we analyzed a model of computational routing networks and show using both theoretical analysis and simulations that decreasing rates lead to more robust and efficient networks compared to other rates. We also present an application of this strategy to improve the distributed design of airline networks. Thus, inspiration from neural network formation suggests effective ways to design distributed networks across several domains. PMID:26217933

  6. Extracting Hidden Hierarchies in 3D Distribution Networks

    NASA Astrophysics Data System (ADS)

    Modes, Carl D.; Magnasco, Marcelo O.; Katifori, Eleni

    2016-07-01

    Natural and man-made transport webs are frequently dominated by dense sets of nested cycles. The architecture of these networks, as defined by the topology and edge weights, determines how efficiently the networks perform their function. Yet, the set of tools that can characterize such a weighted cycle-rich architecture in a physically relevant, mathematically compact way is sparse. In order to fill this void, we have developed a new algorithm that rests on an abstraction of the physical "tiling" in the case of a two-dimensional network to an effective tiling of an abstract surface in 3-space that the network may be thought to sit in. Generically, these abstract surfaces are richer than the flat plane because there are now two families of fundamental units that may aggregate upon cutting weakest links—the plaquettes of the tiling and the longer "topological" cycles associated with the abstract surface itself. Upon sequential removal of the weakest links, as determined by a physically relevant edge weight, such as flow volume or capacity, neighboring plaquettes merge and a new tree graph characterizing this merging process results. The properties of this characteristic tree can provide the physical and topological data required to describe the architecture of the network and to build physical models. The new algorithm can be used for automated phenotypic characterization of any weighted network whose structure is dominated by cycles, such as mammalian vasculature in the organs or the force networks in jammed granular matter.

  7. Method and apparatus for reducing the harmonic currents in alternating-current distribution networks

    DOEpatents

    Beverly, L.H.; Hance, R.D.; Kristalinski, A.L.; Visser, A.T.

    1996-11-19

    An improved apparatus and method reduce the harmonic content of AC line and neutral line currents in polyphase AC source distribution networks. The apparatus and method employ a polyphase Zig-Zag transformer connected between the AC source distribution network and a load. The apparatus and method also employs a mechanism for increasing the source neutral impedance of the AC source distribution network. This mechanism can consist of a choke installed in the neutral line between the AC source and the Zig-Zag transformer. 23 figs.

  8. Method and apparatus for reducing the harmonic currents in alternating-current distribution networks

    DOEpatents

    Beverly, Leon H.; Hance, Richard D.; Kristalinski, Alexandr L.; Visser, Age T.

    1996-01-01

    An improved apparatus and method reduce the harmonic content of AC line and neutral line currents in polyphase AC source distribution networks. The apparatus and method employ a polyphase Zig-Zag transformer connected between the AC source distribution network and a load. The apparatus and method also employs a mechanism for increasing the source neutral impedance of the AC source distribution network. This mechanism can consist of a choke installed in the neutral line between the AC source and the Zig-Zag transformer.

  9. Distributive Computer Networking: Making It Work on a Regional Basis: Effective sharing through a network requires new management and resource distribution techniques.

    PubMed

    Cornew, R W; Morse, P M

    1975-08-15

    After 4 years of operation the NERComP network is now a self-supporting success. Some of the reasons for its success are that (i) the network started small and built up utilization; (ii) the members, through monthly trustee meetings, practiced "participatory management" from the outset; (iii) unlike some networks, NERComP appealed to individual academic and research users who were terminal-oriented and who controlled their own budgets; (iv) the compactness of the New England region made it an ideal laboratory for testing networking concepts; and (v) a dedicated staff was willing to work hard in the face of considerable uncertainty. While the major problems were "political, organizational and economic" (1) we have found that they can be solved if the network meets real needs. We have also found that it is difficult to proceed beyond a certain point without investing responsibility and authority in the networking organization. Conversely, there is a need to distribute some responsibilities such as marketing and user services back to the member institutions. By adopting a modest starting point and achieving limited goals the necessary trust and working relationships between institutions can be built. In our case the necessary planning has been facilitated by recognizing three distinct network functions: governance, user services, and technical operations. Separating out the three essential networing tasks and dealing with each individually through advisory committees, each with its own staff coordinator, has overcome a distracting tendency to address all issues at once. It has also provided an element of feedback between the end user and the supplier not usually present in networking activity. The success of NERComP demonstrates that a distributive-type network can work. Our experiences in New England-which, because of its numerous colleges and universities free from domination by any single institution, is a microcosm for academic computing in the United States

  10. Effective Suppression of Pathological Synchronization in Cortical Networks by Highly Heterogeneous Distribution of Inhibitory Connections

    PubMed Central

    Kada, Hisashi; Teramae, Jun-Nosuke; Tokuda, Isao T.

    2016-01-01

    Even without external random input, cortical networks in vivo sustain asynchronous irregular firing with low firing rate. In addition to detailed balance between excitatory and inhibitory activities, recent theoretical studies have revealed that another feature commonly observed in cortical networks, i.e., long-tailed distribution of excitatory synapses implying coexistence of many weak and a few extremely strong excitatory synapses, plays an essential role in realizing the self-sustained activity in recurrent networks of biologically plausible spiking neurons. The previous studies, however, have not considered highly non-random features of the synaptic connectivity, namely, bidirectional connections between cortical neurons are more common than expected by chance and strengths of synapses are positively correlated between pre- and postsynaptic neurons. The positive correlation of synaptic connections may destabilize asynchronous activity of networks with the long-tailed synaptic distribution and induce pathological synchronized firing among neurons. It remains unclear how the cortical network avoids such pathological synchronization. Here, we demonstrate that introduction of the correlated connections indeed gives rise to synchronized firings in a cortical network model with the long-tailed distribution. By using a simplified feed-forward network model of spiking neurons, we clarify the underlying mechanism of the synchronization. We then show that the synchronization can be efficiently suppressed by highly heterogeneous distribution, typically a lognormal distribution, of inhibitory-to-excitatory connection strengths in a recurrent network model of cortical neurons. PMID:27803659

  11. Distributed learning automata-based algorithm for community detection in complex networks

    NASA Astrophysics Data System (ADS)

    Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza

    2016-03-01

    Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.

  12. NetWall distributed firewall in the use of campus network

    NASA Astrophysics Data System (ADS)

    He, Junhua; Zhang, Pengshuai

    2011-10-01

    Internet provides a modern means of education but also non-mainstream consciousness and poor dissemination of information opens the door, network and moral issues have become prominent, poor dissemination of information and network spread rumors and negative effects of new problems, ideological and political education in schools had a huge impact, poses a severe challenge. This paper presents a distributed firewall will NetWall deployed in a campus network solution. The characteristics of the campus network, using technology to filter out bad information on the means of control, of sensitive information related to the record, establish a complete information security management platform for the campus network.

  13. Geometry of river networks. II. Distributions of component size and number

    SciTech Connect

    Dodds, Peter Sheridan; Rothman, Daniel H.

    2001-01-01

    The structure of a river network may be seen as a discrete set of nested subnetworks built out of individual stream segments. These network components are assigned an integral stream order via a hierarchical and discrete ordering method. Exponential relationships, known as Horton's laws, between stream order and ensemble-averaged quantities pertaining to network components are observed. We extend these observations to incorporate fluctuations and all higher moments by developing functional relationships between distributions. The relationships determined are drawn from a combination of theoretical analysis, analysis of real river networks including the Mississippi, Amazon, and Nile, and numerical simulations on a model of directed, random networks. Underlying distributions of stream segment lengths are identified as exponential. Combinations of these distributions form single-humped distributions with exponential tails, the sums of which are in turn shown to give power-law distributions of stream lengths. Distributions of basin area and stream segment frequency are also addressed. The calculations identify a single length scale as a measure of size fluctuations in network components. This article is the second in a series of three addressing the geometry of river networks.

  14. Data quality assessment for comparative effectiveness research in distributed data networks

    PubMed Central

    Brown, Jeffrey; Kahn, Michael; Toh, Sengwee

    2015-01-01

    Background Electronic health information routinely collected during healthcare delivery and reimbursement can help address the need for evidence about the real-world effectiveness, safety, and quality of medical care. Often, distributed networks that combine information from multiple sources are needed to generate this real-world evidence. Objective We provide a set of field-tested best practices and a set of recommendations for data quality checking for comparative effectiveness research (CER) in distributed data networks. Methods Explore the requirements for data quality checking and describe data quality approaches undertaken by several existing multi-site networks. Results There are no established standards regarding how to evaluate the quality of electronic health data for CER within distributed networks. Data checks of increasing complexity are often employed, ranging from consistency with syntactic rules to evaluation of semantics and consistency within and across sites. Temporal trends within and across sites are widely used, as are checks of each data refresh or update. Rates of specific events and exposures by age group, sex, and month are also common. Discussion Secondary use of electronic health data for CER holds promise but is complex, especially in distributed data networks that incorporate periodic data refreshes. The viability of a learning health system is dependent on a robust understanding of the quality, validity, and optimal secondary uses of routinely collected electronic health data within distributed health data networks. Robust data quality checking can strengthen confidence in findings based on distributed data network. PMID:23793049

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

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Wang, Zidong; Shen, Bo

    2014-05-01

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

  16. Patient Informed Governance of Distributed Research Networks: Results and Discussion from Six Patient Focus Groups

    PubMed Central

    Mamo, Laura A.; Browe, Dennis K.; Logan, Holly C.; Kim, Katherine K.

    2013-01-01

    Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients’ views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes. PMID:24551383

  17. Patient informed governance of distributed research networks: results and discussion from six patient focus groups.

    PubMed

    Mamo, Laura A; Browe, Dennis K; Logan, Holly C; Kim, Katherine K

    2013-01-01

    Understanding how to govern emerging distributed research networks is essential to their success. Distributed research networks aggregate patient medical data from many institutions leaving data within the local provider security system. While much is known about patients' views on secondary medical research, little is known about their views on governance of research networks. We conducted six focus groups with patients from three medical centers across the U.S. to understand their perspectives on privacy, consent, and ethical concerns of sharing their data as part of research networks. Participants positively endorsed sharing their health data with these networks believing that doing so could advance healthcare knowledge. However, patients expressed several concerns regarding security and broader ethical issues such as commercialism, public benefit, and social responsibility. We suggest that network governance guidelines move beyond strict technical requirements and address wider socio-ethical concerns by fully including patients in governance processes.

  18. PAND: A Distribution to Identify Functional Linkage from Networks with Preferential Attachment Property

    PubMed Central

    Li, Hua; Tong, Pan; Gallegos, Juan; Dimmer, Emily; Cai, Guoshuai; Molldrem, Jeffrey J.; Liang, Shoudan

    2015-01-01

    Technology advances have immensely accelerated large-scale mapping of biological networks, which necessitates the development of accurate and powerful network-based algorithms to make functional inferences. A prevailing approach is to leverage functions of neighboring nodes to predict unknown molecular function. However, existing neighbor-based algorithms have ignored the scale-free property hidden in many biological networks. By assuming that neighbor sharing is constrained by the preferential attachment property, we developed a Preferential Attachment based common Neighbor Distribution (PAND) to calculate the probability of the neighbor-sharing event between any two nodes in scale-free networks, which nearly perfectly matched the observed probability in simulations. By applying PAND to a human protein-protein interaction (PPI) network, we showed that smaller probabilities represented closer functional linkages between proteins. With the PAND-derive linkages, we were able to build new networks where the links are more functionally reliable than those of the human PPI network. We then applied simple annotation schemes to a PAND-derived network to make reliable functional predictions for proteins. We also developed an R package called PANDA (PAND-derived functional Associations) to implement the methods proposed in this study. In conclusion, PAND is a useful distribution to calculate the probability of the neighbor-sharing events in scale-free networks. With PAND, we are able to extract reliable functional linkages from real biological networks and builds new networks that are better bases for further functional inference. PMID:26158709

  19. Innovation of laboratory exercises in course Distributed systems and computer networks

    NASA Astrophysics Data System (ADS)

    Souček, Pavel; Slavata, Oldřich; Holub, Jan

    2013-09-01

    This paper is focused on innovation of laboratory exercises in course Distributed Systems and Computer Networks. These exercises were introduced in November of 2012 and replaced older exercises in order to reflect real life applications.

  20. Distributed Transforms for Efficient Data Gathering in Sensor Networks

    NASA Technical Reports Server (NTRS)

    Ortega, Antonio (Inventor); Narang, Sunil K. (Inventor); Shen, Godwin (Inventor); Perez-Trufero, Javier (Inventor)

    2014-01-01

    Devices, systems, and techniques for data collecting network such as wireless sensors are disclosed. A described technique includes detecting one or more remote nodes included in the wireless sensor network using a local power level that controls a radio range of the local node. The technique includes transmitting a local outdegree. The local outdegree can be based on a quantity of the one or more remote nodes. The technique includes receiving one or more remote outdegrees from the one or more remote nodes. The technique includes determining a local node type of the local node based on detecting a node type of the one or more remote nodes, using the one or more remote outdegrees, and using the local outdegree. The technique includes adjusting characteristics, including an energy usage characteristic and a data compression characteristic, of the wireless sensor network by selectively modifying the local power level and selectively changing the local node type.

  1. Distributed Teaching Presence and Communicative Patterns in Asynchronous Learning: Name versus Reply Networks

    ERIC Educational Resources Information Center

    Engel, Anna; Coll, Cesar; Bustos, Alfonso

    2013-01-01

    This work explores some methodological challenges in the application of Social Network Analysis (SNA) to the study of "Asynchronous Learning Networks" (ALN). Our interest in the SNA is situated within the framework of the study of Distributed Teaching Presence (DTP), understood as the exercise of educational influence, through a multi-method…

  2. The values of the parameters of some multilayer distributed RC null networks

    NASA Technical Reports Server (NTRS)

    Huelsman, L. P.; Raghunath, S.

    1974-01-01

    In this correspondence, the values of the parameters of some multilayer distributed RC notch networks are determined, and the usually accepted values are shown to be in error. The magnitude of the error is illustrated by graphs of the frequency response of the networks.

  3. Neural networks as a possible architecture for the distributed control of space systems

    NASA Technical Reports Server (NTRS)

    Fiesler, E.; Choudry, A.

    1987-01-01

    Researchers attempted to identify the features essential for large, complex, multi-modular multi-functional systems possessing a high level of interconnectivity. These features were studied in the context of neural networks with the aim of arriving at a possible architecture of the distributed control system-specific features of the neural networks and their applicability in space systems.

  4. RTS2: Lessons learned from a widely distributed telescope network

    NASA Astrophysics Data System (ADS)

    Kubánek, P.

    2008-03-01

    RTS (Remote Telescope System 2) is a highly modular open source telescope and observatory management software package. It evolved from RTS, which was developed in Python to control a telescope aimed at observing optical transients of γ ray burts. The development of a network system capable of operating robotic telescopes is both difficult and complicated. Along with continued software development one must be concerned with maintaining operations and obtaining results. This is a review of experiences gained building a network of robotic telescopes. It focuses on describing which issues are important during development of the robotic observatory software and requirements for future development of the RTS package.

  5. Simulation based flow distribution network optimization for vacuum assisted resin transfer moulding process

    NASA Astrophysics Data System (ADS)

    Hsiao, Kuang-Ting; Devillard, Mathieu; Advani, Suresh G.

    2004-05-01

    In the vacuum assisted resin transfer moulding (VARTM) process, using a flow distribution network such as flow channels and high permeability fabrics can accelerate the resin infiltration of the fibre reinforcement during the manufacture of composite parts. The flow distribution network significantly influences the fill time and fill pattern and is essential for the process design. The current practice has been to cover the top surface of the fibre preform with the distribution media with the hope that the resin will flood the top surface immediately and penetrate through the thickness. However, this approach has some drawbacks. One is when the resin finds its way to the vent before it has penetrated the preform entirely, which results in a defective part or resin wastage. Also, if the composite structure contains ribs or inserts, this approach invariably results in dry spots. Instead of this intuitive approach, we propose a science-based approach to design the layout of the distribution network. Our approach uses flow simulation of the resin into the network and the preform and a genetic algorithm to optimize the flow distribution network. An experimental case study of a co-cured rib structure is conducted to demonstrate the design procedure and validate the optimized flow distribution network design. Good agreement between the flow simulations and the experimental results was observed. It was found that the proposed design algorithm effectively optimized the flow distribution network of the part considered in our case study and hence should prove to be a useful tool to extend the VARTM process to manufacture of complex structures with effective use of the distribution network layup.

  6. Fiber linked distributed data acquisition in an open network architecture

    SciTech Connect

    Pawelski, F.J.

    1995-03-01

    Flexible and easily expanded process control systems can be achieved through the use of an open and distributed architecture. This paper discusses how to achieve a truly open and distributed process control system as well as some of the goals, concerns and advantages of such a system.

  7. How breadth of degree distribution influences network robustness: comparing localized and random attacks.

    PubMed

    Yuan, Xin; Shao, Shuai; Stanley, H Eugene; Havlin, Shlomo

    2015-09-01

    The stability of networks is greatly influenced by their degree distributions and in particular by their breadth. Networks with broader degree distributions are usually more robust to random failures but less robust to localized attacks. To better understand the effect of the breadth of the degree distribution we study two models in which the breadth is controlled and compare their robustness against localized attacks (LA) and random attacks (RA). We study analytically and by numerical simulations the cases where the degrees in the networks follow a bi-Poisson distribution, P(k)=αe^{-λ_{1}}λ_{1}^{k}/k!+(1-α)e^{-λ_{2}}λ_{2}^{k}/k!,α∈[0,1], and a Gaussian distribution, P(k)=Aexp(-(k-μ)^{2}/2σ^{2}), with a normalization constant A where k≥0. In the bi-Poisson distribution the breadth is controlled by the values of α, λ_{1}, and λ_{2}, while in the Gaussian distribution it is controlled by the standard deviation, σ. We find that only when α=0 or α=1, i.e., degrees obeying a pure Poisson distribution, are LA and RA the same. In all other cases networks are more vulnerable under LA than under RA. For a Gaussian distribution with an average degree μ fixed, we find that when σ^{2} is smaller than μ the network is more vulnerable against random attack. When σ^{2} is larger than μ, however, the network becomes more vulnerable against localized attack. Similar qualitative results are also shown for interdependent networks. PMID:26465441

  8. How breadth of degree distribution influences network robustness: Comparing localized and random attacks

    NASA Astrophysics Data System (ADS)

    Yuan, Xin; Shao, Shuai; Stanley, H. Eugene; Havlin, Shlomo

    2015-09-01

    The stability of networks is greatly influenced by their degree distributions and in particular by their breadth. Networks with broader degree distributions are usually more robust to random failures but less robust to localized attacks. To better understand the effect of the breadth of the degree distribution we study two models in which the breadth is controlled and compare their robustness against localized attacks (LA) and random attacks (RA). We study analytically and by numerical simulations the cases where the degrees in the networks follow a bi-Poisson distribution, P (k ) =α e-λ1λ/1kk ! +(1 -α ) e-λ2λ/2kk ! ,α ∈[0 ,1 ] , and a Gaussian distribution, P (k ) =A exp(-(k/-μ) 22 σ2 ), with a normalization constant A where k ≥0 . In the bi-Poisson distribution the breadth is controlled by the values of α , λ1, and λ2, while in the Gaussian distribution it is controlled by the standard deviation, σ . We find that only when α =0 or α =1 , i.e., degrees obeying a pure Poisson distribution, are LA and RA the same. In all other cases networks are more vulnerable under LA than under RA. For a Gaussian distribution with an average degree μ fixed, we find that when σ2 is smaller than μ the network is more vulnerable against random attack. When σ2 is larger than μ , however, the network becomes more vulnerable against localized attack. Similar qualitative results are also shown for interdependent networks.

  9. Distributed Finite Element Analysis Using a Transputer Network

    NASA Technical Reports Server (NTRS)

    Watson, James; Favenesi, James; Danial, Albert; Tombrello, Joseph; Yang, Dabby; Reynolds, Brian; Turrentine, Ronald; Shephard, Mark; Baehmann, Peggy

    1989-01-01

    The principal objective of this research effort was to demonstrate the extraordinarily cost effective acceleration of finite element structural analysis problems using a transputer-based parallel processing network. This objective was accomplished in the form of a commercially viable parallel processing workstation. The workstation is a desktop size, low-maintenance computing unit capable of supercomputer performance yet costs two orders of magnitude less. To achieve the principal research objective, a transputer based structural analysis workstation termed XPFEM was implemented with linear static structural analysis capabilities resembling commercially available NASTRAN. Finite element model files, generated using the on-line preprocessing module or external preprocessing packages, are downloaded to a network of 32 transputers for accelerated solution. The system currently executes at about one third Cray X-MP24 speed but additional acceleration appears likely. For the NASA selected demonstration problem of a Space Shuttle main engine turbine blade model with about 1500 nodes and 4500 independent degrees of freedom, the Cray X-MP24 required 23.9 seconds to obtain a solution while the transputer network, operated from an IBM PC-AT compatible host computer, required 71.7 seconds. Consequently, the $80,000 transputer network demonstrated a cost-performance ratio about 60 times better than the $15,000,000 Cray X-MP24 system.

  10. Multisensory integration substantiates distributed and overlapping neural networks.

    PubMed

    Pasqualotto, Achille

    2016-01-01

    The hypothesis that highly overlapping networks underlie brain functions (neural reuse) is decisively supported by three decades of multisensory research. Multisensory areas process information from more than one sensory modality and therefore represent the best examples of neural reuse. Recent evidence of multisensory processing in primary visual cortices further indicates that neural reuse is a basic feature of the brain. PMID:27562234

  11. A Topology Visualization Early Warning Distribution Algorithm for Large-Scale Network Security Incidents

    PubMed Central

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology. PMID:24191145

  12. A topology visualization early warning distribution algorithm for large-scale network security incidents.

    PubMed

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology.

  13. A topology visualization early warning distribution algorithm for large-scale network security incidents.

    PubMed

    He, Hui; Fan, Guotao; Ye, Jianwei; Zhang, Weizhe

    2013-01-01

    It is of great significance to research the early warning system for large-scale network security incidents. It can improve the network system's emergency response capabilities, alleviate the cyber attacks' damage, and strengthen the system's counterattack ability. A comprehensive early warning system is presented in this paper, which combines active measurement and anomaly detection. The key visualization algorithm and technology of the system are mainly discussed. The large-scale network system's plane visualization is realized based on the divide and conquer thought. First, the topology of the large-scale network is divided into some small-scale networks by the MLkP/CR algorithm. Second, the sub graph plane visualization algorithm is applied to each small-scale network. Finally, the small-scale networks' topologies are combined into a topology based on the automatic distribution algorithm of force analysis. As the algorithm transforms the large-scale network topology plane visualization problem into a series of small-scale network topology plane visualization and distribution problems, it has higher parallelism and is able to handle the display of ultra-large-scale network topology. PMID:24191145

  14. Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

    PubMed

    Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

    2016-05-01

    Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed.

  15. Evolving Scale-Free Networks by Poisson Process: Modeling and Degree Distribution.

    PubMed

    Feng, Minyu; Qu, Hong; Yi, Zhang; Xie, Xiurui; Kurths, Jurgen

    2016-05-01

    Since the great mathematician Leonhard Euler initiated the study of graph theory, the network has been one of the most significant research subject in multidisciplinary. In recent years, the proposition of the small-world and scale-free properties of complex networks in statistical physics made the network science intriguing again for many researchers. One of the challenges of the network science is to propose rational models for complex networks. In this paper, in order to reveal the influence of the vertex generating mechanism of complex networks, we propose three novel models based on the homogeneous Poisson, nonhomogeneous Poisson and birth death process, respectively, which can be regarded as typical scale-free networks and utilized to simulate practical networks. The degree distribution and exponent are analyzed and explained in mathematics by different approaches. In the simulation, we display the modeling process, the degree distribution of empirical data by statistical methods, and reliability of proposed networks, results show our models follow the features of typical complex networks. Finally, some future challenges for complex systems are discussed. PMID:25956002

  16. Improving Power Quality in Low-Voltage Networks Containing Distributed Energy Resources

    NASA Astrophysics Data System (ADS)

    Mazumder, Sumit; Ghosh, Arindam; Zare, Firuz

    2013-05-01

    Severe power quality problems can arise when a large number of single-phase distributed energy resources (DERs) are connected to a low-voltage power distribution system. Due to the random location and size of DERs, it may so happen that a particular phase generates excess power than its load demand. In such an event, the excess power will be fed back to the distribution substation and will eventually find its way to the transmission network, causing undesirable voltage-current unbalance. As a solution to this problem, the article proposes the use of a distribution static compensator (DSTATCOM), which regulates voltage at the point of common coupling (PCC), thereby ensuring balanced current flow from and to the distribution substation. Additionally, this device can also support the distribution network in the absence of the utility connection, making the distribution system work as a microgrid. The proposals are validated through extensive digital computer simulation studies using PSCADTM.

  17. The Study of Development Strategy for Bank Distribution Network through the Analysis of Inter-regional Financial Transaction Network

    NASA Astrophysics Data System (ADS)

    Hong, Jae Weon; Hong, Won Eui; Kwak, Yoon Sik

    This study attempts to shed light on the factors that influence the locations of bank branches in establishing a bank's distribution network from the angle of the network analysis. Whereas the previous studies analyzed the locations of bank branches on the basis of their geographical characteristics and image, the significance of this study rests upon the fact that it endeavors to explore the location factors from a new perspective of the movement path of financial customers. For this analysis, the network between administrative districts, which form the fundamental unit of a location, was analyzed based on the financial transactional data. The important findings of this study are as follows. First, in conformity with the previous studies, the income level, the spending level, the number of businesses, and the size of workforce in the pertinent region were all found to influence the size of a bank's market. Second, the centrality index extracted from the analysis of the network was found to have a significant effect on the locations of bank branches. In particular, the degree centrality was revealed to have a greater influence on the size of a bank's market than does the closeness centrality. Such results of this study clearly suggest the needs for a new approach from the perspective of network in furtherance of other factors that have been considered important in the previous studies of the distribution network strategies.

  18. Distributed microprocessor automation network for synthesizing radiotracers used in positron emission tomography

    SciTech Connect

    Russell, J.A.G.; Alexoff, D.L.; Wolf, A.P.

    1984-09-01

    This presentation describes an evolving distributed microprocessor network for automating the routine production synthesis of radiotracers used in Positron Emission Tomography. We first present a brief overview of the PET method for measuring biological function, and then outline the general procedure for producing a radiotracer. The paper identifies several reasons for our automating the syntheses of these compounds. There is a description of the distributed microprocessor network architecture chosen and the rationale for that choice. Finally, we speculate about how this network may be exploited to extend the power of the PET method from the large university or National Laboratory to the biomedical research and clinical community at large. 20 refs. (DT)

  19. Traffic-driven epidemic spreading on scale-free networks with tunable degree distribution

    NASA Astrophysics Data System (ADS)

    Yang, Han-Xin; Wang, Bing-Hong

    2016-04-01

    We study the traffic-driven epidemic spreading on scale-free networks with tunable degree distribution. The heterogeneity of networks is controlled by the exponent γ of power-law degree distribution. It is found that the epidemic threshold is minimized at about γ=2.2. Moreover, we find that nodes with larger algorithmic betweenness are more likely to be infected. We expect our work to provide new insights in to the effect of network structures on traffic-driven epidemic spreading.

  20. Distributed Microprocessor Automation Network for Synthesizing Radiotracers Used in Positron Emission Tomography [PET

    DOE R&D Accomplishments Database

    Russell, J. A. G.; Alexoff, D. L.; Wolf, A. P.

    1984-09-01

    This presentation describes an evolving distributed microprocessor network for automating the routine production synthesis of radiotracers used in Positron Emission Tomography. We first present a brief overview of the PET method for measuring biological function, and then outline the general procedure for producing a radiotracer. The paper identifies several reasons for our automating the syntheses of these compounds. There is a description of the distributed microprocessor network architecture chosen and the rationale for that choice. Finally, we speculate about how this network may be exploited to extend the power of the PET method from the large university or National Laboratory to the biomedical research and clinical community at large. (DT)

  1. Better understanding of water quality evolution in water distribution networks using data clustering.

    PubMed

    Mandel, Pierre; Maurel, Marie; Chenu, Damien

    2015-12-15

    The complexity of water distribution networks raises challenges in managing, monitoring and understanding their behavior. This article proposes a novel methodology applying data clustering to the results of hydraulic simulation to define quality zones, i.e. zones with the same dynamic water origin. The methodology is presented on an existing Water Distribution Network; a large dataset of conductivity measurements measured by 32 probes validates the definition of the quality zones. The results show how quality zones help better understanding the network operation and how they can be used to analyze water quality events. Moreover, a statistical comparison with 158,230 conductivity measurements validates the definition of the quality zones.

  2. Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

    NASA Astrophysics Data System (ADS)

    Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

    2016-06-01

    In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

  3. Distribution Tolerant Network Technology Flight Validation Report: DINET

    NASA Technical Reports Server (NTRS)

    Jones, Ross M.

    2009-01-01

    In October and November of 2008, the Jet Propulsion Laboratory installed and tested essential elements of Delay/Disruption Tolerant Networking (DTN) technology on the Deep Impact spacecraft. This experiment, called Deep Impact Network Experiment (DINET), was performed in close cooperation with the EPOXI project which has responsibility for the spacecraft. During DINET some 300 images were transmitted from the JPL nodes to the spacecraft. Then, they were automatically forwarded from the spacecraft back to the JPL nodes, exercising DTN's bundle origination, transmission, acquisition, dynamic route computation, congestion control, prioritization, custody transfer, and automatic retransmission procedures, both on the spacecraft and on the ground, over a period of 27 days. All transmitted bundles were successfully received, without corruption. The DINET experiment demonstrated DTN readiness for operational use in space missions.

  4. Overview of the human brain as a distributed computing network

    SciTech Connect

    Gevins, A.S.

    1983-01-01

    The hierarchically organized human brain is viewed as a prime example of a massively parallel, adaptive information processing and process control system. A brief overview of the human brain is provided for computer architects, in hopes that the principles of massive parallelism, dense connectivity and self-organization of assemblies of processing elements will prove relevant to the design of fifth generation VLSI computing networks. 6 references.

  5. The effect of structural and rheological properties on blood flow distributions in capillary networks

    NASA Astrophysics Data System (ADS)

    Goldman, Daniel

    2001-11-01

    In various tissues microvascular structure, both geometric and topological, has been shown to be an important determinant of microcirculatory hemodynamics. In addition, blood rheology affects flow and hematocrit distributions in the microcirculation. Here we study steady-state hemodynamics in capillary networks modeled on the three-dimensional structure of the hamster cheek pouch retractor muscle. Capillary diameter is fixed while other structural properties are varied and an ensemble of similar random networks is generated for each parameter set. Using an experimentally derived two-phase continuum model for the flow of blood plasma and red cells, we investigate the effects of network size and topology on blood flow distributions and their variability. We also use typical capillary network structures to examine the importance of rheological effects under varying conditions. Our results indicate the relative importance of microvascular structure and blood rheology in determining the hemodynamic properties of capillary networks in striated muscle.

  6. Efficient packet transportation on complex networks with nonuniform node capacity distribution

    NASA Astrophysics Data System (ADS)

    He, Xuan; Niu, Kai; He, Zhiqiang; Lin, Jiaru; Jiang, Zhong-Yuan

    2015-03-01

    Provided that node delivery capacity may be not uniformly distributed in many realistic networks, we present a node delivery capacity distribution in which each node capacity is composed of uniform fraction and degree related proportion. Based on the node delivery capacity distribution, we construct a novel routing mechanism called efficient weighted routing (EWR) strategy to enhance network traffic capacity and transportation efficiency. Compared with the shortest path routing and the efficient routing strategies, the EWR achieves the highest traffic capacity. After investigating average path length, network diameter, maximum efficient betweenness, average efficient betweenness, average travel time and average traffic load under extensive simulations, it indicates that the EWR appears to be a very effective routing method. The idea of this routing mechanism gives us a good insight into network science research. The practical use of this work is prospective in some real complex systems such as the Internet.

  7. Discriminating different classes of biological networks by analyzing the graphs spectra distribution.

    PubMed

    Takahashi, Daniel Yasumasa; Sato, João Ricardo; Ferreira, Carlos Eduardo; Fujita, André

    2012-01-01

    The brain's structural and functional systems, protein-protein interaction, and gene networks are examples of biological systems that share some features of complex networks, such as highly connected nodes, modularity, and small-world topology. Recent studies indicate that some pathologies present topological network alterations relative to norms seen in the general population. Therefore, methods to discriminate the processes that generate the different classes of networks (e.g., normal and disease) might be crucial for the diagnosis, prognosis, and treatment of the disease. It is known that several topological properties of a network (graph) can be described by the distribution of the spectrum of its adjacency matrix. Moreover, large networks generated by the same random process have the same spectrum distribution, allowing us to use it as a "fingerprint". Based on this relationship, we introduce and propose the entropy of a graph spectrum to measure the "uncertainty" of a random graph and the Kullback-Leibler and Jensen-Shannon divergences between graph spectra to compare networks. We also introduce general methods for model selection and network model parameter estimation, as well as a statistical procedure to test the nullity of divergence between two classes of complex networks. Finally, we demonstrate the usefulness of the proposed methods by applying them to (1) protein-protein interaction networks of different species and (2) on networks derived from children diagnosed with Attention Deficit Hyperactivity Disorder (ADHD) and typically developing children. We conclude that scale-free networks best describe all the protein-protein interactions. Also, we show that our proposed measures succeeded in the identification of topological changes in the network while other commonly used measures (number of edges, clustering coefficient, average path length) failed.

  8. Network robustness to targeted attacks. The interplay of expansibility and degree distribution

    NASA Astrophysics Data System (ADS)

    Estrada, E.

    2006-08-01

    We study the property of certain complex networks of being both sparse and highly connected, which is known as “good expansion” (GE). A network has GE properties if every subset S of nodes (up to 50% of the nodes) has a neighborhood that is larger than some “expansion factor” φ multiplied by the number of nodes in S. Using a graph spectral method we introduce here a new parameter measuring the good expansion character of a network. By means of this parameter we are able to classify 51 real-world complex networks — technological, biological, informational, biological and social — as GENs or non-GENs. Combining GE properties and node degree distribution (DD) we classify these complex networks in four different groups, which have different resilience to intentional attacks against their nodes. The simultaneous existence of GE properties and uniform degree distribution contribute significantly to the robustness in complex networks. These features appear solely in 14% of the 51 real-world networks studied here. At the other extreme we find that ˜40% of all networks are very vulnerable to targeted attacks. They lack GE properties, display skewed DD — exponential or power-law — and their topologies are changed more dramatically by targeted attacks directed at bottlenecks than by the removal of network hubs.

  9. Analysis and synthesis of distributed-lumped-active networks by digital computer

    NASA Technical Reports Server (NTRS)

    1973-01-01

    The use of digital computational techniques in the analysis and synthesis of DLA (distributed lumped active) networks is considered. This class of networks consists of three distinct types of elements, namely, distributed elements (modeled by partial differential equations), lumped elements (modeled by algebraic relations and ordinary differential equations), and active elements (modeled by algebraic relations). Such a characterization is applicable to a broad class of circuits, especially including those usually referred to as linear integrated circuits, since the fabrication techniques for such circuits readily produce elements which may be modeled as distributed, as well as the more conventional lumped and active ones.

  10. Lifetime optimization of wireless sensor network by a better nodes positioning and energy distribution

    NASA Astrophysics Data System (ADS)

    Lebreton, J. M.; Murad, N. M.

    2014-10-01

    The purpose of this paper is to propose a method of energy distribution on a Wireless Sensor Network (WSN). Nodes are randomly positioned and the sink is placed at the centre of the surface. Simulations show that relay nodes around the sink are too much requested to convey data, which substantially reduces their lifetime. So, several algorithmic solutions are presented to optimize the energy distribution on each node, compared to the classical uniform energy distribution. Their performance is discussed in terms of failure rate of data transmission and network lifetime. Moreover, the total energy distributed on all nodes before the deployment is invariable and some non-uniform energy distributions are created. Finally, simulations show that every energy distributions greatly improve the WSN lifetime and decrease the failure rate of data transmission.

  11. High Speed Quantum Key Distribution Over Optical Fiber Network System1

    PubMed Central

    Ma, Lijun; Mink, Alan; Tang, Xiao

    2009-01-01

    The National Institute of Standards and Technology (NIST) has developed a number of complete fiber-based high-speed quantum key distribution (QKD) systems that includes an 850 nm QKD system for a local area network (LAN), a 1310 nm QKD system for a metropolitan area network (MAN), and a 3-node quantum network controlled by a network manager. This paper discusses the key techniques used to implement these systems, which include polarization recovery, noise reduction, frequency up-conversion detection based on a periodically polled lithium nitrate (PPLN) waveguide, custom high-speed data handling boards and quantum network management. Using our quantum network, a QKD secured video surveillance application has been demonstrated. Our intention is to show the feasibility and sophistication of QKD systems based on current technology. PMID:27504218

  12. Noise-Assisted Concurrent Multipath Traffic Distribution in Ad Hoc Networks

    PubMed Central

    Murata, Masayuki

    2013-01-01

    The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account. PMID:24319375

  13. Apparatus and method for data communication in an energy distribution network

    DOEpatents

    Hussain, Mohsin; LaPorte, Brock; Uebel, Udo; Zia, Aftab

    2014-07-08

    A system for communicating information on an energy distribution network is disclosed. In one embodiment, the system includes a local supervisor on a communication network, wherein the local supervisor can collect data from one or more energy generation/monitoring devices. The system also includes a command center on the communication network, wherein the command center can generate one or more commands for controlling the one or more energy generation devices. The local supervisor can periodically transmit a data signal indicative of the data to the command center via a first channel of the communication network at a first interval. The local supervisor can also periodically transmit a request for a command to the command center via a second channel of the communication network at a second interval shorter than the first interval. This channel configuration provides effective data communication without a significant increase in the use of network resources.

  14. Stability of weighted spectral distribution in a pseudo tree-like network model

    NASA Astrophysics Data System (ADS)

    Bo, Jiao; Yuan-ping, Nie; Cheng-dong, Huang; Jing, Du; Rong-hua, Guo; Fei, Huang; Jian-mai, Shi

    2016-05-01

    The comparison of networks with different orders strongly depends on the stability analysis of graph features in evolving systems. In this paper, we rigorously investigate the stability of the weighted spectral distribution (i.e., a spectral graph feature) as the network order increases. First, we use deterministic scale-free networks generated by a pseudo tree-like model to derive the precise formula of the spectral feature, and then analyze the stability of the spectral feature based on the precise formula. Except for the scale-free feature, the pseudo tree-like model exhibits the hierarchical and small-world structures of complex networks. The stability analysis is useful for the classification of networks with different orders and the similarity analysis of networks that may belong to the same evolving system. Project supported by the National Natural Science Foundation of China (Grant Nos. 61402485, 61303061, and 71201169).

  15. Noise-assisted concurrent multipath traffic distribution in ad hoc networks.

    PubMed

    Asvarujanon, Narun; Leibnitz, Kenji; Wakamiya, Naoki; Murata, Masayuki

    2013-01-01

    The concept of biologically inspired networking has been introduced to tackle unpredictable and unstable situations in computer networks, especially in wireless ad hoc networks where network conditions are continuously changing, resulting in the need of robustness and adaptability of control methods. Unfortunately, existing methods often rely heavily on the detailed knowledge of each network component and the preconfigured, that is, fine-tuned, parameters. In this paper, we utilize a new concept, called attractor perturbation (AP), which enables controlling the network performance using only end-to-end information. Based on AP, we propose a concurrent multipath traffic distribution method, which aims at lowering the average end-to-end delay by only adjusting the transmission rate on each path. We demonstrate through simulations that, by utilizing the attractor perturbation relationship, the proposed method achieves a lower average end-to-end delay compared to other methods which do not take fluctuations into account.

  16. A Streaming Content Distribution Network for E-Learning Support

    ERIC Educational Resources Information Center

    Esteve, M.; Molina, B.; Palau, C.; Fortino, G.

    2006-01-01

    To date e-Learning material has usually been accessed and delivered through a central web server. As the number of users, the amount of information, the frequency of accesses and the volume of data increase, together with the introduction of multimedia streaming applications, a decentralized content distribution architecture is necessary. In this…

  17. Distributed estimation of sensors position in underwater wireless sensor network

    NASA Astrophysics Data System (ADS)

    Zandi, Rahman; Kamarei, Mahmoud; Amiri, Hadi

    2016-05-01

    In this paper, a localisation method for determining the position of fixed sensor nodes in an underwater wireless sensor network (UWSN) is introduced. In this simple and range-free scheme, the node localisation is achieved by utilising an autonomous underwater vehicle (AUV) that transverses through the network deployment area, and that periodically emits a message block via four directional acoustic beams. A message block contains the actual known AUV position as well as a directional dependent marker that allows a node to identify the respective transmit beam. The beams form a fixed angle with the AUV body. If a node passively receives message blocks, it could calculate the arithmetic mean of the coordinates existing in each messages sequence, to find coordinates at two different time instants via two different successive beams. The node position can be derived from the two computed positions of the AUV. The major advantage of the proposed localisation algorithm is that it is silent, which leads to energy efficiency for sensor nodes. The proposed method does not require any synchronisation among the nodes owing to being silent. Simulation results, using MATLAB, demonstrated that the proposed method had better performance than other similar AUV-based localisation methods in terms of the rates of well-localised sensor nodes and positional root mean square error.

  18. Estimating the 3D pore size distribution of biopolymer networks from directionally biased data.

    PubMed

    Lang, Nadine R; Münster, Stefan; Metzner, Claus; Krauss, Patrick; Schürmann, Sebastian; Lange, Janina; Aifantis, Katerina E; Friedrich, Oliver; Fabry, Ben

    2013-11-01

    The pore size of biopolymer networks governs their mechanical properties and strongly impacts the behavior of embedded cells. Confocal reflection microscopy and second harmonic generation microscopy are widely used to image biopolymer networks; however, both techniques fail to resolve vertically oriented fibers. Here, we describe how such directionally biased data can be used to estimate the network pore size. We first determine the distribution of distances from random points in the fluid phase to the nearest fiber. This distribution follows a Rayleigh distribution, regardless of isotropy and data bias, and is fully described by a single parameter--the characteristic pore size of the network. The bias of the pore size estimate due to the missing fibers can be corrected by multiplication with the square root of the visible network fraction. We experimentally verify the validity of this approach by comparing our estimates with data obtained using confocal fluorescence microscopy, which represents the full structure of the network. As an important application, we investigate the pore size dependence of collagen and fibrin networks on protein concentration. We find that the pore size decreases with the square root of the concentration, consistent with a total fiber length that scales linearly with concentration. PMID:24209841

  19. Flow distribution in parallel microfluidic networks and its effect on concentration gradient

    PubMed Central

    Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N.

    2015-01-01

    The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow

  20. Flow distribution in parallel microfluidic networks and its effect on concentration gradient.

    PubMed

    Guermonprez, Cyprien; Michelin, Sébastien; Baroud, Charles N

    2015-09-01

    The architecture of microfluidic networks can significantly impact the flow distribution within its different branches and thereby influence tracer transport within the network. In this paper, we study the flow rate distribution within a network of parallel microfluidic channels with a single input and single output, using a combination of theoretical modeling and microfluidic experiments. Within the ladder network, the flow rate distribution follows a U-shaped profile, with the highest flow rate occurring in the initial and final branches. The contrast with the central branches is controlled by a single dimensionless parameter, namely, the ratio of hydrodynamic resistance between the distribution channel and the side branches. This contrast in flow rates decreases when the resistance of the side branches increases relative to the resistance of the distribution channel. When the inlet flow is composed of two parallel streams, one of which transporting a diffusing species, a concentration variation is produced within the side branches of the network. The shape of this concentration gradient is fully determined by two dimensionless parameters: the ratio of resistances, which determines the flow rate distribution, and the Péclet number, which characterizes the relative speed of diffusion and advection. Depending on the values of these two control parameters, different distribution profiles can be obtained ranging from a flat profile to a step distribution of solute, with well-distributed gradients between these two limits. Our experimental results are in agreement with our numerical model predictions, based on a simplified 2D advection-diffusion problem. Finally, two possible applications of this work are presented: the first one combines the present design with self-digitization principle to encapsulate the controlled concentration in nanoliter chambers, while the second one extends the present design to create a continuous concentration gradient within an open flow

  1. Structure Learning and Statistical Estimation in Distribution Networks - Part II

    SciTech Connect

    Deka, Deepjyoti; Backhaus, Scott N.; Chertkov, Michael

    2015-02-13

    Limited placement of real-time monitoring devices in the distribution grid, recent trends notwithstanding, has prevented the easy implementation of demand-response and other smart grid applications. Part I of this paper discusses the problem of learning the operational structure of the grid from nodal voltage measurements. In this work (Part II), the learning of the operational radial structure is coupled with the problem of estimating nodal consumption statistics and inferring the line parameters in the grid. Based on a Linear-Coupled(LC) approximation of AC power flows equations, polynomial time algorithms are designed to identify the structure and estimate nodal load characteristics and/or line parameters in the grid using the available nodal voltage measurements. Then the structure learning algorithm is extended to cases with missing data, where available observations are limited to a fraction of the grid nodes. The efficacy of the presented algorithms are demonstrated through simulations on several distribution test cases.

  2. Space-time signal processing for distributed pattern detection in sensor networks

    NASA Astrophysics Data System (ADS)

    Paffenroth, Randy C.; Du Toit, Philip C.; Scharf, Louis L.; Jayasumana, Anura P.; Banadara, Vidarshana; Nong, Ryan

    2012-05-01

    We present a theory and algorithm for detecting and classifying weak, distributed patterns in network data that provide actionable information with quantiable measures of uncertainty. Our work demonstrates the eectiveness of space-time inference on graphs, robust matrix completion, and second order analysis for the detection of distributed patterns that are not discernible at the level of individual nodes. Motivated by the importance of the problem, we are specically interested in detecting weak patterns in computer networks related to Cyber Situational Awareness. Our focus is on scenarios where the nodes (terminals, routers, servers, etc.) are sensors that provide measurements (of packet rates, user activity, central processing unit usage, etc.) that, when viewed independently, cannot provide a denitive determination of the underlying pattern, but when fused with data from across the network both spatially and temporally, the relevant patterns emerge. The approach is applicable to many types of sensor networks including computer networks, wireless networks, mobile sensor networks, and social networks, as well as in contexts such as databases and disease outbreaks.

  3. Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems

    SciTech Connect

    Hoyong Kim; Yunseok Ko; Kyunghee Jung . Dept. of Distribution System)

    1993-07-01

    Neural networks have the capability to map the complex and extremely non-linear relationship between the load levels of zone and system topologies, which is required for feeder reconfiguration in distribution systems. This study is intended to propose the strategies to reconfigure the feeder, by using artificial neural networks with mapping ability. Artificial neural networks determine the appropriate system topology that reduces the power loss according to the variation of load pattern. The control strategy can be easily obtained from the system topology which is provided by artificial neural networks. Artificial neural networks are in groups. The first group estimates the proper load level from the load data of each zone, and the second determines the appropriate system topology from the input load level. In addition, several programs with the training set builder are developed for the design, the training and the accuracy test of artificial neural networks. The authors also evaluate the performance of neural networks designed here, on the test distribution system. Neural networks are implemented in FORTRAN language, and trained on the personal computer COMPAQ 386.

  4. System-wide power management control via clock distribution network

    DOEpatents

    Coteus, Paul W.; Gara, Alan; Gooding, Thomas M.; Haring, Rudolf A.; Kopcsay, Gerard V.; Liebsch, Thomas A.; Reed, Don D.

    2015-05-19

    An apparatus, method and computer program product for automatically controlling power dissipation of a parallel computing system that includes a plurality of processors. A computing device issues a command to the parallel computing system. A clock pulse-width modulator encodes the command in a system clock signal to be distributed to the plurality of processors. The plurality of processors in the parallel computing system receive the system clock signal including the encoded command, and adjusts power dissipation according to the encoded command.

  5. Contamination potential of drinking water distribution network biofilms.

    PubMed

    Wingender, J; Flemming, H C

    2004-01-01

    Drinking water distribution system biofilms were investigated for the presence of hygienically relevant microorganisms. Early biofilm formation was evaluated in biofilm reactors on stainless steel, copper, polyvinyl chloride (PVC) and polyethylene coupons exposed to unchlorinated drinking water. After 12 to 18 months, a plateau phase of biofilm development was reached. Surface colonization on the materials ranged between 4 x 10(6) and 3 x 10(7) cells/cm2, with heterotrophic plate count (HPC) bacteria between 9 x 10(3) and 7 x 10(5) colony-forming units (cfu)/cm2. Established biofilms were investigated in 18 pipe sections (2 to 99 years old) cut out from distribution pipelines. Materials included cast iron, galvanized steel, cement and PVC. Colonization ranged from 4 x 10(5) to 2 x 10(8) cells/cm2, HPC levels varied between 1 and 2 x 10(5) cfu/cm2. No correlation was found between extent of colonization and age of the pipes. Using cultural detection methods, coliform bacteria were rarely found, while Escherichia coli, Pseudomonas aeruginosa and Legionella spp. were not detected in the biofilms. In regular operation, distribution system biofilms do not seem to be common habitats for pathogens. However, nutrient-leaching materials like rubber-coated valves were observed with massive biofilms which harboured coliform bacteria contaminating drinking water.

  6. Contamination potential of drinking water distribution network biofilms.

    PubMed

    Wingender, J; Flemming, H C

    2004-01-01

    Drinking water distribution system biofilms were investigated for the presence of hygienically relevant microorganisms. Early biofilm formation was evaluated in biofilm reactors on stainless steel, copper, polyvinyl chloride (PVC) and polyethylene coupons exposed to unchlorinated drinking water. After 12 to 18 months, a plateau phase of biofilm development was reached. Surface colonization on the materials ranged between 4 x 10(6) and 3 x 10(7) cells/cm2, with heterotrophic plate count (HPC) bacteria between 9 x 10(3) and 7 x 10(5) colony-forming units (cfu)/cm2. Established biofilms were investigated in 18 pipe sections (2 to 99 years old) cut out from distribution pipelines. Materials included cast iron, galvanized steel, cement and PVC. Colonization ranged from 4 x 10(5) to 2 x 10(8) cells/cm2, HPC levels varied between 1 and 2 x 10(5) cfu/cm2. No correlation was found between extent of colonization and age of the pipes. Using cultural detection methods, coliform bacteria were rarely found, while Escherichia coli, Pseudomonas aeruginosa and Legionella spp. were not detected in the biofilms. In regular operation, distribution system biofilms do not seem to be common habitats for pathogens. However, nutrient-leaching materials like rubber-coated valves were observed with massive biofilms which harboured coliform bacteria contaminating drinking water. PMID:15303752

  7. Application of a distributed network in computational fluid dynamic simulations

    NASA Technical Reports Server (NTRS)

    Deshpande, Manish; Feng, Jinzhang; Merkle, Charles L.; Deshpande, Ashish

    1994-01-01

    A general-purpose 3-D, incompressible Navier-Stokes algorithm is implemented on a network of concurrently operating workstations using parallel virtual machine (PVM) and compared with its performance on a CRAY Y-MP and on an Intel iPSC/860. The problem is relatively computationally intensive, and has a communication structure based primarily on nearest-neighbor communication, making it ideally suited to message passing. Such problems are frequently encountered in computational fluid dynamics (CDF), and their solution is increasingly in demand. The communication structure is explicitly coded in the implementation to fully exploit the regularity in message passing in order to produce a near-optimal solution. Results are presented for various grid sizes using up to eight processors.

  8. Global Observation Information Networking: Using the Distributed Image Spreadsheet (DISS)

    NASA Technical Reports Server (NTRS)

    Hasler, Fritz

    1999-01-01

    The DISS and many other tools will be used to present visualizations which span the period from the original Suomi/Hasler animations of the first ATS-1 GEO weather satellite images in 1966 ....... to the latest 1999 NASA Earth Science Vision for the next 25 years. Hot off the SGI Onyx Graphics-Supercomputers are NASA's visualizations of Hurricanes Mitch, Georges, Fran and Linda. These storms have been recently featured on the covers of National Geographic, Time, Newsweek and Popular Science and used repeatedly this season on National and International network TV. Results will be presented from a new paper on automatic wind measurements in Hurricane Luis from 1-min GOES images that appeared in the November BAMS.

  9. Investigation of transient overvoltages in heavily meshed low-voltage underground distribution networks

    NASA Astrophysics Data System (ADS)

    Salcedo Ulerio, Reynaldo Odalis

    The analysis of overvoltages in electrical distribution networks is of considerable significance since they may damage the power system infrastructure and the associated electrical equipment. Overvoltages in distribution networks arise due to switching transients, resonance, lightning strikes and ground faults, among other causes. The operation of network protectors (NWP), low voltage circuit breakers with directional power relay, in a secondary network prevents the continuous flow of reverse power. There are three modes of operation for the network protectors: sensitive, time delayed, and insensitive. In case of a fault, although all of the network protectors sense the fault at the same time, their operation is not simultaneous. Many of them open very quickly with opening times similar to those of the feeder breaker. However, some operate a few cycles later, others take several seconds to open and a few might even fail to operate. Therefore, depending on the settings of the network protectors, faults can last for significantly long time due to backfeeding of current from the low voltage (LV) network into the medium voltage (MV) network. In this work, low voltages are defined as 208V/460V and medium voltage are defined as 25kV/35kV. This thesis presents overvoltages which arise because of the occurrence of a single-line-to-ground (SLG) fault on the MV side (connected in delta) of the system. The thesis reveals that overvoltage stresses are imposed on insulation, micro-processor controlled equipment, and switching devices by overvoltages during current backfeeding. Also, it establishes a relationship between overvoltage magnitude, its duration, and the network loading conditions. Overvoltages above 3 p.u. may be developed as a result of a simultaneous occurrence of three phenomena: neutral displacement, Ferranti effect, and magnetic current chopping. Furthermore, this thesis exposes the possibility of occurrence of the ferro-resonance phenomena in a distribution

  10. Impaired Small-World Network Efficiency and Dynamic Functional Distribution in Patients with Cirrhosis

    PubMed Central

    Hsu, Tun-Wei; Wu, Changwei W.; Cheng, Yu-Fan; Chen, Hsiu-Ling; Lu, Cheng-Hsien; Cho, Kuan-Hung

    2012-01-01

    Hepatic encephalopathy (HE) is a complex neuropsychiatric syndrome and a major complication of liver cirrhosis. Dysmetabolism of the brain, related to elevated ammonia levels, interferes with intercortical connectivity and cognitive function. For evaluation of network efficiency, a ‘small-world’ network model can quantify the effectiveness of information transfer within brain networks. This study aimed to use small-world topology to investigate abnormalities of neuronal connectivity among widely distributed brain regions in patients with liver cirrhosis using resting-state functional magnetic resonance imaging (rs-fMRI). Seventeen cirrhotic patients without HE, 9 with minimal HE, 9 with overt HE, and 35 healthy controls were compared. The interregional correlation matrix was obtained by averaging the rs-fMRI time series over all voxels in each of the 90 regions using the automated anatomical labeling model. Cost and correlation threshold values were then applied to construct the functional brain network. The absolute and relative network efficiencies were calculated; quantifying distinct aspects of the local and global topological network organization. Correlations between network topology parameters, ammonia levels, and the severity of HE were determined using linear regression and ANOVA. The local and global topological efficiencies of the functional connectivity network were significantly disrupted in HE patients; showing abnormal small-world properties. Alterations in regional characteristics, including nodal efficiency and nodal strength, occurred predominantly in the association, primary, and limbic/paralimbic regions. The degree of network organization disruption depended on the severity of HE. Ammonia levels were also significantly associated with the alterations in local network properties. Results indicated that alterations in the rs-fMRI network topology of the brain were associated with HE grade; and that focal or diffuse lesions disturbed the

  11. Space Network Time Distribution and Synchronization Protocol Development for Mars Proximity Link

    NASA Technical Reports Server (NTRS)

    Woo, Simon S.; Gao, Jay L.; Mills, David

    2010-01-01

    Time distribution and synchronization in deep space network are challenging due to long propagation delays, spacecraft movements, and relativistic effects. Further, the Network Time Protocol (NTP) designed for terrestrial networks may not work properly in space. In this work, we consider the time distribution protocol based on time message exchanges similar to Network Time Protocol (NTP). We present the Proximity-1 Space Link Interleaved Time Synchronization (PITS) algorithm that can work with the CCSDS Proximity-1 Space Data Link Protocol. The PITS algorithm provides faster time synchronization via two-way time transfer over proximity links, improves scalability as the number of spacecraft increase, lowers storage space requirement for collecting time samples, and is robust against packet loss and duplication which underlying protocol mechanisms provide.

  12. Fibre optical measuring network based on quasi-distributed amplitude sensors for detecting deformation loads

    SciTech Connect

    Kul'chin, Yurii N; Kolchinskiy, V A; Kamenev, O T; Petrov, Yu S

    2013-02-28

    A new design of a sensitive element for a fibre optical sensor of deformation loads is proposed. A distributed fibre optical measuring network, aimed at determining both the load application point and the load mass, has been developed based on these elements. It is shown that neural network methods of data processing make it possible to combine quasi-distributed amplitude sensors of different types into a unified network. The results of the experimental study of a breadboard of a fibre optical measuring network are reported, which demonstrate successful reconstruction of the trajectory of a moving object (load) with a spatial resolution of 8 cm, as well as the load mass in the range of 1 - 10 kg with a sensitivity of 0.043 kg{sup -1}. (laser optics 2012)

  13. Secure Message Distribution Scheme with Configurable Privacy in Heterogeneous Wireless Sensor Networks

    NASA Astrophysics Data System (ADS)

    Li, Yahui; Ma, Jianfeng; Moon, Sangjae

    Security and privacy of wireless sensor networks are key research issues recently. Most existing researches regarding wireless sensor networks security consider homogenous sensor networks. To achieve better security and performance, we adopt a heterogeneous wireless sensor network (HWSN) model that consists of physically different types of sensor nodes. This paper presents a secure message distribution scheme with configurable privacy for HWSNs, which takes advantage of powerful high-end sensor nodes. The scheme establishes a message distribution topology in an efficient and secure manner. The sensor node only need generate one signature for all the messages for all the users, which can greatly save the communication and computation cost of the sensor node. On the other hand, the user can only know the messages that let him know based on a pre-set policy, which can meet the requirement of the privacy. We show that the scheme has small bandwidth requirements and it is resilient against the node compromise attack.

  14. Optimal design of water distribution networks by a discrete state transition algorithm

    NASA Astrophysics Data System (ADS)

    Zhou, Xiaojun; Gao, David Y.; Simpson, Angus R.

    2016-04-01

    In this study it is demonstrated that, with respect to model formulation, the number of linear and nonlinear equations involved in water distribution networks can be reduced to the number of closed simple loops. Regarding the optimization technique, a discrete state transition algorithm (STA) is introduced to solve several cases of water distribution networks. Firstly, the focus is on a parametric study of the 'restoration probability and risk probability' in the dynamic STA. To deal effectively with head pressure constraints, the influence is then investigated of the penalty coefficient and search enforcement on the performance of the algorithm. Based on the experience gained from training the Two-Loop network problem, a discrete STA has successfully achieved the best known solutions for the Hanoi, triple Hanoi and New York network problems.

  15. Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks.

    PubMed

    Carpenter, Gail A.

    1997-11-01

    A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multilayer perceptrons. With a winner-take-all code, the unsupervised model dART reduces to fuzzy ART and the supervised model dARTMAP reduces to fuzzy ARTMAP. With a distributed code, these networks automatically apportion learned changes according to the degree of activation of each coding node, which permits fast as well as slow learning without catastrophic forgetting. Distributed ART models replace the traditional neural network path weight with a dynamic weight equal to the rectified difference between coding node activation and an adaptive threshold. Thresholds increase monotonically during learning according to a principle of atrophy due to disuse. However, monotonic change at the synaptic level manifests itself as bidirectional change at the dynamic level, where the result of adaptation resembles long-term potentiation (LTP) for single-pulse or low frequency test inputs but can resemble long-term depression (LTD) for higher frequency test inputs. This paradoxical behavior is traced to dual computational properties of phasic and tonic coding signal components. A parallel distributed match-reset-search process also helps stabilize memory. Without the match-reset-search system, dART becomes a type of distributed competitive learning network. PMID:12662488

  16. Scalable Video Broadcasting with Distributed Node Selection in Wireless Networks

    NASA Astrophysics Data System (ADS)

    Lee, Yonghun; Lee, Kyujin; Lee, Kyesan; Suh, Doug Young

    We propose a distributed node selection (DNS) scheme that guarantees quality of service (QoS) of the scalable video broadcasting system over wireless channels. The proposed DNS scheme chooses the destination node based on the SVC layer information, and it selects the best relay from a set of competing candidate nodes by considering two factors: 1) wireless channel conditions between destination and relay candidates and 2) scalable video's layer information. In simulations, the performance of the proposed scheme in terms of quality gains, complexity (overhead) and applicability was examined.

  17. Distributed Grooming in Multi-Domain IP/MPLS-DWDM Networks

    SciTech Connect

    Liu, Qing

    2009-12-01

    This paper studies distributed multi-domain, multilayer provisioning (grooming) in IP/MPLS-DWDM networks. Although many multi-domain studies have emerged over the years, these have primarily considered 'homogeneous' network layers. Meanwhile, most grooming studies have assumed idealized settings with 'global' link state across all layers. Hence there is a critical need to develop practical distributed grooming schemes for real-world networks consisting of multiple domains and technology layers. Along these lines, a detailed hierarchical framework is proposed to implement inter-layer routing, distributed grooming, and setup signaling. The performance of this solution is analyzed in detail using simulation studies and future work directions are also high-lighted.

  18. Distributed adaptive tracking control for synchronization of unknown networked Lagrangian systems.

    PubMed

    Chen, Gang; Lewis, Frank L

    2011-06-01

    This paper investigates the cooperative tracking control problem for a group of Lagrangian vehicle systems with directed communication graph topology. All the vehicles can have different dynamics. A design method for a distributed adaptive protocol is given which guarantees that all the networked systems synchronize to the motion of a target system. The dynamics of the networked systems, as well as the target system, are all assumed unknown. A neural network (NN) is used at each node to approximate the distributed dynamics. The resulting protocol consists of a simple decentralized proportional-plus-derivative term and a nonlinear term with distributed adaptive tuning laws at each node. The case with nonconstant NN approximation error is considered. There, a robust term is added to suppress the external disturbances and the approximation errors of the NNs. Simulation examples are included to demonstrate the effectiveness of the proposed algorithms.

  19. A Network-Aware Distributed Storage Cache for Data Intensive Environments

    SciTech Connect

    Tierney, B.L.; Lee, J.R.; Johnston, W.E.; Crowley, B.; Holding, M.

    1999-12-23

    Modern scientific computing involves organizing, moving, visualizing, and analyzing massive amounts of data at multiple sites around the world. The technologies, the middleware services, and the architectures that are used to build useful high-speed, wide area distributed systems, constitute the field of data intensive computing. In this paper the authors describe an architecture for data intensive applications where they use a high-speed distributed data cache as a common element for all of the sources and sinks of data. This cache-based approach provides standard interfaces to a large, application-oriented, distributed, on-line, transient storage system. They describe their implementation of this cache, how they have made it network aware, and how they do dynamic load balancing based on the current network conditions. They also show large increases in application throughput by access to knowledge of the network conditions.

  20. The European ALMA Regional Centre Network: A Geographically Distributed User Support Model

    NASA Astrophysics Data System (ADS)

    Hatziminaoglou, E.; Zwaan, M.; Andreani, P.; Barta, M.; Bertoldi, F.; Brand, J.; Gueth, F.; Hogerheijde, M.; Maercker, M.; Massardi, M.; Muehle, S.; Muxlow, Th.; Richards, A.; Schilke, P.; Tilanus, R.; Vlemmings, W.; Afonso, J.; Messias, H.

    2015-12-01

    In recent years there has been a paradigm shift from centralised to geographically distributed resources. Individual entities are no longer able to host or afford the necessary expertise in-house, and, as a consequence, society increasingly relies on widespread collaborations. Although such collaborations are now the norm for scientific projects, more technical structures providing support to a distributed scientific community without direct financial or other material benefits are scarce. The network of European ALMA Regional Centre (ARC) nodes is an example of such an internationally distributed user support network. It is an organised effort to provide the European ALMA user community with uniform expert support to enable optimal usage and scientific output of the ALMA facility. The network model for the European ARC nodes is described in terms of its organisation, communication strategies and user support.

  1. Censoring distributed nonlinear state estimates in radar networks

    NASA Astrophysics Data System (ADS)

    Conte, Armond S.; Niu, Ruixin

    2016-05-01

    In a distributed radar track fusion system, it is desired to limit the communication rate between the sensors and the central node to only the most relevant information available. One way to do this is to use some metric that judges quantity of new information available, in comparison to that which has already been provided. The J-Divergence is a symmetric metric, derived from the Kullback-Liebler divergence, which performs a comparison of the statistical distance between two probability distributions. For the comparison between new and old data, a large J-Divergence can represent the existence of new information, while a small J-Divergence represents the lack of new information. Previous work included an application where the J-Divergence was used to limit data for scenarios in which the primary state estimator was an Extended Kalman Filter and used only Gaussian approximations at the local sensors. This paper expands the range of estimators to particle filters in order to account for situations where censoring is desired to be applied to non-linear/non-Gaussian environments. A derivation of the J-Divergence between probability density functions (PDFs) which are approximated by particles is provided for use in a non-feedback fusion case. An example application is given involving a 2D radar tracking scenario using the J-Divergences of a particle filter with the Gaussian approximation and a particle filter with the approximated discrete prior/posterior PDFs.

  2. Data fusion on a distributed heterogeneous sensor network.

    SciTech Connect

    Lamborn, Peter; Williams, Pamela J.

    2006-02-01

    Alarm-based sensor systems are being explored as a tool to expand perimeter security for facilities and force protection. However, the collection of increased sensor data has resulted in an insufficient solution that includes faulty data points. Data analysis is needed to reduce nuisance and false alarms, which will improve officials decision making and confidence levels in the system's alarms. Moreover, operational costs can be allayed and losses mitigated if authorities are alerted only when a real threat is detected. In the current system, heuristics such as persistence of alarm and type of sensor that detected an event are used to guide officials responses. We hypothesize that fusing data from heterogeneous sensors in the sensor field can provide more complete situational awareness than looking at individual sensor data. We propose a two stage approach to reduce false alarms. First, we use self organizing maps to cluster sensors based on global positioning coordinates and then train classifiers on the within cluster data to obtain a local view of the event. Next, we train a classifier on the local results to compute a global solution. We investigate the use of machine learning techniques, such as k-nearest neighbor, neural networks, and support vector machines to improve alarm accuracy. On simulated sensor data, the proposed approach identifies false alarms with greater accuracy than a weighted voting algorithm.

  3. Distributed sensor network for local-area atmospheric modeling

    NASA Astrophysics Data System (ADS)

    French, Patrick D.; Lovell, John S.; Seaman, Nelson L.

    2003-09-01

    In the event of a Weapons of Mass Destruction (WMD) chemical or radiological release, quick identification of the nature and source of the release can support efforts to warn, protect and evacuate threatened populations downwind; mitigate the release; provide more accurate plume forecasting; and collect critical transient evidence to help identify the perpetrator(s). Although there are systems available to assist in tracking a WMD release and then predicting where a plume may be traveling, there are no reliable systems available to determine the source location of that release. This would typically require the timely deployment of a remote sensing capability, a grid of expendable air samplers, or a surface sampling plan if the plume has dissipated. Each of these typical solutions has major drawbacks (i.e.: excessive cost, technical feasibility, duration to accomplish, etc...). This paper presents data to support the use of existing rapid-response meteorological modeling coupled with existing transport and diffusion modeling along with a prototype cost-effective situational awareness monitor which would reduce the sensor network requirements while still accomplishing the overall mission of having a 95% probability in converging on a source location within 100 meters.

  4. A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks

    NASA Technical Reports Server (NTRS)

    Bhaduri, Kanishka; Srivastava, Ashok N.

    2009-01-01

    This paper offers a local distributed algorithm for expectation maximization in large peer-to-peer environments. The algorithm can be used for a variety of well-known data mining tasks in a distributed environment such as clustering, anomaly detection, target tracking to name a few. This technology is crucial for many emerging peer-to-peer applications for bioinformatics, astronomy, social networking, sensor networks and web mining. Centralizing all or some of the data for building global models is impractical in such peer-to-peer environments because of the large number of data sources, the asynchronous nature of the peer-to-peer networks, and dynamic nature of the data/network. The distributed algorithm we have developed in this paper is provably-correct i.e. it converges to the same result compared to a similar centralized algorithm and can automatically adapt to changes to the data and the network. We show that the communication overhead of the algorithm is very low due to its local nature. This monitoring algorithm is then used as a feedback loop to sample data from the network and rebuild the model when it is outdated. We present thorough experimental results to verify our theoretical claims.

  5. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks

    PubMed Central

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S.

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the “critical degree” (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

  6. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

    PubMed

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology.

  7. Network effects across the earnings distribution: payoffs to visible and invisible job finding assistance.

    PubMed

    McDonald, Steve

    2015-01-01

    This study makes three critical contributions to the "Do Contacts Matter?" debate. First, the widely reported null relationship between informal job searching and wages is shown to be mostly the artifact of a coding error and sample selection restrictions. Second, previous analyses examined only active informal job searching without fully considering the benefits derived from unsolicited network assistance (the "invisible hand of social capital") - thereby underestimating the network effect. Third, wage returns to networks are examined across the earnings distribution. Longitudinal data from the NLSY reveal significant wage returns for network-based job finding over formal job searching, especially for individuals who were informally recruited into their jobs (non-searchers). Fixed effects quantile regression analyses show that contacts generate wage premiums among middle and high wage jobs, but not low wage jobs. These findings challenge conventional wisdom on contact effects and advance understanding of how social networks affect wage attainment and inequality.

  8. Network effects across the earnings distribution: payoffs to visible and invisible job finding assistance.

    PubMed

    McDonald, Steve

    2015-01-01

    This study makes three critical contributions to the "Do Contacts Matter?" debate. First, the widely reported null relationship between informal job searching and wages is shown to be mostly the artifact of a coding error and sample selection restrictions. Second, previous analyses examined only active informal job searching without fully considering the benefits derived from unsolicited network assistance (the "invisible hand of social capital") - thereby underestimating the network effect. Third, wage returns to networks are examined across the earnings distribution. Longitudinal data from the NLSY reveal significant wage returns for network-based job finding over formal job searching, especially for individuals who were informally recruited into their jobs (non-searchers). Fixed effects quantile regression analyses show that contacts generate wage premiums among middle and high wage jobs, but not low wage jobs. These findings challenge conventional wisdom on contact effects and advance understanding of how social networks affect wage attainment and inequality. PMID:25432620

  9. Mapping Systemic Risk: Critical Degree and Failures Distribution in Financial Networks.

    PubMed

    Smerlak, Matteo; Stoll, Brady; Gupta, Agam; Magdanz, James S

    2015-01-01

    The financial crisis illustrated the need for a functional understanding of systemic risk in strongly interconnected financial structures. Dynamic processes on complex networks being intrinsically difficult to model analytically, most recent studies of this problem have relied on numerical simulations. Here we report analytical results in a network model of interbank lending based on directly relevant financial parameters, such as interest rates and leverage ratios. We obtain a closed-form formula for the "critical degree" (the number of creditors per bank below which an individual shock can propagate throughout the network), and relate failures distributions to network topologies, in particular scalefree ones. Our criterion for the onset of contagion turns out to be isomorphic to the condition for cooperation to evolve on graphs and social networks, as recently formulated in evolutionary game theory. This remarkable connection supports recent calls for a methodological rapprochement between finance and ecology. PMID:26207631

  10. Modeling solute transport in distribution networks with variable demand and time step sizes.

    SciTech Connect

    Peyton, Chad E.; Bilisoly, Roger Lee; Buchberger, Steven G.; McKenna, Sean Andrew; Yarrington, Lane

    2004-06-01

    The effect of variable demands at short time scales on the transport of a solute through a water distribution network has not previously been studied. We simulate flow and transport in a small water distribution network using EPANET to explore the effect of variable demand on solute transport across a range of hydraulic time step scales from 1 minute to 2 hours. We show that variable demands at short time scales can have the following effects: smoothing of a pulse of tracer injected into a distribution network and increasing the variability of both the transport pathway and transport timing through the network. Variable demands are simulated for these different time step sizes using a previously developed Poisson rectangular pulse (PRP) demand generator that considers demand at a node to be a combination of exponentially distributed arrival times with log-normally distributed intensities and durations. Solute is introduced at a tank and at three different network nodes and concentrations are modeled through the system using the Lagrangian transport scheme within EPANET. The transport equations within EPANET assume perfect mixing of the solute within a parcel of water and therefore physical dispersion cannot occur. However, variation in demands along the solute transport path contribute to both removal and distortion of the injected pulse. The model performance measures examined are the distribution of the Reynolds number, the variation in the center of mass of the solute across time, and the transport path and timing of the solute through the network. Variation in all three performance measures is greatest at the shortest time step sizes. As the scale of the time step increases, the variability in these performance measures decreases. The largest time steps produce results that are inconsistent with the results produced by the smaller time steps.

  11. Improved Cost-Base Design of Water Distribution Networks using Genetic Algorithm

    NASA Astrophysics Data System (ADS)

    Moradzadeh Azar, Foad; Abghari, Hirad; Taghi Alami, Mohammad; Weijs, Steven

    2010-05-01

    Population growth and progressive extension of urbanization in different places of Iran cause an increasing demand for primary needs. The water, this vital liquid is the most important natural need for human life. Providing this natural need is requires the design and construction of water distribution networks, that incur enormous costs on the country's budget. Any reduction in these costs enable more people from society to access extreme profit least cost. Therefore, investment of Municipal councils need to maximize benefits or minimize expenditures. To achieve this purpose, the engineering design depends on the cost optimization techniques. This paper, presents optimization models based on genetic algorithm(GA) to find out the minimum design cost Mahabad City's (North West, Iran) water distribution network. By designing two models and comparing the resulting costs, the abilities of GA were determined. the GA based model could find optimum pipe diameters to reduce the design costs of network. Results show that the water distribution network design using Genetic Algorithm could lead to reduction of at least 7% in project costs in comparison to the classic model. Keywords: Genetic Algorithm, Optimum Design of Water Distribution Network, Mahabad City, Iran.

  12. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

    PubMed

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states. PMID:26283956

  13. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states

    PubMed Central

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states. PMID:26283956

  14. Synaptic dynamics and neuronal network connectivity are reflected in the distribution of times in Up states.

    PubMed

    Dao Duc, Khanh; Parutto, Pierre; Chen, Xiaowei; Epsztein, Jérôme; Konnerth, Arthur; Holcman, David

    2015-01-01

    The dynamics of neuronal networks connected by synaptic dynamics can sustain long periods of depolarization that can last for hundreds of milliseconds such as Up states recorded during sleep or anesthesia. Yet the underlying mechanism driving these periods remain unclear. We show here within a mean-field model that the residence time of the neuronal membrane potential in cortical Up states does not follow a Poissonian law, but presents several peaks. Furthermore, the present modeling approach allows extracting some information about the neuronal network connectivity from the time distribution histogram. Based on a synaptic-depression model, we find that these peaks, that can be observed in histograms of patch-clamp recordings are not artifacts of electrophysiological measurements, but rather are an inherent property of the network dynamics. Analysis of the equations reveals a stable focus located close to the unstable limit cycle, delimiting a region that defines the Up state. The model further shows that the peaks observed in the Up state time distribution are due to winding around the focus before escaping from the basin of attraction. Finally, we use in vivo recordings of intracellular membrane potential and we recover from the peak distribution, some information about the network connectivity. We conclude that it is possible to recover the network connectivity from the distribution of times that the neuronal membrane voltage spends in Up states.

  15. Distribution of orientation selectivity in recurrent networks of spiking neurons with different random topologies.

    PubMed

    Sadeh, Sadra; Rotter, Stefan

    2014-01-01

    Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity.

  16. Distribution of Orientation Selectivity in Recurrent Networks of Spiking Neurons with Different Random Topologies

    PubMed Central

    Sadeh, Sadra; Rotter, Stefan

    2014-01-01

    Neurons in the primary visual cortex are more or less selective for the orientation of a light bar used for stimulation. A broad distribution of individual grades of orientation selectivity has in fact been reported in all species. A possible reason for emergence of broad distributions is the recurrent network within which the stimulus is being processed. Here we compute the distribution of orientation selectivity in randomly connected model networks that are equipped with different spatial patterns of connectivity. We show that, for a wide variety of connectivity patterns, a linear theory based on firing rates accurately approximates the outcome of direct numerical simulations of networks of spiking neurons. Distance dependent connectivity in networks with a more biologically realistic structure does not compromise our linear analysis, as long as the linearized dynamics, and hence the uniform asynchronous irregular activity state, remain stable. We conclude that linear mechanisms of stimulus processing are indeed responsible for the emergence of orientation selectivity and its distribution in recurrent networks with functionally heterogeneous synaptic connectivity. PMID:25469704

  17. Sampling cluster stability for peer-to-peer based content distribution networks

    NASA Astrophysics Data System (ADS)

    Darlagiannis, Vasilios; Mauthe, Andreas; Steinmetz, Ralf

    2006-01-01

    Several types of Content Distribution Networks are being deployed over the Internet today, based on different architectures to meet their requirements (e.g., scalability, efficiency and resiliency). Peer-to-Peer (P2P) based Content Distribution Networks are promising approaches that have several advantages. Structured P2P networks, for instance, take a proactive approach and provide efficient routing mechanisms. Nevertheless, their maintenance can increase considerably in highly dynamic P2P environments. In order to address this issue, a two-tier architecture that combines a structured overlay network with a clustering mechanism is suggested in a hybrid scheme. In this paper, we examine several sampling algorithms utilized in the aforementioned hybrid network that collect local information in order to apply a selective join procedure. The algorithms are based mostly on random walks inside the overlay network. The aim of the selective join procedure is to provide a well balanced and stable overlay infrastructure that can easily overcome the unreliable behavior of the autonomous peers that constitute the network. The sampling algorithms are evaluated using simulation experiments where several properties related to the graph structure are revealed.

  18. OCEAN-PC and a distributed network for ocean data

    NASA Technical Reports Server (NTRS)

    Mclain, Douglas R.

    1992-01-01

    The Intergovernmental Oceanographic Commission (IOC) wishes to develop an integrated software package for oceanographic data entry and access in developing countries. The software, called 'OCEAN-PC', would run on low cost PC microcomputers and would encourage and standardize: (1) entry of local ocean observations; (2) quality control of the local data; (3) merging local data with historical data; (4) improved display and analysis of the merged data; and (5) international data exchange. OCEAN-PC will link existing MS-DOS oceanographic programs and data sets with table-driven format conversions. Since many ocean data sets are now being distributed on optical discs (Compact Discs - Read Only Memory, CD-ROM, Mass et al. 1987), OCEAN-PC will emphasize access to CD-ROMs.

  19. Degree Distribution of Position-Dependent Ball-Passing Networks in Football Games

    NASA Astrophysics Data System (ADS)

    Narizuka, Takuma; Yamamoto, Ken; Yamazaki, Yoshihiro

    2015-08-01

    We propose a simple stochastic model describing the position-dependent ball-passing network in football (soccer) games. In this network, a player in a certain area in a divided field is a node, and a pass between two nodes corresponds to an edge. Our stochastic process model is characterized by the consecutive choice of a node depending on its intrinsic fitness. We derive an explicit expression for the degree distribution and find that the derived distribution reproduces that for actual data reasonably well.

  20. Characterizing short-term stability for Boolean networks over any distribution of transfer functions

    NASA Astrophysics Data System (ADS)

    Seshadhri, C.; Smith, Andrew M.; Vorobeychik, Yevgeniy; Mayo, Jackson R.; Armstrong, Robert C.

    2016-07-01

    We present a characterization of short-term stability of Kauffman's N K (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness.

  1. Subcarrier Wave Quantum Key Distribution in Telecommunication Network with Bitrate 800 kbit/s

    NASA Astrophysics Data System (ADS)

    Gleim, A. V.; Nazarov, Yu. V.; Egorov, V. I.; Smirnov, S. V.; Bannik, O. I.; Chistyakov, V. V.; Kynev, S. M.; Anisimov, A. A.; Kozlov, S. A.; Vasiliev, V. N.

    2015-09-01

    In the course of work on creating the first quantum communication network in Russia we demonstrated quantum key distribution in metropolitan optical network infrastructure. A single-pass subcarrier wave quantum cryptography scheme was used in the experiments. BB84 protocol with strong reference was chosen for performing key distribution. The registered sifted key rate in an optical cable with 1.5 dB loss was 800 Kbit/s. Signal visibility exceeded 98%, and quantum bit error rate value was 1%. The achieved result is a record for this type of systems.

  2. Analysis and research on the balanced distribution of the network-based data in parallel database

    NASA Astrophysics Data System (ADS)

    He, JunHua

    2011-12-01

    The rapid development of parallel computer systems, making parallel operating environment gradually mature and widely used in scientific computing and research in many fields, thus parallel database of research becomes more and more attention and research has become an important database field of study. This network-based parallel cluster of characteristics and the current parallel computer system new trends, analyzes the network parallel clusters of workstations, parallel database data skew problem in data distribution characteristics of the environment is proposed with the ability to adapt to the dynamic data balanced distribution programs.

  3. Characterizing short-term stability for Boolean networks over any distribution of transfer functions.

    PubMed

    Seshadhri, C; Smith, Andrew M; Vorobeychik, Yevgeniy; Mayo, Jackson R; Armstrong, Robert C

    2016-07-01

    We present a characterization of short-term stability of Kauffman's NK (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness. PMID:27575142

  4. Characterizing short-term stability for Boolean networks over any distribution of transfer functions.

    PubMed

    Seshadhri, C; Smith, Andrew M; Vorobeychik, Yevgeniy; Mayo, Jackson R; Armstrong, Robert C

    2016-07-01

    We present a characterization of short-term stability of Kauffman's NK (random) Boolean networks under arbitrary distributions of transfer functions. Given such a Boolean network where each transfer function is drawn from the same distribution, we present a formula that determines whether short-term chaos (damage spreading) will happen. Our main technical tool which enables the formal proof of this formula is the Fourier analysis of Boolean functions, which describes such functions as multilinear polynomials over the inputs. Numerical simulations on mixtures of threshold functions and nested canalyzing functions demonstrate the formula's correctness.

  5. Optical-network-connected multi-channel 96-GHz-band distributed radar system

    NASA Astrophysics Data System (ADS)

    Kanno, Atsushi; Kuri, Toshiaki; Kawanishi, Tetsuya

    2015-05-01

    The millimeter-wave (MMW) radar is a promising candidate for high-precision imaging because of its short wavelength and broad range of available bandwidths. In particular in the frequency range of 92-100 GHz, which is regulated for radiolocation, an atmospheric attenuation coefficient less than 1 dB/km limits the imaging range. Therefore, a combination of MMW radar and distributed antenna system directly connected to optical fiber networks can realize both high-precision imaging and large-area surveillance. In this paper, we demonstrate a multi-channel MMW frequency-modulated continuous-wave distributed radar system connected to an analog radio-over-fiber network.

  6. Distributed Permafrost Observation Network in Western Alaska: the First Results

    NASA Astrophysics Data System (ADS)

    Romanovsky, V. E.; Cable, W.; Marchenko, S. S.; Panda, S. K.

    2014-12-01

    The area of Western Alaska including the Selawik National Wildlife Refuge (SNWR) is generally underrepresented in terms of permafrost thermal monitoring. Thus, the main objective of this study was to establish a permafrost monitoring network in Western Alaska in order to understand the spatial variability in permafrost thermal regime in the area and to have a baseline in order to detect future change. Present and future thawing of permafrost in the region will have a dramatic effect on the ecosystems and infrastructure because the permafrost here generally has a high ice content, as a result of preservation of old ground ice in these relatively cold regions even during the warmer time intervals of the Holocene. Over the summers of 2011 and 2012 a total of 26 automated monitoring stations were established to collect temperature data from the active layer and near-surface permafrost. While most of these stations were basic and only measured the temperature down to 1.5 m at 4 depths, three of the stations had higher vertical temperature resolution down to 3 m. The sites were selected using an ecotype (basic vegetation groups) map of very high resolution (30 m) that had been created for the area in 2009. We found the Upland Dwarf Birch-Tussock Shrub ecotype to be the coldest with a mean annual ground temperature at 1 meter (MAGT1.0) of -3.9 °C during the August 1st, 2012 to July 31st, 2013 measurement period. This is also the most widespread ecotype in the SNWR, covering approximately 28.4% by area. The next widespread ecotype in the SNWR is the Lowland and Upland Birch-Ericaceous Low Shrub. This ecotype had higher ground temperatures with an average MAGT1.0 of -2.4 °C during the same measurement period. We also found that within some ecotypes (White Spruce and Alder-Willow Shrub) the presence or absence of moss on the surface seems to indicate the presence or absence of near surface permafrost. In general, we found good agreement between ecotype classes and

  7. A Distributed Transmission Rate Adjustment Algorithm in Heterogeneous CSMA/CA Networks

    PubMed Central

    Xie, Shuanglong; Low, Kay Soon; Gunawan, Erry

    2015-01-01

    Distributed transmission rate tuning is important for a wide variety of IEEE 802.15.4 network applications such as industrial network control systems. Such systems often require each node to sustain certain throughput demand in order to guarantee the system performance. It is thus essential to determine a proper transmission rate that can meet the application requirement and compensate for network imperfections (e.g., packet loss). Such a tuning in a heterogeneous network is difficult due to the lack of modeling techniques that can deal with the heterogeneity of the network as well as the network traffic changes. In this paper, a distributed transmission rate tuning algorithm in a heterogeneous IEEE 802.15.4 CSMA/CA network is proposed. Each node uses the results of clear channel assessment (CCA) to estimate the busy channel probability. Then a mathematical framework is developed to estimate the on-going heterogeneous traffics using the busy channel probability at runtime. Finally a distributed algorithm is derived to tune the transmission rate of each node to accurately meet the throughput requirement. The algorithm does not require modifications on IEEE 802.15.4 MAC layer and it has been experimentally implemented and extensively tested using TelosB nodes with the TinyOS protocol stack. The results reveal that the algorithm is accurate and can satisfy the throughput demand. Compared with existing techniques, the algorithm is fully distributed and thus does not require any central coordination. With this property, it is able to adapt to traffic changes and re-adjust the transmission rate to the desired level, which cannot be achieved using the traditional modeling techniques. PMID:25822140

  8. On the Relevancy of Efficient, Integrated Computer and Network Monitoring in HEP Distributed Online Environment

    NASA Astrophysics Data System (ADS)

    Carvalho, D.; Gavillet, Ph.; Delgado, V.; Albert, J. N.; Bellas, N.; Javello, J.; Miere, Y.; Ruffinoni, D.; Smith, G.

    Large Scientific Equipments are controlled by Computer Systems whose complexity is growing driven, on the one hand by the volume and variety of the information, its distributed nature, the sophistication of its treatment and, on the other hand by the fast evolution of the computer and network market. Some people call them genetically Large-Scale Distributed Data Intensive Information Systems or Distributed Computer Control Systems (DCCS) for those systems dealing more with real time control. Taking advantage of (or forced by) the distributed architecture, the tasks are more and more often implemented as Client-Server applications. In this framework the monitoring of the computer nodes, the communications network and the applications becomes of primary importance for ensuring the safe running and guaranteed performance of the system. With the future generation of HEP experiments, such as those at the LHC in view, it is proposed to integrate the various functions of DCCS monitoring into one general purpose Multi-layer System.

  9. Learning signaling network structures with sparsely distributed data.

    PubMed

    Sachs, Karen; Itani, Solomon; Carlisle, Jennifer; Nolan, Garry P; Pe'er, Dana; Lauffenburger, Douglas A

    2009-02-01

    Flow cytometric measurement of signaling protein abundances has proved particularly useful for elucidation of signaling pathway structure. The single cell nature of the data ensures a very large dataset size, providing a statistically robust dataset for structure learning. Moreover, the approach is easily scaled to many conditions in high throughput. However, the technology suffers from a dimensionality constraint: at the cutting edge, only about 12 protein species can be measured per cell, far from sufficient for most signaling pathways. Because the structure learning algorithm (in practice) requires that all variables be measured together simultaneously, this restricts structure learning to the number of variables that constitute the flow cytometer's upper dimensionality limit. To address this problem, we present here an algorithm that enables structure learning for sparsely distributed data, allowing structure learning beyond the measurement technology's upper dimensionality limit for simultaneously measurable variables. The algorithm assesses pairwise (or n-wise) dependencies, constructs "Markov neighborhoods" for each variable based on these dependencies, measures each variable in the context of its neighborhood, and performs structure learning using a constrained search.

  10. Search for function coefficient distribution in traditional Chinese medicine network

    NASA Astrophysics Data System (ADS)

    He, Yue; Zhang, Peipei; Sun, Anzheng; Su, Beibei; He, Da-Ren

    2004-03-01

    We suggest a model for a simulation on development of traditional Chinese medicine system. Suppose there are a certain number of Chinese medicines. Each of them is given randomly a "function coefficient", which has a value between 0 and 1. The larger it is the stronger is its function for solving one healthy problem and serving as an "emperor" in a prescription formulation. The smaller it is the stronger is its function for harmonizing and/or accessorizing a prescription formulation. In every step of time a new medicine is discovered. With a probability, P(m), which is determined according to our statistical investigation results, it can produce a new prescription formulation with other m-1 medicines. We assume that the probability for choosing the function coefficients of these m medicines follow a distribution function, which is everywhere smooth. A program has been set up to perform a search for this function form so that the simulation results show a best agreement to our statistical data. We believe the result function form will be helpful for an understanding on real development of traditional Chinese medicine system.

  11. Biology-Inspired Distributed Consensus in Massively-Deployed Sensor Networks

    NASA Technical Reports Server (NTRS)

    Jones, Kennie H.; Lodding, Kenneth N.; Olariu, Stephan; Wilson, Larry; Xin, Chunsheng

    2005-01-01

    Promises of ubiquitous control of the physical environment by large-scale wireless sensor networks open avenues for new applications that are expected to redefine the way we live and work. Most of recent research has concentrated on developing techniques for performing relatively simple tasks in small-scale sensor networks assuming some form of centralized control. The main contribution of this work is to propose a new way of looking at large-scale sensor networks, motivated by lessons learned from the way biological ecosystems are organized. Indeed, we believe that techniques used in small-scale sensor networks are not likely to scale to large networks; that such large-scale networks must be viewed as an ecosystem in which the sensors/effectors are organisms whose autonomous actions, based on local information, combine in a communal way to produce global results. As an example of a useful function, we demonstrate that fully distributed consensus can be attained in a scalable fashion in massively deployed sensor networks where individual motes operate based on local information, making local decisions that are aggregated across the network to achieve globally-meaningful effects.

  12. A distributed general multi-sensor cardinalized probability hypothesis density (CPHD) filter for sensor networks

    NASA Astrophysics Data System (ADS)

    Datta Gupta, S.; Nannuru, S.; Coates, M.; Rabbat, M.

    2015-05-01

    We develop a distributed cardinalized probability hypothesis density (CPHD) filter that can be deployed in a sensor network to process the measurements of multiple sensors that make conditionally independent measurements. In contrast to the majority of the related work, which involves performing local filter updates and then exchanging data to fuse the local intensity functions and cardinality distributions, we strive to approximate the update step that a centralized multi-sensor CPHD filter would perform.

  13. Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network.

    PubMed

    Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N

    2015-01-01

    Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

  14. Bayes Node Energy Polynomial Distribution to Improve Routing in Wireless Sensor Network

    PubMed Central

    Palanisamy, Thirumoorthy; Krishnasamy, Karthikeyan N.

    2015-01-01

    Wireless Sensor Network monitor and control the physical world via large number of small, low-priced sensor nodes. Existing method on Wireless Sensor Network (WSN) presented sensed data communication through continuous data collection resulting in higher delay and energy consumption. To conquer the routing issue and reduce energy drain rate, Bayes Node Energy and Polynomial Distribution (BNEPD) technique is introduced with energy aware routing in the wireless sensor network. The Bayes Node Energy Distribution initially distributes the sensor nodes that detect an object of similar event (i.e., temperature, pressure, flow) into specific regions with the application of Bayes rule. The object detection of similar events is accomplished based on the bayes probabilities and is sent to the sink node resulting in minimizing the energy consumption. Next, the Polynomial Regression Function is applied to the target object of similar events considered for different sensors are combined. They are based on the minimum and maximum value of object events and are transferred to the sink node. Finally, the Poly Distribute algorithm effectively distributes the sensor nodes. The energy efficient routing path for each sensor nodes are created by data aggregation at the sink based on polynomial regression function which reduces the energy drain rate with minimum communication overhead. Experimental performance is evaluated using Dodgers Loop Sensor Data Set from UCI repository. Simulation results show that the proposed distribution algorithm significantly reduce the node energy drain rate and ensure fairness among different users reducing the communication overhead. PMID:26426701

  15. States of mind: emotions, body feelings, and thoughts share distributed neural networks.

    PubMed

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

    2012-09-01

    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

  16. Beyond motor scheme: a supramodal distributed representation in the action-observation network.

    PubMed

    Ricciardi, Emiliano; Handjaras, Giacomo; Bonino, Daniela; Vecchi, Tomaso; Fadiga, Luciano; Pietrini, Pietro

    2013-01-01

    The representation of actions within the action-observation network is thought to rely on a distributed functional organization. Furthermore, recent findings indicate that the action-observation network encodes not merely the observed motor act, but rather a representation that is independent from a specific sensory modality or sensory experience. In the present study, we wished to determine to what extent this distributed and 'more abstract' representation of action is truly supramodal, i.e. shares a common coding across sensory modalities. To this aim, a pattern recognition approach was employed to analyze neural responses in sighted and congenitally blind subjects during visual and/or auditory presentation of hand-made actions. Multivoxel pattern analyses-based classifiers discriminated action from non-action stimuli across sensory conditions (visual and auditory) and experimental groups (blind and sighted). Moreover, these classifiers labeled as 'action' the pattern of neural responses evoked during actual motor execution. Interestingly, discriminative information for the action/non action classification was located in a bilateral, but left-prevalent, network that strongly overlaps with brain regions known to form the action-observation network and the human mirror system. The ability to identify action features with a multivoxel pattern analyses-based classifier in both sighted and blind individuals and independently from the sensory modality conveying the stimuli clearly supports the hypothesis of a supramodal, distributed functional representation of actions, mainly within the action-observation network.

  17. Beyond Motor Scheme: A Supramodal Distributed Representation in the Action-Observation Network

    PubMed Central

    Ricciardi, Emiliano; Handjaras, Giacomo; Bonino, Daniela; Vecchi, Tomaso; Fadiga, Luciano; Pietrini, Pietro

    2013-01-01

    The representation of actions within the action-observation network is thought to rely on a distributed functional organization. Furthermore, recent findings indicate that the action-observation network encodes not merely the observed motor act, but rather a representation that is independent from a specific sensory modality or sensory experience. In the present study, we wished to determine to what extent this distributed and ‘more abstract’ representation of action is truly supramodal, i.e. shares a common coding across sensory modalities. To this aim, a pattern recognition approach was employed to analyze neural responses in sighted and congenitally blind subjects during visual and/or auditory presentation of hand-made actions. Multivoxel pattern analyses-based classifiers discriminated action from non-action stimuli across sensory conditions (visual and auditory) and experimental groups (blind and sighted). Moreover, these classifiers labeled as ‘action’ the pattern of neural responses evoked during actual motor execution. Interestingly, discriminative information for the action/non action classification was located in a bilateral, but left-prevalent, network that strongly overlaps with brain regions known to form the action-observation network and the human mirror system. The ability to identify action features with a multivoxel pattern analyses-based classifier in both sighted and blind individuals and independently from the sensory modality conveying the stimuli clearly supports the hypothesis of a supramodal, distributed functional representation of actions, mainly within the action-observation network. PMID:23472216

  18. 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

  19. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach.

  20. Fundamentally Distributed Information Processing Integrates the Motor Network into the Mental Workspace during Mental Rotation.

    PubMed

    Schlegel, Alexander; Konuthula, Dedeepya; Alexander, Prescott; Blackwood, Ethan; Tse, Peter U

    2016-08-01

    The manipulation of mental representations in the human brain appears to share similarities with the physical manipulation of real-world objects. In particular, some neuroimaging studies have found increased activity in motor regions during mental rotation, suggesting that mental and physical operations may involve overlapping neural populations. Does the motor network contribute information processing to mental rotation? If so, does it play a similar computational role in both mental and manual rotation, and how does it communicate with the wider network of areas involved in the mental workspace? Here we used multivariate methods and fMRI to study 24 participants as they mentally rotated 3-D objects or manually rotated their hands in one of four directions. We find that information processing related to mental rotations is distributed widely among many cortical and subcortical regions, that the motor network becomes tightly integrated into a wider mental workspace network during mental rotation, and that motor network activity during mental rotation only partially resembles that involved in manual rotation. Additionally, these findings provide evidence that the mental workspace is organized as a distributed core network that dynamically recruits specialized subnetworks for specific tasks as needed. PMID:27054403

  1. Quantum key distribution for security guarantees over QoS-driven 3D satellite networks

    NASA Astrophysics Data System (ADS)

    Wang, Ping; Zhang, Xi; Chen, Genshe; Pham, Khanh; Blasch, Erik

    2014-06-01

    In recent years, quantum-based communication is emerging as a new technique for ensuring secured communications because it can guarantee absolute security between two different remote entities. Quantum communication performs the transmission and exchange of quantum information among distant nodes within a network. Quantum key distribution (QKD) is a methodology for generating and distributing random encryption keys using the principles of quantum physics. In this paper, we investigate the techniques on how to efficiently use QKD in 3D satellite networks and propose an effective method to overcome its communications-distance limitations. In order to implement secured and reliable communications over wireless satellite links, we develop a free-space quantum channel model in satellite communication networks. To enlarge the communications distances over 3D satellite networks, we propose to employ the intermediate nodes to relay the unconditional keys and guarantee the Quantum Bit Error Rate (QBER) for security requirement over 3D satellite networks. We also propose the communication model for QKD security-Quality of Service (QoS) guarantee and an adaptive cooperative routing selection scheme to optimize the throughput performance of QKD-based satellite communications networks. The obtained simulation results verify our proposed schemes.

  2. Efficient Allocation of Resources for Defense of Spatially Distributed Networks Using Agent-Based Simulation.

    PubMed

    Kroshl, William M; Sarkani, Shahram; Mazzuchi, Thomas A

    2015-09-01

    This article presents ongoing research that focuses on efficient allocation of defense resources to minimize the damage inflicted on a spatially distributed physical network such as a pipeline, water system, or power distribution system from an attack by an active adversary, recognizing the fundamental difference between preparing for natural disasters such as hurricanes, earthquakes, or even accidental systems failures and the problem of allocating resources to defend against an opponent who is aware of, and anticipating, the defender's efforts to mitigate the threat. Our approach is to utilize a combination of integer programming and agent-based modeling to allocate the defensive resources. We conceptualize the problem as a Stackelberg "leader follower" game where the defender first places his assets to defend key areas of the network, and the attacker then seeks to inflict the maximum damage possible within the constraints of resources and network structure. The criticality of arcs in the network is estimated by a deterministic network interdiction formulation, which then informs an evolutionary agent-based simulation. The evolutionary agent-based simulation is used to determine the allocation of resources for attackers and defenders that results in evolutionary stable strategies, where actions by either side alone cannot increase its share of victories. We demonstrate these techniques on an example network, comparing the evolutionary agent-based results to a more traditional, probabilistic risk analysis (PRA) approach. Our results show that the agent-based approach results in a greater percentage of defender victories than does the PRA-based approach. PMID:25683347

  3. An Integrated Distributed Watershed Model with Channel Network for Rainfall Runoff Simulation

    NASA Astrophysics Data System (ADS)

    Keesara, V.; T. I., E.; E. P., R.; A. T., K.

    2008-05-01

    Over the years, the demand on water resources has increased due to population and industrial growth. This high demand and less availability of fresh water necessitate management of available water resources in a sustainable way. In a watershed perspective, spatial and temporal estimation of runoff is important for the sustainable management of water resources. Owing to the importance and complexity of runoff process in a watershed, it has to be simulated by physically based models, which are based on physical laws governing the phenomena. In natural watersheds after overland flow enters into channels, the flow takes place through dendritic channel networks. The channel flow component has to be simulated as flow occurs in network of channels. Finite Element Method (FEM) has inherent advantages to solve the governing equations describing the runoff. Geographical Information Systems (GIS) is useful in storing, retrieving and managing data required by the physically distributed models. In the present study, distributed rainfall runoff model constitutes overland flow model and channel network model. The overland flow has been simulated as flow occurring on overland flow strips, which constitutes overland flow elements using overland flow model. This overland flow reaches channels as lateral inflow which is routed through a network of channels using channel network model. Diffusion wave equations, which are solved numerically using FEM, have been used to evaluate the runoff. Philip infiltration model has been chosen to compute the infiltration. Interflow model has been used to simulate the excess runoff, to account the exfiltration in this watershed. GIS has been used to prepare the input data required for the distributed model. The channel network based distributed model has been applied to Peacheater Creek watershed in USA. The data required for Peacheater Creek watershed was obtained from Distributed Model Intercomparison Project (DMIP). ARC/INFO software was used to

  4. Low-Power RF SOI-CMOS Technology for Distributed Sensor Networks

    NASA Technical Reports Server (NTRS)

    Dogan, Numan S.

    2003-01-01

    The objective of this work is to design and develop Low-Power RF SOI-CMOS Technology for Distributed Sensor Networks. We briefly report on the accomplishments in this work. We also list the impact of this work on graduate student research training/involvement.

  5. TALON - The Telescope Alert Operation Network System : intelligent linking of distributed autonomous robotic telescopes

    SciTech Connect

    White, R. R.; Wren, J.; Davis, H. R.; Galassi, M. C.; Starr, D. L.; Vestrand, W. T.; Wozniak, P. R.

    2004-01-01

    The internet has brought about great change in the astronomical community, but this interconnectivity is just starting to be exploited for use in instrumentation. Utilizing the internet for communicating between distributed astronomical systems is still in its infancy, but it already shows great potential. Here we present an example of a distributed network of telescopes that performs more efficienfiy in synchronous operation than as individual instruments. RAPid Telescopes for Optical Response (RAPTOR) is a system of telescopes at LANL that has intelligent intercommunication, combined with wide-field optics, temporal monitoring software, and deep-field follow-up capability all working in closed-loop real-time operation. The Telescope ALert Operations Network (TALON) is a network server that allows intercommunication of alert triggers from external and internal resources and controls the distribution of these to each of the telescopes on the network. TALON is designed to grow, allowing any number of telescopes to be linked together and communicate. Coupled with an intelligent alert client at each telescope, it can analyze and respond to each distributed TALON alert based on the telescopes needs and schedule.

  6. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks -journal article

    EPA Science Inventory

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Wate...

  7. Water Quality Modeling in the Dead End Sections of Drinking Water Distribution Networks

    EPA Science Inventory

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Wate...

  8. Modeling Multiple Human-Automation Distributed Systems using Network-form Games

    NASA Technical Reports Server (NTRS)

    Brat, Guillaume

    2012-01-01

    The paper describes at a high-level the network-form game framework (based on Bayes net and game theory), which can be used to model and analyze safety issues in large, distributed, mixed human-automation systems such as NextGen.

  9. LandScape Command Set: Local Area Network Distributed Supervisory Control and Programming Environment

    SciTech Connect

    Burchard, R.L.; Small, D.E.

    1999-01-01

    This paper presents the Local Area Network Distributed Supervisory Control and Programming Environment (LandScape) commands set that provides a Generic Device Subsystem Application Programmers Interface (API). These commands are implemented using the Common Object Request Broker Architecture (CORBA) specification with Orbix from Iona Technologies.

  10. Developing A Modeling Tool for Flow Profiling in Irrigation Distribution Network

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Efforts are underway to rehabilitate the irrigation districts, such as in the Rio Grande River Basin in Texas. Water distribution network models are needed to help prioritize and analyze various rehabilitation options, as well as to scientifically quantify irrigation water demands, usages, and losse...

  11. Variable-Length Message Transmission for Distributed Loop Computer Networks (Part I).

    ERIC Educational Resources Information Center

    Reames, C. C.; Liu, M. T.

    An introduction to the problems of variable-length message transmission in distributed loop computer networks, with a summary of previous accomplishments in the area, begins this technically-oriented document. An improved technique, overcoming some of the inadequacies in presently used techniques, is proposed together with a conceptual model of…

  12. Unified Framework for Deriving Simultaneous Equation Algorithms for Water Distribution Networks

    EPA Science Inventory

    The known formulations for steady state hydraulics within looped water distribution networks are re-derived in terms of linear and non-linear transformations of the original set of partly linear and partly non-linear equations that express conservation of mass and energy. All of ...

  13. Parallel distributed processing and neural networks: origins, methodology and cognitive functions.

    PubMed

    Parks, R W; Long, D L; Levine, D S; Crockett, D J; McGeer, E G; McGeer, P L; Dalton, I E; Zec, R F; Becker, R E; Coburn, K L

    1991-10-01

    Parallel Distributed Processing (PDP), a computational methodology with origins in Associationism, is used to provide empirical information regarding neurobiological systems. Recently, supercomputers have enabled neuroscientists to model brain behavior-relationships. An overview of supercomputer architecture demonstrates the advantages of parallel over serial processing. Histological data provide physical evidence of the parallel distributed nature of certain aspects of the human brain, as do corresponding computer simulations. Whereas sensory networks follow more sequential neural network pathways, in vivo brain imaging studies of attention and rudimentary language tasks appear to involve multiple cortical and subcortical areas. Controversy remains as to whether associative models or Artificial Intelligence symbolic models better reflect neural networks of cognitive functions; however, considerable interest has shifted towards associative models.

  14. Video distribution techniques over WiMAX networks for m-Health applications.

    PubMed

    Markarian, Garik; Mihaylova, Lyudmila; Tsitserov, Dmitry V; Zvikhachevskaya, A

    2012-01-01

    In this paper, we propose a novel approach for video distribution over IEEE 802.16 networks for mobile Healthcare (m-Health) applications. The technique incorporates resource distribution, scheduling, and content-aware video streaming taking advantage of a flexible quality of service functionality offered by IEEE 802.16/WiMAX technology. The proposed technique is thoroughly investigated using network simulator software under various real-life m-Health scenarios, which include streaming video over medium access control layer service connections. It is shown that the technique is fully compatible with the WiMAX standard specification and allows a 9-16% increase in the overall network throughput, which is dependent upon the initial system configuration and the selection of WiMAX user parameters. PMID:22057065

  15. A statistical model for the length distribution of meshes in a polymer network

    NASA Astrophysics Data System (ADS)

    Lang, M.; Michalke, W.; Kreitmeier, S.

    2001-05-01

    A statistical model is introduced which allows estimation of the length distribution of meshes in a unimodal polymer network. The length distribution is responsible for the type and number of entanglements in a network and can thus provide information about the deformation behavior of polymers. The model can also predict the influence of certain simulation parameters such as the degree of cross linkage, the chain length, or the density of the melt from which the network is built. Both a reaction- and a diffusion-controlled cross-linking process can be mapped. We found that a shorter chain length implies a smaller number of chains per mesh. An increase of the degree of cross linkage as well as a lowering of the density of the melt also leads to a smaller average length of the meshes.

  16. Video distribution techniques over WiMAX networks for m-Health applications.

    PubMed

    Markarian, Garik; Mihaylova, Lyudmila; Tsitserov, Dmitry V; Zvikhachevskaya, A

    2012-01-01

    In this paper, we propose a novel approach for video distribution over IEEE 802.16 networks for mobile Healthcare (m-Health) applications. The technique incorporates resource distribution, scheduling, and content-aware video streaming taking advantage of a flexible quality of service functionality offered by IEEE 802.16/WiMAX technology. The proposed technique is thoroughly investigated using network simulator software under various real-life m-Health scenarios, which include streaming video over medium access control layer service connections. It is shown that the technique is fully compatible with the WiMAX standard specification and allows a 9-16% increase in the overall network throughput, which is dependent upon the initial system configuration and the selection of WiMAX user parameters.

  17. Distributed adaptive pinning control for cluster synchronization of nonlinearly coupled Lur'e networks

    NASA Astrophysics Data System (ADS)

    Tang, Ze; Park, Ju H.; Lee, Tae H.

    2016-10-01

    This paper is devoted to the cluster synchronization issue of nonlinearly coupled Lur'e networks under the distributed adaptive pinning control strategy. The time-varying delayed networks consisted of identical and nonidentical Lur'e systems are discussed respectively by applying the edge-based pinning control scheme. In each cluster, the edges belonging to the spanning tree are pinned. In view of the nonlinearly couplings of the networks, for the first time, an efficient distributed nonlinearly adaptive update law based on the local information of the dynamical behaviors of node is proposed. Sufficient criteria for the achievement of cluster synchronization are derived based on S-procedure, Kronecker product and Lyapunov stability theory. Additionally, some illustrative examples are provided to demonstrate the effectiveness of the theoretical results.

  18. Measurement-Device-Independent Quantum Key Distribution over Untrustful Metropolitan Network

    NASA Astrophysics Data System (ADS)

    Tang, Yan-Lin; Yin, Hua-Lei; Zhao, Qi; Liu, Hui; Sun, Xiang-Xiang; Huang, Ming-Qi; Zhang, Wei-Jun; Chen, Si-Jing; Zhang, Lu; You, Li-Xing; Wang, Zhen; Liu, Yang; Lu, Chao-Yang; Jiang, Xiao; Ma, Xiongfeng; Zhang, Qiang; Chen, Teng-Yun; Pan, Jian-Wei

    2016-01-01

    Quantum cryptography holds the promise to establish an information-theoretically secure global network. All field tests of metropolitan-scale quantum networks to date are based on trusted relays. The security critically relies on the accountability of the trusted relays, which will break down if the relay is dishonest or compromised. Here, we construct a measurement-device-independent quantum key distribution (MDIQKD) network in a star topology over a 200-square-kilometer metropolitan area, which is secure against untrustful relays and against all detection attacks. In the field test, our system continuously runs through one week with a secure key rate 10 times larger than previous results. Our results demonstrate that the MDIQKD network, combining the best of both worlds—security and practicality, constitutes an appealing solution to secure metropolitan communications.

  19. Distributed estimation in networked systems under periodic and event-based communication policies

    NASA Astrophysics Data System (ADS)

    Millán, Pablo; Orihuela, Luis; Jurado, Isabel; Vivas, Carlos; Rubio, Francisco R.

    2015-01-01

    This paper's aim is to present a novel design technique for distributed estimation in networked systems. The problem assumes a network of interconnected agents each one having partial access to measurements from a linear plant and broadcasting their estimations to their neighbours. The objective is to reach a reliable estimation of the plant state from every agent location. The observer's structure implemented in each agent is based on local Luenberger-like observers in combination with consensus strategies. The paper focuses on the following network related issues: delays, packet dropouts and communication policy (time and event-driven). The design problem is solved via linear matrix inequalities and stability proofs are provided. The technique is of application for sensor networks and large scale systems where centralized estimation schemes are not advisable and energy-aware implementations are of interest. Simulation examples are provided to show the performance of the proposed methodologies.

  20. Belief-propagation algorithm and the Ising model on networks with arbitrary distributions of motifs

    NASA Astrophysics Data System (ADS)

    Yoon, S.; Goltsev, A. V.; Dorogovtsev, S. N.; Mendes, J. F. F.

    2011-10-01

    We generalize the belief-propagation algorithm to sparse random networks with arbitrary distributions of motifs (triangles, loops, etc.). Each vertex in these networks belongs to a given set of motifs (generalization of the configuration model). These networks can be treated as sparse uncorrelated hypergraphs in which hyperedges represent motifs. Here a hypergraph is a generalization of a graph, where a hyperedge can connect any number of vertices. These uncorrelated hypergraphs are treelike (hypertrees), which crucially simplifies the problem and allows us to apply the belief-propagation algorithm to these loopy networks with arbitrary motifs. As natural examples, we consider motifs in the form of finite loops and cliques. We apply the belief-propagation algorithm to the ferromagnetic Ising model with pairwise interactions on the resulting random networks and obtain an exact solution of this model. We find an exact critical temperature of the ferromagnetic phase transition and demonstrate that with increasing the clustering coefficient and the loop size, the critical temperature increases compared to ordinary treelike complex networks. However, weak clustering does not change the critical behavior qualitatively. Our solution also gives the birth point of the giant connected component in these loopy networks.

  1. Estimating interevent time distributions from finite observation periods in communication networks

    NASA Astrophysics Data System (ADS)

    Kivelä, Mikko; Porter, Mason A.

    2015-11-01

    A diverse variety of processes—including recurrent disease episodes, neuron firing, and communication patterns among humans—can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.

  2. Estimating interevent time distributions from finite observation periods in communication networks.

    PubMed

    Kivelä, Mikko; Porter, Mason A

    2015-11-01

    A diverse variety of processes-including recurrent disease episodes, neuron firing, and communication patterns among humans-can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions. PMID:26651750

  3. Estimating interevent time distributions from finite observation periods in communication networks.

    PubMed

    Kivelä, Mikko; Porter, Mason A

    2015-11-01

    A diverse variety of processes-including recurrent disease episodes, neuron firing, and communication patterns among humans-can be described using interevent time (IET) distributions. Many such processes are ongoing, although event sequences are only available during a finite observation window. Because the observation time window is more likely to begin or end during long IETs than during short ones, the analysis of such data is susceptible to a bias induced by the finite observation period. In this paper, we illustrate how this length bias is born and how it can be corrected without assuming any particular shape for the IET distribution. To do this, we model event sequences using stationary renewal processes, and we formulate simple heuristics for determining the severity of the bias. To illustrate our results, we focus on the example of empirical communication networks, which are temporal networks that are constructed from communication events. The IET distributions of such systems guide efforts to build models of human behavior, and the variance of IETs is very important for estimating the spreading rate of information in networks of temporal interactions. We analyze several well-known data sets from the literature, and we find that the resulting bias can lead to systematic underestimates of the variance in the IET distributions and that correcting for the bias can lead to qualitatively different results for the tails of the IET distributions.

  4. Geographic location, network patterns and population distribution of rural settlements in Greece

    NASA Astrophysics Data System (ADS)

    Asimakopoulos, Avraam; Mogios, Emmanuel; Xenikos, Dimitrios G.

    2016-10-01

    Our work addresses the problem of how social networks are embedded in space, by studying the spread of human population over complex geomorphological terrain. We focus on villages or small cities up to a few thousand inhabitants located in mountainous areas in Greece. This terrain presents a familiar tree-like structure of valleys and land plateaus. Cities are found more often at lower altitudes and exhibit preference on south orientation. Furthermore, the population generally avoids flat land plateaus and river beds, preferring locations slightly uphill, away from the plateau edge. Despite the location diversity regarding geomorphological parameters, we find certain quantitative norms when we examine location and population distributions relative to the (man-made) transportation network. In particular, settlements at radial distance ℓ away from road network junctions have the same mean altitude, practically independent of ℓ ranging from a few meters to 10 km. Similarly, the distribution of the settlement population at any given ℓ is the same for all ℓ. Finally, the cumulative distribution of the number of rural cities n(ℓ) is fitted to the Weibull distribution, suggesting that human decisions for creating settlements could be paralleled to mechanisms typically attributed to this particular statistical distribution.

  5. A Rule-Based and Hypertextual Electronic Mail System for Electronic Learning Environments: Applying the Distributed Network Learning Framework.

    ERIC Educational Resources Information Center

    Jacobson, Michael J.; Levin, James A.

    This paper discusses issues related to the design of software tools that support learners in their participation in network-based learning activities. To guide the development and use of a new class of educationally-oriented network tools, this paper proposes a cognitively-based, distributed network learning framework (DNLF). This framework has…

  6. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC

    PubMed Central

    Anandaraj, M.; Ganeshkumar, P.; Vijayakumar, K. P.; Selvaraj, K.

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10–15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  7. An Efficient Framework for Large Scale Multimedia Content Distribution in P2P Network: I2NC.

    PubMed

    Anandaraj, M; Ganeshkumar, P; Vijayakumar, K P; Selvaraj, K

    2015-01-01

    Network coding (NC) makes content distribution more effective and easier in P2P content distribution network and reduces the burden of the original seeder. It generalizes traditional network routing by allowing the intermediate nodes to generate new coded packet by combining the received packets. The randomization introduced by network coding makes all packets equally important and resolves the problem of locating the rarest block. Further, it reduces traffic in the network. In this paper, we analyze the performance of traditional network coding in P2P content distribution network by using a mathematical model and it is proved that traffic reduction has not been fully achieved in P2P network using traditional network coding. It happens due to the redundant transmission of noninnovative information block among the peers in the network. Hence, we propose a new framework, called I2NC (intelligent-peer selection and incremental-network coding), to eliminate the unnecessary flooding of noninnovative coded packets and thereby to improve the performance of network coding in P2P content distribution further. A comparative study and analysis of the proposed system is made through various related implementations and the results show that 10-15% of traffic reduced and improved the average and maximum download time by reducing original seeder's workload. PMID:26605375

  8. A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks.

    PubMed

    Xu, Yang; Hu, Xuemei; Hu, Haixiao; Liu, Ming

    2016-01-01

    In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors' local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption. PMID:27537891

  9. A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks

    PubMed Central

    Xu, Yang; Hu, Xuemei; Hu, Haixiao; Liu, Ming

    2016-01-01

    In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors’ local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption. PMID:27537891

  10. A Matrix-Based Proactive Data Relay Algorithm for Large Distributed Sensor Networks.

    PubMed

    Xu, Yang; Hu, Xuemei; Hu, Haixiao; Liu, Ming

    2016-08-16

    In large-scale distributed sensor networks, sensed data is required to be relayed around the network so that one or few sensors can gather adequate relative data to produce high quality information for decision-making. In regards to very high energy-constraint sensor nodes, data transmission should be extremely economical. However, traditional data delivery protocols are potentially inefficient relaying unpredictable sensor readings for data fusion in large distributed networks for either overwhelming query transmissions or unnecessary data coverage. By building sensors' local model from their previously transmitted data in three matrixes, we have developed a novel energy-saving data relay algorithm, which allows sensors to proactively make broadcast decisions by using a neat matrix computation to provide balance between transmission and energy-saving. In addition, we designed a heuristic maintenance algorithm to efficiently update these three matrices. This can easily be deployed to large-scale mobile networks in which decisions of sensors are based on their local matrix models no matter how large the network is, and the local models of these sensors are updated constantly. Compared with some traditional approaches based on our simulations, the efficiency of this approach is manifested in uncertain environment. The results show that our approach is scalable and can effectively balance aggregating data with minimizing energy consumption.

  11. Distributed processing method for arbitrary view generation in camera sensor network

    NASA Astrophysics Data System (ADS)

    Tehrani, Mehrdad P.; Fujii, Toshiaki; Tanimoto, Masayuki

    2003-05-01

    Camera sensor network as a new advent of technology is a network that each sensor node can capture video signals, process and communicate them with other nodes. The processing task in this network is to generate arbitrary view, which can be requested from central node or user. To avoid unnecessary communication between nodes in camera sensor network and speed up the processing time, we have distributed the processing tasks between nodes. In this method, each sensor node processes part of interpolation algorithm to generate the interpolated image with local communication between nodes. The processing task in camera sensor network is ray-space interpolation, which is an object independent method and based on MSE minimization by using adaptive filtering. Two methods were proposed for distributing processing tasks, which are Fully Image Shared Decentralized Processing (FIS-DP), and Partially Image Shared Decentralized Processing (PIS-DP), to share image data locally. Comparison of the proposed methods with Centralized Processing (CP) method shows that PIS-DP has the highest processing speed after FIS-DP, and CP has the lowest processing speed. Communication rate of CP and PIS-DP is almost same and better than FIS-DP. So, PIS-DP is recommended because of its better performance than CP and FIS-DP.

  12. Report on NSF/ARO/ONR Workshop on Distributed Camera Networks: Research Challenges and Future Directions

    NASA Astrophysics Data System (ADS)

    Bhanu, Bir; Roy Chowdhury, Amit

    Large-scale video networks are becoming increasingly important for a wide range of critical applications. The development of automated techniques for aggregating and interpreting information from multiple video streams in large-scale networks in real-life scenarios is very challenging. Research in video sensor networks is highly interdisciplinary and requires expertise from a variety of fields. The goal of this effort was to organize a two-day nationally recognized workshop in the domain of camera networks that brings together leading researchers from academia, industry and the government. The workshop was held at the University of California at Riverside on May 11-12, 2009. The workshop was attended by 75 participants. The workshop was sponsored by the US National Science Foundation, US Army Research Office and US Office of Naval Research. The workshop addressed critical interdisciplinary challenges at the intersection of large-scale video camera networks and distributed sensing, processing, communication and control; distributed video understanding; embedded real-time systems; graphics and simulation; and education. The recommendations of the workshop are summarized in the following order of topics: Video Processing and Video Understanding

  13. Distributed estimation based on covariances under network-induced phenomena described by random measurement matrices

    NASA Astrophysics Data System (ADS)

    Caballero-Águila, R.; Hermoso-Carazo, A.; Linares-Pérez, J.

    2016-07-01

    Recursive distributed filtering and fixed-point smoothing algorithms are proposed from measurements through sensor networks perturbed by random parameter matrices and additive noises. The proposed observation model provides a unified framework to consider some network-induced random phenomena. Using an innovation approach, intermediate distributed optimal least-squares (LS) linear estimators are firstly obtained at each sensor node, processing the available output measurements, not only from the own sensor but also from its neighbouring sensors according to the network topology. After that, the proposed distributed estimators are designed at each node as the LS matrix-weighted linear combination of the intermediate estimators within its neighbourhood. The proposed algorithms use only covariance information and do not require the state-space model of the signal. To compare the accuracy of the estimators, recursive expressions for the estimation error covariance matrices are also derived. A simulation example shows the effectiveness of the proposed estimation algorithms and some of the network-induced uncertainties covered by the observation model with random parameter matrices considered in this paper.

  14. A growth model for directed complex networks with power-law shape in the out-degree distribution.

    PubMed

    Esquivel-Gómez, J; Stevens-Navarro, E; Pineda-Rico, U; Acosta-Elias, J

    2015-01-01

    Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1. PMID:25567141

  15. A growth model for directed complex networks with power-law shape in the out-degree distribution

    PubMed Central

    Esquivel-Gómez, J.; Stevens-Navarro, E.; Pineda-Rico, U.; Acosta-Elias, J.

    2015-01-01

    Many growth models have been published to model the behavior of real complex networks. These models are able to reproduce several of the topological properties of such networks. However, in most of these growth models, the number of outgoing links (i.e., out-degree) of nodes added to the network is constant, that is all nodes in the network are born with the same number of outgoing links. In other models, the resultant out-degree distribution decays as a poisson or an exponential distribution. However, it has been found that in real complex networks, the out-degree distribution decays as a power-law. In order to obtain out-degree distribution with power-law behavior some models have been proposed. This work introduces a new model that allows to obtain out-degree distributions that decay as a power-law with an exponent in the range from 0 to 1. PMID:25567141

  16. Multi-Channel Distributed Coordinated Function over Single Radio in Wireless Sensor Networks

    PubMed Central

    Campbell, Carlene E.-A.; Loo, Kok-Keong (Jonathan); Gemikonakli, Orhan; Khan, Shafiullah; Singh, Dhananjay

    2011-01-01

    Multi-channel assignments are becoming the solution of choice to improve performance in single radio for wireless networks. Multi-channel allows wireless networks to assign different channels to different nodes in real-time transmission. In this paper, we propose a new approach, Multi-channel Distributed Coordinated Function (MC-DCF) which takes advantage of multi-channel assignment. The backoff algorithm of the IEEE 802.11 distributed coordination function (DCF) was modified to invoke channel switching, based on threshold criteria in order to improve the overall throughput for wireless sensor networks (WSNs) over 802.11 networks. We presented simulation experiments in order to investigate the characteristics of multi-channel communication in wireless sensor networks using an NS2 platform. Nodes only use a single radio and perform channel switching only after specified threshold is reached. Single radio can only work on one channel at any given time. All nodes initiate constant bit rate streams towards the receiving nodes. In this work, we studied the impact of non-overlapping channels in the 2.4 frequency band on: constant bit rate (CBR) streams, node density, source nodes sending data directly to sink and signal strength by varying distances between the sensor nodes and operating frequencies of the radios with different data rates. We showed that multi-channel enhancement using our proposed algorithm provides significant improvement in terms of throughput, packet delivery ratio and delay. This technique can be considered for WSNs future use in 802.11 networks especially when the IEEE 802.11n becomes popular thereby may prevent the 802.15.4 network from operating effectively in the 2.4 GHz frequency band. PMID:22346614

  17. Distributed haptic interactions with physically based 3D deformable models over lossy networks.

    PubMed

    Tang, Ziying; Yang, Yin; Guo, Xiaohu; Prabhakaran, Balakrishnan

    2013-01-01

    Researchers have faced great challenges when simulating complicated 3D volumetric deformable models in haptics-enabled collaborative/cooperative virtual environments (HCVEs) due to the expensive simulation cost, heavy communication load, and unstable network conditions. When general network services are applied to HCVEs, network problems such as packet loss, delay, and jitter can cause severe visual distortion, haptic instability, and system inconsistency. In this paper, we propose a novel approach to support haptic interactions with physically based 3D deformable models in a distributed virtual environment. Our objective is to achieve real-time sharing of deformable and force simulations over general networks. Combining linear modal analysis and corotational methods, we can effectively simulate physical behaviors of 3D objects, even for large rotational deformations. We analyze different factors that influence HCVEs' performance and focus on exploring solutions for streaming over lossy networks. In our system, 3D deformation can be described by a fairly small amount of data (several KB) using accelerations in the spectral domain, so that we can achieve low communication load and effective streaming. We develop a loss compensation and prediction algorithm to correct the errors/distortions caused by network problem, and a force prediction method to simulate force at users' side to ensure the haptic stability, and the visual and haptic consistency. Our system works well under both the client-server and the peer-to-peer distribution structures, and can be easily extended to other topologies. In addition to theoretical analysis, we have tested the proposed system and algorithms under various network conditions. The experimental results are remarkably good, confirming the effectiveness, robustness, and validity of our approach. PMID:24808394

  18. Robustness of a distributed neural network controller for locomotion in a hexapod robot

    NASA Technical Reports Server (NTRS)

    Chiel, Hillel J.; Beer, Randall D.; Quinn, Roger D.; Espenschied, Kenneth S.

    1992-01-01

    A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

  19. Establish a Data Transmission Platform of the Rig Based on the Distributed Network

    NASA Astrophysics Data System (ADS)

    Bao, Zefu; Li, Tao

    In order to control in real-time ,closed-loop feedback the information, saving the money and labor,we distribute a platform of network data. It through the establishment of the platform in the oil drilling to achieve the easiest route of each device of the rig that conveying timely. The design proposed the platform to transfer networking data by PA which allows the rig control for optimal use. Against the idea,achieving first through on-site cabling and the establishment of data transmission module in the rig monitoring system. The results of standard field application show that the platform solve the problem of rig control.

  20. [Isolation and characterization of injured coliforms from the drinking water distribution network of La Plata, Argentina].

    PubMed

    Basualdo, J A; Córdoba, M A; De Luca, M M; Roccia, I L; Pezzani, B C; Vay, C; Ageron, E; Grimont, P A

    2001-01-01

    We screened the La Plata drinking water distribution network for fecal and total coliform bacterial indicator by purification procedures, cultivating 66 membrane-filtered samples from the two networks on m-T7 agar. Subterranean and river-derived water yielded 13 and 18 confirmed gram-negative bacillus isolates, with 54% and 72% representing total coliforms, respectively. Those from the former source were Klebsiella oxytoca, Enterobacter agglomerans, and Enterobacter aerogenes and from the latter Klebsiella oxytoca, Enterobacter agglomerans, and Enterobacter cloacae, genomic group 3. Since 58% of the samples were positive using m-T7 medium it is suggested that the inclusion in standard quality control protocols should be implemented.

  1. Distributed generation of shared RSA keys in mobile ad hoc networks

    NASA Astrophysics Data System (ADS)

    Liu, Yi-Liang; Huang, Qin; Shen, Ying

    2005-12-01

    Mobile Ad Hoc Networks is a totally new concept in which mobile nodes are able to communicate together over wireless links in an independent manner, independent of fixed physical infrastructure and centralized administrative infrastructure. However, the nature of Ad Hoc Networks makes them very vulnerable to security threats. Generation and distribution of shared keys for CA (Certification Authority) is challenging for security solution based on distributed PKI(Public-Key Infrastructure)/CA. The solutions that have been proposed in the literature and some related issues are discussed in this paper. The solution of a distributed generation of shared threshold RSA keys for CA is proposed in the present paper. During the process of creating an RSA private key share, every CA node only has its own private security. Distributed arithmetic is used to create the CA's private share locally, and that the requirement of centralized management institution is eliminated. Based on fully considering the Mobile Ad Hoc network's characteristic of self-organization, it avoids the security hidden trouble that comes by holding an all private security share of CA, with which the security and robustness of system is enhanced.

  2. Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks

    PubMed Central

    Guo, Kehua; Zhang, Ping; Ma, Jianhua

    2016-01-01

    Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

  3. Secure and Cost-Effective Distributed Aggregation for Mobile Sensor Networks.

    PubMed

    Guo, Kehua; Zhang, Ping; Ma, Jianhua

    2016-01-01

    Secure data aggregation (SDA) schemes are widely used in distributed applications, such as mobile sensor networks, to reduce communication cost, prolong the network life cycle and provide security. However, most SDA are only suited for a single type of statistics (i.e., summation-based or comparison-based statistics) and are not applicable to obtaining multiple statistic results. Most SDA are also inefficient for dynamic networks. This paper presents multi-functional secure data aggregation (MFSDA), in which the mapping step and coding step are introduced to provide value-preserving and order-preserving and, later, to enable arbitrary statistics support in the same query. MFSDA is suited for dynamic networks because these active nodes can be counted directly from aggregation data. The proposed scheme is tolerant to many types of attacks. The network load of the proposed scheme is balanced, and no significant bottleneck exists. The MFSDA includes two versions: MFSDA-I and MFSDA-II. The first one can obtain accurate results, while the second one is a more generalized version that can significantly reduce network traffic at the expense of less accuracy loss. PMID:27120599

  4. Numerical simulation of fibrous biomaterials with randomly distributed fiber network structure.

    PubMed

    Jin, Tao; Stanciulescu, Ilinca

    2016-08-01

    This paper presents a computational framework to simulate the mechanical behavior of fibrous biomaterials with randomly distributed fiber networks. A random walk algorithm is implemented to generate the synthetic fiber network in 2D used in simulations. The embedded fiber approach is then adopted to model the fibers as embedded truss elements in the ground matrix, which is essentially equivalent to the affine fiber kinematics. The fiber-matrix interaction is partially considered in the sense that the two material components deform together, but no relative movement is considered. A variational approach is carried out to derive the element residual and stiffness matrices for finite element method (FEM), in which material and geometric nonlinearities are both included. Using a data structure proposed to record the network geometric information, the fiber network is directly incorporated into the FEM simulation without significantly increasing the computational cost. A mesh sensitivity analysis is conducted to show the influence of mesh size on various simulation results. The proposed method can be easily combined with Monte Carlo (MC) simulations to include the influence of the stochastic nature of the network and capture the material behavior in an average sense. The computational framework proposed in this work goes midway between homogenizing the fiber network into the surrounding matrix and accounting for the fully coupled fiber-matrix interaction at the segment length scale, and can be used to study the connection between the microscopic structure and the macro-mechanical behavior of fibrous biomaterials with a reasonable computational cost. PMID:26342926

  5. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations

    PubMed Central

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  6. Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation

    PubMed Central

    Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D.; Halko, Mark

    2016-01-01

    Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

  7. Design, implementation, and use of a real-time distributed simulation testbed for mobile communication networks

    NASA Astrophysics Data System (ADS)

    Baker, Dennis J.

    1997-06-01

    There is a need to design, develop, and test new mobile communication networks for military applications. The hardware cost to outfit a single node may be quite high. Much of the cost is in rf hardware, modems, and encryption devices. Replicating such costs over several nodes and adding the cost of maintaining a field site can quickly lead to unacceptable budget levels. One solution to this problem is, in the initial development and testing phase, to develop network communication systems that can operate with either real or simulated transmitters, receivers, modems, etc. This paper describes how we accomplished this task for the development of a high frequency, data/voice (D/V) mobile network. The underlying, distributed, real-time simulation software evolved from Sim++2. On top of this we built a simulation package to model mobile communication networks. Software for the SubNet Controller (SNC) of the hf D/V Network was developed to work with these simulation packages as well as to work with real rf equipment. The SNC software was tested in a 6-node network in which some of the rf equipment was simulated and some was real. The resultant system provides a testbed for examining the performance of command and control systems that must operate over mobile rf communication systems.

  8. Distributed Information Compression for Target Tracking in Cluster-Based Wireless Sensor Networks

    PubMed Central

    Liao, Shi-Kuan; Lai, Kai-Jay; Tsai, Hsiao-Ping; Wen, Chih-Yu

    2016-01-01

    Target tracking is a critical wireless sensor application, which involves signal and information processing technologies. In conventional target position estimation methods, an estimate is usually demonstrated by an average target position. In contrast, this work proposes a distributed information compression method to describe the measurement uncertainty of tracking problems in cluster-based wireless sensor networks. The leader-based information processing scheme is applied to perform target positioning and energy conservation. A two-level hierarchical network topology is adopted for energy-efficient target tracking with information compression. A Level 1 network architecture is a cluster-based network topology for managing network operations. A Level 2 network architecture is an event-based and leader-based topology, utilizing the concept of information compression to process the estimates of sensor nodes. The simulation results show that compared to conventional schemes, the proposed data processing scheme has a balanced system performance in terms of tracking accuracy, data size for transmission and energy consumption. PMID:27338417

  9. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.

    PubMed

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology. PMID:26441628

  10. Exact probability distributions of selected species in stochastic chemical reaction networks.

    PubMed

    López-Caamal, Fernando; Marquez-Lago, Tatiana T

    2014-09-01

    Chemical reactions are discrete, stochastic events. As such, the species' molecular numbers can be described by an associated master equation. However, handling such an equation may become difficult due to the large size of reaction networks. A commonly used approach to forecast the behaviour of reaction networks is to perform computational simulations of such systems and analyse their outcome statistically. This approach, however, might require high computational costs to provide accurate results. In this paper we opt for an analytical approach to obtain the time-dependent solution of the Chemical Master Equation for selected species in a general reaction network. When the reaction networks are composed exclusively of zeroth and first-order reactions, this analytical approach significantly alleviates the computational burden required by simulation-based methods. By building upon these analytical solutions, we analyse a general monomolecular reaction network with an arbitrary number of species to obtain the exact marginal probability distribution for selected species. Additionally, we study two particular topologies of monomolecular reaction networks, namely (i) an unbranched chain of monomolecular reactions with and without synthesis and degradation reactions and (ii) a circular chain of monomolecular reactions. We illustrate our methodology and alternative ways to use it for non-linear systems by analysing a protein autoactivation mechanism. Later, we compare the computational load required for the implementation of our results and a pure computational approach to analyse an unbranched chain of monomolecular reactions. Finally, we study calcium ions gates in the sarco/endoplasmic reticulum mediated by ryanodine receptors.

  11. Distributed Information Compression for Target Tracking in Cluster-Based Wireless Sensor Networks.

    PubMed

    Liao, Shi-Kuan; Lai, Kai-Jay; Tsai, Hsiao-Ping; Wen, Chih-Yu

    2016-01-01

    Target tracking is a critical wireless sensor application, which involves signal and information processing technologies. In conventional target position estimation methods, an estimate is usually demonstrated by an average target position. In contrast, this work proposes a distributed information compression method to describe the measurement uncertainty of tracking problems in cluster-based wireless sensor networks. The leader-based information processing scheme is applied to perform target positioning and energy conservation. A two-level hierarchical network topology is adopted for energy-efficient target tracking with information compression. A Level 1 network architecture is a cluster-based network topology for managing network operations. A Level 2 network architecture is an event-based and leader-based topology, utilizing the concept of information compression to process the estimates of sensor nodes. The simulation results show that compared to conventional schemes, the proposed data processing scheme has a balanced system performance in terms of tracking accuracy, data size for transmission and energy consumption.

  12. Enhancing the Temporal Complexity of Distributed Brain Networks with Patterned Cerebellar Stimulation.

    PubMed

    Farzan, Faranak; Pascual-Leone, Alvaro; Schmahmann, Jeremy D; Halko, Mark

    2016-01-01

    Growing evidence suggests that sensory, motor, cognitive and affective processes map onto specific, distributed neural networks. Cerebellar subregions are part of these networks, but how the cerebellum is involved in this wide range of brain functions remains poorly understood. It is postulated that the cerebellum contributes a basic role in brain functions, helping to shape the complexity of brain temporal dynamics. We therefore hypothesized that stimulating cerebellar nodes integrated in different networks should have the same impact on the temporal complexity of cortical signals. In healthy humans, we applied intermittent theta burst stimulation (iTBS) to the vermis lobule VII or right lateral cerebellar Crus I/II, subregions that prominently couple to the dorsal-attention/fronto-parietal and default-mode networks, respectively. Cerebellar iTBS increased the complexity of brain signals across multiple time scales in a network-specific manner identified through electroencephalography (EEG). We also demonstrated a region-specific shift in power of cortical oscillations towards higher frequencies consistent with the natural frequencies of targeted cortical areas. Our findings provide a novel mechanism and evidence by which the cerebellum contributes to multiple brain functions: specific cerebellar subregions control the temporal dynamics of the networks they are engaged in. PMID:27009405

  13. A unified framework for spiking and gap-junction interactions in distributed neuronal network simulations.

    PubMed

    Hahne, Jan; Helias, Moritz; Kunkel, Susanne; Igarashi, Jun; Bolten, Matthias; Frommer, Andreas; Diesmann, Markus

    2015-01-01

    Contemporary simulators for networks of point and few-compartment model neurons come with a plethora of ready-to-use neuron and synapse models and support complex network topologies. Recent technological advancements have broadened the spectrum of application further to the efficient simulation of brain-scale networks on supercomputers. In distributed network simulations the amount of spike data that accrues per millisecond and process is typically low, such that a common optimization strategy is to communicate spikes at relatively long intervals, where the upper limit is given by the shortest synaptic transmission delay in the network. This approach is well-suited for simulations that employ only chemical synapses but it has so far impeded the incorporation of gap-junction models, which require instantaneous neuronal interactions. Here, we present a numerical algorithm based on a waveform-relaxation technique which allows for network simulations with gap junctions in a way that is compatible with the delayed communication strategy. Using a reference implementation in the NEST simulator, we demonstrate that the algorithm and the required data structures can be smoothly integrated with existing code such that they complement the infrastructure for spiking connections. To show that the unified framework for gap-junction and spiking interactions achieves high performance and delivers high accuracy in the presence of gap junctions, we present benchmarks for workstations, clusters, and supercomputers. Finally, we discuss limitations of the novel technology.

  14. Mapping Power Law Distributions in Digital Health Social Networks: Methods, Interpretations, and Practical Implications

    PubMed Central

    2015-01-01

    Background Social networks are common in digital health. A new stream of research is beginning to investigate the mechanisms of digital health social networks (DHSNs), how they are structured, how they function, and how their growth can be nurtured and managed. DHSNs increase in value when additional content is added, and the structure of networks may resemble the characteristics of power laws. Power laws are contrary to traditional Gaussian averages in that they demonstrate correlated phenomena. Objectives The objective of this study is to investigate whether the distribution frequency in four DHSNs can be characterized as following a power law. A second objective is to describe the method used to determine the comparison. Methods Data from four DHSNs—Alcohol Help Center (AHC), Depression Center (DC), Panic Center (PC), and Stop Smoking Center (SSC)—were compared to power law distributions. To assist future researchers and managers, the 5-step methodology used to analyze and compare datasets is described. Results All four DHSNs were found to have right-skewed distributions, indicating the data were not normally distributed. When power trend lines were added to each frequency distribution, R 2 values indicated that, to a very high degree, the variance in post frequencies can be explained by actor rank (AHC .962, DC .975, PC .969, SSC .95). Spearman correlations provided further indication of the strength and statistical significance of the relationship (AHC .987. DC .967, PC .983, SSC .993, P<.001). Conclusions This is the first study to investigate power distributions across multiple DHSNs, each addressing a unique condition. Results indicate that despite vast differences in theme, content, and length of existence, DHSNs follow properties of power laws. The structure of DHSNs is important as it gives insight to researchers and managers into the nature and mechanisms of network functionality. The 5-step process undertaken to compare actor contribution patterns

  15. MaxEnt analysis of a water distribution network in Canberra, ACT, Australia

    NASA Astrophysics Data System (ADS)

    Waldrip, Steven H.; Niven, Robert K.; Abel, Markus; Schlegel, Michael; Noack, Bernd R.

    2015-01-01

    A maximum entropy (MaxEnt) method is developed to infer the state of a pipe flow network, for situations in which there is insufficient information to form a closed equation set. This approach substantially extends existing deterministic methods for the analysis of engineered flow networks (e.g. Newton's method or the Hardy Cross scheme). The network is represented as an undirected graph structure, in which the uncertainty is represented by a continuous relative entropy on the space of internal and external flow rates. The head losses (potential differences) on the network are treated as dependent variables, using specified pipe-flow resistance functions. The entropy is maximised subject to "observable" constraints on the mean values of certain flow rates and/or potential differences, and also "physical" constraints arising from the frictional properties of each pipe and from Kirchhoff's nodal and loop laws. A numerical method is developed in Matlab for solution of the integral equation system, based on multidimensional quadrature. Several nonlinear resistance functions (e.g. power-law and Colebrook) are investigated, necessitating numerical solution of the implicit Lagrangian by a double iteration scheme. The method is applied to a 1123-node, 1140-pipe water distribution network for the suburb of Torrens in the Australian Capital Territory, Australia, using network data supplied by water authority ACTEW Corporation Limited. A number of different assumptions are explored, including various network geometric representations, prior probabilities and constraint settings, yielding useful predictions of network demand and performance. We also propose this methodology be used in conjunction with in-flow monitoring systems, to obtain better inferences of user consumption without large investments in monitoring equipment and maintenance.

  16. El Sistema's Open Secrets

    ERIC Educational Resources Information Center

    Booth, Eric

    2011-01-01

    In this article, the author talks about Venezuela's national youth orchestra program called El Sistema whose attributes offer a direct challenge to traditional Western music practices. As U.S. classical music--and all "high arts"--struggle to find relevance to more than the small "arts club" percentage of the U.S. populace, El Sistema proposes…

  17. Examining the Distribution, Modularity, and Community Structure in Article Networks for Systematic Reviews.

    PubMed

    Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

    2015-01-01

    Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization.

  18. Distributed Spectrum Sharing for Video Streaming in Cognitive Radio Ad Hoc Networks

    NASA Astrophysics Data System (ADS)

    Ding, Lei; Pudlewski, Scott; Melodia, Tommaso; Batalama, Stella; Matyjas, John D.; Medley, Michael J.

    A distributed joint routing and spectrum sharing algorithm for video streaming applications over cognitive radio ad hoc networks is proposed in this article. The proposed cross-layer control scheme dynamically allocates routes, spectrum and power to maximize the network throughput under the constraints posed by delay-sensitive video applications. The algorithm evaluates the expected delay of competing flows in single-hop and two-hop networks considering the time-varying spectrum condition and occupancy, traffic characteristics, and the condition of queues at intermediate nodes. Simulation results show that the proposed algorithm significantly reduces the packet loss rate and improves the average peak signal-to-noise ratio (PSNR) of the received video streams.

  19. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

    PubMed

    Yoon, Young; Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users.

  20. Techniques for selecting topology and implementing the distributed control system network

    NASA Astrophysics Data System (ADS)

    Chernyi, S.

    2016-04-01

    On grounds of reviews devoted to flows analysis methods in the data processing networks within the automated control systems for the technological process and assessment of these methods by the selected set of requirements, one may make conclusion about expediency of using the combination of graph flow algorithms and the queuing theory. The outputs of the research concerning the impact of network dynamics on the drilling platform distributed system control quality prove the fact that the quality of the transient depends upon the frequency of discretization and intensity of flows. With increasing the intensity of flows, the static error of the control enlarges. It was concluded that in order to control the automation objects in the real-time mode it is required to minimize the delays in transmitting packets in the network.

  1. Bipartite networks of oscillators with distributed delays: Synchronization branches and multistability.

    PubMed

    Punetha, Nirmal; Ramaswamy, Ramakrishna; Atay, Fatihcan M

    2015-04-01

    We study synchronization in bipartite networks of phase oscillators with general nonlinear coupling and distributed time delays. Phase-locked solutions are shown to arise, where the oscillators in each partition are perfectly synchronized among themselves but can have a phase difference with the other partition, with the phase difference necessarily being either zero or π radians. Analytical conditions for the stability of both types of solutions are obtained and solution branches are explicitly calculated, revealing that the network can have several coexisting stable solutions. With increasing value of the mean delay, the system exhibits hysteresis, phase flips, final state sensitivity, and an extreme form of multistability where the numbers of stable in-phase and antiphase synchronous solutions with distinct frequencies grow without bound. The theory is applied to networks of Landau-Stuart and Rössler oscillators and shown to accurately predict both in-phase and antiphase synchronous behavior in appropriate parameter ranges.

  2. Bipartite networks of oscillators with distributed delays: Synchronization branches and multistability

    NASA Astrophysics Data System (ADS)

    Punetha, Nirmal; Ramaswamy, Ramakrishna; Atay, Fatihcan M.

    2015-04-01

    We study synchronization in bipartite networks of phase oscillators with general nonlinear coupling and distributed time delays. Phase-locked solutions are shown to arise, where the oscillators in each partition are perfectly synchronized among themselves but can have a phase difference with the other partition, with the phase difference necessarily being either zero or π radians. Analytical conditions for the stability of both types of solutions are obtained and solution branches are explicitly calculated, revealing that the network can have several coexisting stable solutions. With increasing value of the mean delay, the system exhibits hysteresis, phase flips, final state sensitivity, and an extreme form of multistability where the numbers of stable in-phase and antiphase synchronous solutions with distinct frequencies grow without bound. The theory is applied to networks of Landau-Stuart and Rössler oscillators and shown to accurately predict both in-phase and antiphase synchronous behavior in appropriate parameter ranges.

  3. Layer 1 VPN services in distributed next-generation SONET/SDH networks with inverse multiplexing

    NASA Astrophysics Data System (ADS)

    Ghani, N.; Muthalaly, M. V.; Benhaddou, D.; Alanqar, W.

    2006-05-01

    Advances in next-generation SONET/SDH along with GMPLS control architectures have enabled many new service provisioning capabilities. In particular, a key services paradigm is the emergent Layer 1 virtual private network (L1 VPN) framework, which allows multiple clients to utilize a common physical infrastructure and provision their own 'virtualized' circuit-switched networks. This precludes expensive infrastructure builds and increases resource utilization for carriers. Along these lines, a novel L1 VPN services resource management scheme for next-generation SONET/SDH networks is proposed that fully leverages advanced virtual concatenation and inverse multiplexing features. Additionally, both centralized and distributed GMPLS-based implementations are also tabled to support the proposed L1 VPN services model. Detailed performance analysis results are presented along with avenues for future research.

  4. Relaxation dynamics of small-world degree-distributed treelike polymer networks

    NASA Astrophysics Data System (ADS)

    Galiceanu, Mircea; Oliveira, Edieliton S.; Dolgushev, Maxim

    2016-11-01

    Hyperbranched polymers are typically treelike macromolecules with a very disordered structure. Here we construct hyperbranched polymers based on the degree distribution of the small-world networks. This algorithm allows us to study a transition from monodisperse linear chains to structurally-disordered dendritic polymers by varying the parameter p (0 ≤ p ≤ 1), which measures the randomness and the degree of branching of the network. Employing the framework of generalized Gaussian structures, we determine for the obtained structures the relaxation spectra, which are exemplified on the mechanical relaxation moduli (storage and loss moduli). We monitor these physical quantities for networks of different sizes and for various values of the parameter p. In the intermediate frequency domain, we encounter macroscopically distinguishable behaviours.

  5. Scaling of weighted spectral distribution in deterministic scale-free networks

    NASA Astrophysics Data System (ADS)

    Jiao, Bo; Nie, Yuan-ping; Shi, Jian-mai; Huang, Cheng-dong; Zhou, Ying; Du, Jing; Guo, Rong-hua; Tao, Ye-rong

    2016-06-01

    Scale-free networks are abundant in the real world. In this paper, we investigate the scaling properties of the weighted spectral distribution in several deterministic and stochastic models of evolving scale-free networks. First, we construct a new deterministic scale-free model whose node degrees have a unified format. Using graph structure features, we derive a precise formula for the spectral metric in this model. This formula verifies that the spectral metric grows sublinearly as network size (i.e., the number of nodes) grows. Additionally, the mathematical reasoning of the precise formula theoretically provides detailed explanations for this scaling property. Finally, we validate the scaling properties of the spectral metric using some stochastic models. The experimental results show that this scaling property can be retained regardless of local world, node deleting and assortativity adjustment.

  6. A design testbed for distributed V/UHF networks with mobile terminals

    NASA Astrophysics Data System (ADS)

    Carnegie, Andrew

    A flexible design tool for mobile radio networks was implemented. Both low level areas such as modulation, coding, and synchronization, and high level techniques involving protocol details can be analyzed simultaneously. The simulation software is based on a Rayleigh fading channel model with a network layer protocol implementation. Described here is how a Rayleigh distribution can be generated and how it is used to implement the channel simulation by a conversion to a probability of error based on the modulation technique required. The network model is discussed with reference to the OSI Open Systems Interconnection reference model, and the variable configuration is described. To access the success of the system, an investigation into the use of variable, optimum length packets is illustrated.

  7. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network.

    PubMed

    Yoon, Young; Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users. PMID:27367610

  8. Intrusion-Aware Alert Validation Algorithm for Cooperative Distributed Intrusion Detection Schemes of Wireless Sensor Networks

    PubMed Central

    Shaikh, Riaz Ahmed; Jameel, Hassan; d’Auriol, Brian J.; Lee, Heejo; Lee, Sungyoung; Song, Young-Jae

    2009-01-01

    Existing anomaly and intrusion detection schemes of wireless sensor networks have mainly focused on the detection of intrusions. Once the intrusion is detected, an alerts or claims will be generated. However, any unidentified malicious nodes in the network could send faulty anomaly and intrusion claims about the legitimate nodes to the other nodes. Verifying the validity of such claims is a critical and challenging issue that is not considered in the existing cooperative-based distributed anomaly and intrusion detection schemes of wireless sensor networks. In this paper, we propose a validation algorithm that addresses this problem. This algorithm utilizes the concept of intrusion-aware reliability that helps to provide adequate reliability at a modest communication cost. In this paper, we also provide a security resiliency analysis of the proposed intrusion-aware alert validation algorithm. PMID:22454568

  9. Secret Forwarding of Events over Distributed Publish/Subscribe Overlay Network

    PubMed Central

    Kim, Beom Heyn

    2016-01-01

    Publish/subscribe is a communication paradigm where loosely-coupled clients communicate in an asynchronous fashion. Publish/subscribe supports the flexible development of large-scale, event-driven and ubiquitous systems. Publish/subscribe is prevalent in a number of application domains such as social networking, distributed business processes and real-time mission-critical systems. Many publish/subscribe applications are sensitive to message loss and violation of privacy. To overcome such issues, we propose a novel method of using secret sharing and replication techniques. This is to reliably and confidentially deliver decryption keys along with encrypted publications even under the presence of several Byzantine brokers across publish/subscribe overlay networks. We also propose a framework for dynamically and strategically allocating broker replicas based on flexibly definable criteria for reliability and performance. Moreover, a thorough evaluation is done through a case study on social networks using the real trace of interactions among Facebook users. PMID:27367610

  10. Design constraints for third-order PLL nodes in master-slave clock distribution networks

    NASA Astrophysics Data System (ADS)

    Bueno, A. M.; Rigon, A. G.; Ferreira, A. A.; Piqueira, José R. C.

    2010-09-01

    Clock signal distribution in telecommunication commercial systems usually adopts a master-slave architecture, with a precise time basis generator as a master and phase-locked loops (PLLs) as slaves. In the majority of the networks, second-order PLLs are adopted due to their simplicity and stability. Nevertheless, in some applications better transient responses are necessary and, consequently, greater order PLLs need to be used, in spite of the possibility of bifurcations and chaotic attractors. Here a master-slave network with third-order PLLs is analyzed and conditions for the stability of the synchronous state are derived, providing design constraints for the node parameters, in order to guarantee stability and reachability of the synchronous state for the whole network. Numerical simulations are carried out in order to confirm the analytical results.

  11. Examining the Distribution, Modularity, and Community Structure in Article Networks for Systematic Reviews

    PubMed Central

    Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin

    2015-01-01

    Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization. PMID:26958292

  12. Mobile agent and multilayer integrated distributed intrusion detection model for clustering ad hoc networks

    NASA Astrophysics Data System (ADS)

    Feng, Jianxin; Wang, Guangxing

    2004-04-01

    Ad hoc networks do not depend on any predefined infrastructure or centralized administration to operate. Their security characters require more complex security preventions. As the second line of defense, Intrusion detection is the necessary means of getting the high survivability. In this paper the security characters of ad hoc networks and the related contents of intrusion detection are discussed. Mobile Agent and Multi-layer Integrated Distributed Intrusion Detection Model (MAMIDIDM) and a heuristic global detection algorithm are proposed tentatively by combining the mobile agent technology with the multi-layer conception. This heuristic global detection algorithm combines the mobile agent detection engine with the multi-layer detection engines and analyzes the results obtained by the corresponding detection engines. MAMIDIDM has the better flexibility and extensibility, can execute the intrusion detection in clustering ad hoc networks effectively.

  13. Evolutionary prisoner's dilemma on Newman-Watts social networks with an asymmetric payoff distribution mechanism

    NASA Astrophysics Data System (ADS)

    Du, Wen-Bo; Cao, Xian-Bin; Yang, Han-Xin; Hu, Mao-Bin

    2010-01-01

    In this paper, we introduce an asymmetric payoff distribution mechanism into the evolutionary prisoner's dilemma game (PDG) on Newman-Watts social networks, and study its effects on the evolution of cooperation. The asymmetric payoff distribution mechanism can be adjusted by the parameter α: if α > 0, the rich will exploit the poor to get richer; if α < 0, the rich are forced to offer part of their income to the poor. Numerical results show that the cooperator frequency monotonously increases with α and is remarkably promoted when α > 0. The effects of updating order and self-interaction are also investigated. The co-action of random updating and self-interaction can induce the highest cooperation level. Moreover, we employ the Gini coefficient to investigate the effect of asymmetric payoff distribution on the the system's wealth distribution. This work may be helpful for understanding cooperative behaviour and wealth inequality in society.

  14. Energy efficient wireless sensor network for structural health monitoring using distributed embedded piezoelectric transducers

    NASA Astrophysics Data System (ADS)

    Li, Peng; Olmi, Claudio; Song, Gangbing

    2010-04-01

    Piezoceramic based transducers are widely researched and used for structural health monitoring (SHM) systems due to the piezoceramic material's inherent advantage of dual sensing and actuation. Wireless sensor network (WSN) technology benefits from advances made in piezoceramic based structural health monitoring systems, allowing easy and flexible installation, low system cost, and increased robustness over wired system. However, piezoceramic wireless SHM systems still faces some drawbacks, one of these is that the piezoceramic based SHM systems require relatively high computational capabilities to calculate damage information, however, battery powered WSN sensor nodes have strict power consumption limitation and hence limited computational power. On the other hand, commonly used centralized processing networks require wireless sensors to transmit all data back to the network coordinator for analysis. This signal processing procedure can be problematic for piezoceramic based SHM applications as it is neither energy efficient nor robust. In this paper, we aim to solve these problems with a distributed wireless sensor network for piezoceramic base structural health monitoring systems. Three important issues: power system, waking up from sleep impact detection, and local data processing, are addressed to reach optimized energy efficiency. Instead of sweep sine excitation that was used in the early research, several sine frequencies were used in sequence to excite the concrete structure. The wireless sensors record the sine excitations and compute the time domain energy for each sine frequency locally to detect the energy change. By comparing the data of the damaged concrete frame with the healthy data, we are able to find out the damage information of the concrete frame. A relative powerful wireless microcontroller was used to carry out the sampling and distributed data processing in real-time. The distributed wireless network dramatically reduced the data

  15. A Wolf Pack Algorithm for Active and Reactive Power Coordinated Optimization in Active Distribution Network

    NASA Astrophysics Data System (ADS)

    Zhuang, H. M.; Jiang, X. J.

    2016-08-01

    This paper presents an active and reactive power dynamic optimization model for active distribution network (ADN), whose control variables include the output of distributed generations (DGs), charge or discharge power of energy storage system (ESS) and reactive power from capacitor banks. To solve the high-dimension nonlinear optimization model, a new heuristic swarm intelligent method, namely wolf pack algorithm (WPA) with better global convergence and computational robustness, is adapted so that the network loss minimization can be achieved. In this paper, the IEEE33-bus system is used to show the effectiveness of WPA technique compared with other techniques. Numerical tests on the modified IEEE 33-bus system show that WPA for active and reactive multi-period optimization of ADN is exact and effective.

  16. Optimal epidemic spreading on complex networks with heterogeneous waiting time distribution

    NASA Astrophysics Data System (ADS)

    Yang, Guan-Ling; Yang, Xinsong

    2016-04-01

    In this paper, the effects of heterogeneous waiting time on spreading dynamics is studied based on network-dependent information. A new non-Markovian susceptible-infected-susceptible (SIS) model is first proposed, in which node's waiting time is dependent on its degree and may be different from each other. Every node tries to transmit the epidemic to its neighbors after the waiting time. Moreover, by using the mean-field theory and numerical simulations, it is discovered that the epidemic threshold is correlated to the network topology and the distribution of the waiting time. Furthermore, our results reveal that an optimal distribution of the heterogeneous waiting time can suppress the epidemic spreading.

  17. XNsim: Internet-Enabled Collaborative Distributed Simulation via an Extensible Network

    NASA Technical Reports Server (NTRS)

    Novotny, John; Karpov, Igor; Zhang, Chendi; Bedrossian, Nazareth S.

    2007-01-01

    In this paper, the XNsim approach to achieve Internet-enabled, dynamically scalable collaborative distributed simulation capabilities is presented. With this approach, a complete simulation can be assembled from shared component subsystems written in different formats, that run on different computing platforms, with different sampling rates, in different geographic locations, and over singlelmultiple networks. The subsystems interact securely with each other via the Internet. Furthermore, the simulation topology can be dynamically modified. The distributed simulation uses a combination of hub-and-spoke and peer-topeer network topology. A proof-of-concept demonstrator is also presented. The XNsim demonstrator can be accessed at http://www.jsc.draver.corn/xn that hosts various examples of Internet enabled simulations.

  18. Hybrid decode-amplify-forward (HDAF) scheme in distributed Alamouti-coded cooperative network

    NASA Astrophysics Data System (ADS)

    Gurrala, Kiran Kumar; Das, Susmita

    2015-05-01

    In this article, a signal-to-noise ratio (SNR)-based hybrid decode-amplify-forward scheme in a distributed Alamouti-coded cooperative network is proposed. Considering a flat Rayleigh fading channel environment, the MATLAB simulation and analysis are carried out. In the cooperative scheme, two relays are employed, where each relay is transmitting each row Alamouti code. The selection of SNR threshold depends on the target rate information. The closed form expressions of symbol error rate (SER), the outage probability and average channel capacity with tight upper bounds are derived and compared with the simulation done in MATLAB environment. Furthermore, the impact of relay location on the SER performance is analysed. It is observed that the proposed hybrid relaying technique outperforms the individual amplify and forward and decode and forward ones in the distributed Alamouti-coded cooperative network.

  19. Distributed edge detection algorithm based on wavelet transform for wireless video sensor network

    NASA Astrophysics Data System (ADS)

    Li, Qiulin; Hao, Qun; Song, Yong; Wang, Dongsheng

    2010-12-01

    Edge detection algorithms are critical to image processing and computer vision. Traditional edge detection algorithms are not suitable for wireless video sensor network (WVSN) in which the nodes are with in limited calculation capability and resources. In this paper, a distributed edge detection algorithm based on wavelet transform designed for WVSN is proposed. Wavelet transform decompose the image into several parts, then the parts are assigned to different nodes through wireless network separately. Each node performs sub-image edge detecting algorithm correspondingly, all the results are sent to sink node, Fusing and Synthesis which include image binary and edge connect are executed in it. And finally output the edge image. Lifting scheme and parallel distributed algorithm are adopted to improve the efficiency, simultaneously, decrease the computational complexity. Experimental results show that this method could achieve higher efficiency and better result.

  20. Distributed edge detection algorithm based on wavelet transform for wireless video sensor network

    NASA Astrophysics Data System (ADS)

    Li, Qiulin; Hao, Qun; Song, Yong; Wang, Dongsheng

    2011-05-01

    Edge detection algorithms are critical to image processing and computer vision. Traditional edge detection algorithms are not suitable for wireless video sensor network (WVSN) in which the nodes are with in limited calculation capability and resources. In this paper, a distributed edge detection algorithm based on wavelet transform designed for WVSN is proposed. Wavelet transform decompose the image into several parts, then the parts are assigned to different nodes through wireless network separately. Each node performs sub-image edge detecting algorithm correspondingly, all the results are sent to sink node, Fusing and Synthesis which include image binary and edge connect are executed in it. And finally output the edge image. Lifting scheme and parallel distributed algorithm are adopted to improve the efficiency, simultaneously, decrease the computational complexity. Experimental results show that this method could achieve higher efficiency and better result.

  1. Quantum key distribution over an installed multimode optical fiber local area network.

    PubMed

    Namekata, Naoto; Mori, Shigehiko; Inoue, Shuichiro

    2005-12-12

    We have investigated the possibility of a multimode fiber link for a quantum channel. Transmission of light in an extremely underfilled mode distribution promises a single-mode-like behavior in the multimode fiber. To demonstrate the performance of the fiber link we performed quantum key distribution, on the basis of the BB84 four-state protocol, over 550 m of an installed multimode optical fiber local area network, and the quantum-bit-error rate of 1.09 percent was achieved. PMID:19503207

  2. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays.

    PubMed

    Guodong Zhang; Yi Shen; Quan Yin; Junwei Sun

    2015-01-01

    In this paper, based on the knowledge of memristor and recurrent neural networks (RNNs), the model of the memristor-based RNNs with discrete and distributed delays is established. By constructing proper Lyapunov functionals and using inequality technique, several sufficient conditions are given to ensure the passivity of the memristor-based RNNs with discrete and distributed delays in the sense of Filippov solutions. The passivity conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. In addition, the results of this paper complement and extend the earlier publications. Finally, numerical simulations are employed to illustrate the effectiveness of the obtained results.

  3. Prototype of network distributed control system for MLF/J-PARC

    NASA Astrophysics Data System (ADS)

    Nakatani, Takeshi; Nakajima, Kenji; Torii, Shuki; Bharoto; Higemoto, Wataru; Sato, Setsuo; Otomo, Toshiya; Arai, Masatoshi

    2006-11-01

    We have developed a prototype data acquisition and device control system for experiment instruments at the Material and Life science Facility (MLF)/Japan-Proton Accelerator Research Complex (J-PARC). The system employs distributed computing via Ethernet, client/server architecture, modular structure and a state machine. Communication between client and server software utilizes socket protocols over TCP/IP. We have deployed this prototype software in the network distributed control system by improving the data acquisition software used at KENS, introducing the system for the SWAN at KENS/KEK. It was kept in working order throughout 2 weeks of machine operation.

  4. The origin of the criticality in meme popularity distribution on complex networks.

    PubMed

    Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

    2016-01-01

    Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks. PMID:27009399

  5. Recognizing animal-caused faults in power distribution systems using artificial neural networks

    SciTech Connect

    Chow, Mo Yuen; Yee, S.O. . Dept. of Electrical and Computer Engineering); Taylor, L.S. . Distribution Engineering)

    1993-07-01

    Faults are likely to occur in most power distribution systems. If the causes of the faults are known, specific action can be taken to eliminate the fault sources as soon as possible to avoid unnecessary costs, such as power system down-time cost, that are caused by failing to identify the fault sources. However, experts that can accurately recognize the causes of distribution faults are scarce and the knowledge about the nature of these faults is easily transferable from person to person. Therefore, artificial neural networks are used in this paper to recognize the causes of faults in power distribution systems, based on fault currents information collected for each outage. Actual field data collected by Duke Power Company are used in this paper. The methodology and implementation of artificial neural networks and fuzzy logic for the identification of animal-caused distribution faults will be presented. Satisfactory results have been obtained, and the developed methodology can be easily generalized and used to identify other causes of faults in power distribution systems.

  6. The origin of the criticality in meme popularity distribution on complex networks

    NASA Astrophysics Data System (ADS)

    Kim, Yup; Park, Seokjong; Yook, Soon-Hyung

    2016-03-01

    Previous studies showed that the meme popularity distribution is described by a heavy-tailed distribution or a power-law, which is a characteristic feature of the criticality. Here, we study the origin of the criticality on non-growing and growing networks based on the competition induced criticality model. From the direct Mote Carlo simulations and the exact mapping into the position dependent biased random walk (PDBRW), we find that the meme popularity distribution satisfies a very robust power- law with exponent α = 3/2 if there is an innovation process. On the other hand, if there is no innovation, then we find that the meme popularity distribution is bounded and highly skewed for early transient time periods, while it satisfies a power-law with exponent α ≠ 3/2 for intermediate time periods. The exact mapping into PDBRW clearly shows that the balance between the creation of new memes by the innovation process and the extinction of old memes is the key factor for the criticality. We confirm that the balance for the criticality sustains for relatively small innovation rate. Therefore, the innovation processes with significantly influential memes should be the simple and fundamental processes which cause the critical distribution of the meme popularity in real social networks.

  7. A Distributed Multiagent System Architecture for Body Area Networks Applied to Healthcare Monitoring

    PubMed Central

    Laza, Rosalía; Pereira, António

    2015-01-01

    In the last years the area of health monitoring has grown significantly, attracting the attention of both academia and commercial sectors. At the same time, the availability of new biomedical sensors and suitable network protocols has led to the appearance of a new generation of wireless sensor networks, the so-called wireless body area networks. Nowadays, these networks are routinely used for continuous monitoring of vital parameters, movement, and the surrounding environment of people, but the large volume of data generated in different locations represents a major obstacle for the appropriate design, development, and deployment of more elaborated intelligent systems. In this context, we present an open and distributed architecture based on a multiagent system for recognizing human movements, identifying human postures, and detecting harmful activities. The proposed system evolved from a single node for fall detection to a multisensor hardware solution capable of identifying unhampered falls and analyzing the users' movement. The experiments carried out contemplate two different scenarios and demonstrate the accuracy of our proposal as a real distributed movement monitoring and accident detection system. Moreover, we also characterize its performance, enabling future analyses and comparisons with similar approaches. PMID:25874202

  8. Quantum teleportation with independent sources and prior entanglement distribution over a network

    NASA Astrophysics Data System (ADS)

    Sun, Qi-Chao; Mao, Ya-Li; Chen, Si-Jing; Zhang, Wei; Jiang, Yang-Fan; Zhang, Yan-Bao; Zhang, Wei-Jun; Miki, Shigehito; Yamashita, Taro; Terai, Hirotaka; Jiang, Xiao; Chen, Teng-Yun; You, Li-Xing; Chen, Xian-Feng; Wang, Zhen; Fan, Jing-Yun; Zhang, Qiang; Pan, Jian-Wei

    2016-10-01

    Quantum teleportation faithfully transfers a quantum state between distant nodes in a network, which enables revolutionary information-processing applications. This has motivated a tremendous amount of research activity. However, in the past not a single quantum-teleportation experiment has been realized with independent quantum sources, entanglement distribution prior to the Bell-state measurement (BSM) and feedforward operation simultaneously, even in the laboratory environment. We take the challenge and report the construction of a 30 km optical-fibre-based quantum network distributed over a 12.5 km area. This network is robust against noise in the real world with active stabilization strategies, which allows us to realize quantum teleportation with all the ingredients simultaneously. Both the quantum-state and process-tomography measurements and an independent statistical hypothesis test confirm the quantum nature of the quantum teleportation over this network. Our experiment marks a critical step towards the realization of a global ‘quantum internet’ in the real world.

  9. A high performance long-reach passive optical network with a novel excess bandwidth distribution scheme

    NASA Astrophysics Data System (ADS)

    Chao, I.-Fen; Zhang, Tsung-Min

    2015-06-01

    Long-reach passive optical networks (LR-PONs) have been considered to be promising solutions for future access networks. In this paper, we propose a distributed medium access control (MAC) scheme over an advantageous LR-PON network architecture that reroutes the control information from and back to all ONUs through an (N + 1) × (N + 1) star coupler (SC) deployed near the ONUs, thereby overwhelming the extremely long propagation delay problem in LR-PONs. In the network, the control slot is designed to contain all bandwidth requirements of all ONUs and is in-band time-division-multiplexed with a number of data slots within a cycle. In the proposed MAC scheme, a novel profit-weight-based dynamic bandwidth allocation (P-DBA) scheme is presented. The algorithm is designed to efficiently and fairly distribute the amount of excess bandwidth based on a profit value derived from the excess bandwidth usage of each ONU, which resolves the problems of previously reported DBA schemes that are either unfair or inefficient. The simulation results show that the proposed decentralized algorithms exhibit a nearly three-order-of-magnitude improvement in delay performance compared to the centralized algorithms over LR-PONs. Moreover, the newly proposed P-DBA scheme guarantees low delay performance and fairness even when under attack by the malevolent ONU irrespective of traffic loads and burstiness.

  10. SHD digital cinema distribution over a long distance network of Internet2

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Takahiro; Shirai, Daisuke; Fujii, Tatsuya; Nomura, Mitsuru; Fujii, Tetsuro; Ono, Sadayasu

    2003-06-01

    We have developed a prototype SHD (Super High Definition) digital cinema distribution system that can store, transmit and display eight-million-pixel motion pictures that have the image quality of a 35-mm film movie. The system contains a video server, a real-time decoder, and a D-ILA projector. Using a gigabit Ethernet link and TCP/IP, the server transmits JPEG2000 compressed motion picture data streams to the decoder at transmission speeds as high as 300 Mbps. The received data streams are decompressed by the decoder, and then projected onto a screen via the projector. With this system, digital cinema contents can be distributed over a wide-area optical gigabit IP network. However, when digital cinema contents are delivered over long distances by using a gigabit IP network and TCP, the round-trip time increases and network throughput either stops rising or diminishes. In a long-distance SHD digital cinema transmission experiment performed on the Internet2 network in October 2002, we adopted enlargement of the TCP window, multiple TCP connections, and shaping function to control the data transmission quantity. As a result, we succeeded in transmitting the SHD digital cinema content data at about 300 Mbps between Chicago and Los Angeles, a distance of more than 3000 km.

  11. A Lego Mindstorms NXT based test bench for multiagent exploratory systems and distributed network partitioning

    NASA Astrophysics Data System (ADS)

    Patil, Riya Raghuvir

    Networks of communicating agents require distributed algorithms for a variety of tasks in the field of network analysis and control. For applications such as swarms of autonomous vehicles, ad hoc and wireless sensor networks, and such military and civilian applications as exploring and patrolling a robust autonomous system that uses a distributed algorithm for selfpartitioning can be significantly helpful. A single team of autonomous vehicles in a field may need to self-dissemble into multiple teams, conducive to completing multiple control tasks. Moreover, because communicating agents are subject to changes, namely, addition or failure of an agent or link, a distributed or decentralized algorithm is favorable over having a central agent. A framework to help with the study of self-partitioning of such multi agent systems that have most basic mobility model not only saves our time in conception but also gives us a cost effective prototype without negotiating the physical realization of the proposed idea. In this thesis I present my work on the implementation of a flexible and distributed stochastic partitioning algorithm on the LegoRTM Mindstorms' NXT on a graphical programming platform using National Instruments' LabVIEW(TM) forming a team of communicating agents via NXT-Bee radio module. We single out mobility, communication and self-partition as the core elements of the work. The goal is to randomly explore a precinct for reference sites. Agents who have discovered the reference sites announce their target acquisition to form a network formed based upon the distance of each agent with the other wherein the self-partitioning begins to find an optimal partition. Further, to illustrate the work, an experimental test-bench of five Lego NXT robots is presented.

  12. Parallel multi-join query optimization algorithm for distributed sensor network in the internet of things

    NASA Astrophysics Data System (ADS)

    Zheng, Yan

    2015-03-01

    Internet of things (IoT), focusing on providing users with information exchange and intelligent control, attracts a lot of attention of researchers from all over the world since the beginning of this century. IoT is consisted of large scale of sensor nodes and data processing units, and the most important features of IoT can be illustrated as energy confinement, efficient communication and high redundancy. With the sensor nodes increment, the communication efficiency and the available communication band width become bottle necks. Many research work is based on the instance which the number of joins is less. However, it is not proper to the increasing multi-join query in whole internet of things. To improve the communication efficiency between parallel units in the distributed sensor network, this paper proposed parallel query optimization algorithm based on distribution attributes cost graph. The storage information relations and the network communication cost are considered in this algorithm, and an optimized information changing rule is established. The experimental result shows that the algorithm has good performance, and it would effectively use the resource of each node in the distributed sensor network. Therefore, executive efficiency of multi-join query between different nodes could be improved.

  13. Neural networks for combined control of capacitor banks and voltage regulators in distribution systems

    SciTech Connect

    Gu, Z.; Rizy, D.T.

    1996-02-01

    A neural network for controlling shunt capacitor banks and feeder voltage regulators in electric distribution systems is presented. The objective of the neural controller is to minimize total I{sup 2}R losses and maintain all bus voltages within standard limits. The performance of the neural network for different input selections and training data is discussed and compared. Two different input selections are tried, one using the previous control states of the capacitors and regulator along with measured line flows and voltage which is equivalent to having feedback and the other with measured line flows and voltage without previous control settings. The results indicate that the neural net controller with feedback can outperform the one without. Also, proper selection of a training data set that adequately covers the operating space of the distribution system is important for achieving satisfactory performance with the neural controller. The neural controller is tested on a radially configured distribution system with 30 buses, 5 switchable capacitor banks an d one nine tap line regulator to demonstrate the performance characteristics associated with these principles. Monte Carlo simulations show that a carefully designed and relatively compact neural network with a small but carefully developed training set can perform quite well under slight and extreme variation of loading conditions.

  14. Optimizing booster chlorination in water distribution networks: a water quality index approach.

    PubMed

    Islam, Nilufar; Sadiq, Rehan; Rodriguez, Manuel J

    2013-10-01

    The optimization of chlorine dosage and the number of booster locations is an important aspect of water quality management in distribution networks. Booster chlorination helps to maintain uniformity and adequacy of free residual chlorine concentration, essential for safeguarding against microbiological contamination. Higher chlorine dosages increase free residual chlorine concentration but generate harmful by-products, in addition to taste and odor complaints. It is possible to address these microbial, chemical, and aesthetic water quality issues through free residual chlorine concentration. Estimating a water quality index (WQI) based on regulatory chlorine thresholds for microbial, chemical, and aesthetics criteria can help engineers make intelligent decisions. An innovative scheme for maintaining adequate residual chlorine with optimal chlorine dosages and numbers of booster locations was established based on a proposed WQI. The City of Kelowna (BC, Canada) water distribution network served to demonstrate the application of the proposed scheme. Temporal free residual chlorine concentration predicted with EPANET software was used to estimate the WQI, later coupled with an optimization scheme. Preliminary temporal and spatial analyses identified critical zones (relatively poor water quality) in the distribution network. The model may also prove useful for small or rural communities where free residual chlorine is considered as the only water quality criterion.

  15. A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks

    PubMed Central

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2015-01-01

    In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node’s energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network. PMID:26287189

  16. A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

    PubMed

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2015-01-01

    In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network. PMID:26287189

  17. A Distributed Data-Gathering Protocol Using AUV in Underwater Sensor Networks.

    PubMed

    Khan, Jawaad Ullah; Cho, Ho-Shin

    2015-08-06

    In this paper, we propose a distributed data-gathering scheme using an autonomous underwater vehicle (AUV) working as a mobile sink to gather data from a randomly distributed underwater sensor network where sensor nodes are clustered around several cluster headers. Unlike conventional data-gathering schemes where the AUV visits either every node or every cluster header, the proposed scheme allows the AUV to visit some selected nodes named path-nodes in a way that reduces the overall transmission power of the sensor nodes. Monte Carlo simulations are performed to investigate the performance of the proposed scheme compared with several preexisting techniques employing the AUV in terms of total amount of energy consumption, standard deviation of each node's energy consumption, latency to gather data at a sink, and controlling overhead. Simulation results show that the proposed scheme not only reduces the total energy consumption but also distributes the energy consumption more uniformly over the network, thereby increasing the lifetime of the network.

  18. A Wireless Sensor Network approach for distributed in-line chemical analysis of water.

    PubMed

    Capella, J V; Bonastre, A; Ors, R; Peris, M

    2010-03-15

    In this work we propose the implementation of a distributed system based on a Wireless Sensor Network for the control of a chemical analysis system for fresh water. This implementation is presented by describing the nodes that form the distributed system, the communication system by wireless networks, control strategies, and so on. Nitrate, ammonium, and chloride are measured in-line using appropriate ion selective electrodes (ISEs), the results obtained being compared with those provided by the corresponding reference methods. Recovery analyses with ISEs and standard methods, study of interferences, and evaluation of major sensor features have also been carried out. The communication among the nodes that form the distributed system is implemented by means of the utilization of proprietary wireless networks, and secondary data transmission services (GSM or GPRS) provided by a mobile telephone operator. The information is processed, integrated and stored in a control center. These data can be retrieved--through the Internet--so as to know the real-time system status and its evolution. PMID:20152412

  19. Using hybrid angle/distance information for distributed topology control in vehicular sensor networks.

    PubMed

    Huang, Chao-Chi; Chiu, Yang-Hung; Wen, Chih-Yu

    2014-01-01

    In a vehicular sensor network (VSN), the key design issue is how to organize vehicles effectively, such that the local network topology can be stabilized quickly. In this work, each vehicle with on-board sensors can be considered as a local controller associated with a group of communication members. In order to balance the load among the nodes and govern the local topology change, a group formation scheme using localized criteria is implemented. The proposed distributed topology control method focuses on reducing the rate of group member change and avoiding the unnecessary information exchange. Two major phases are sequentially applied to choose the group members of each vehicle using hybrid angle/distance information. The operation of Phase I is based on the concept of the cone-based method, which can select the desired vehicles quickly. Afterwards, the proposed time-slot method is further applied to stabilize the network topology. Given the network structure in Phase I, a routing scheme is presented in Phase II. The network behaviors are explored through simulation and analysis in a variety of scenarios. The results show that the proposed mechanism is a scalable and effective control framework for VSNs. PMID:25350506

  20. Calibration of an outdoor distributed camera network with a 3D point cloud.

    PubMed

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-07-29

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC).

  1. Calibration of an Outdoor Distributed Camera Network with a 3D Point Cloud

    PubMed Central

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H.; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-01-01

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221

  2. Calibration of an outdoor distributed camera network with a 3D point cloud.

    PubMed

    Ortega, Agustín; Silva, Manuel; Teniente, Ernesto H; Ferreira, Ricardo; Bernardino, Alexandre; Gaspar, José; Andrade-Cetto, Juan

    2014-01-01

    Outdoor camera networks are becoming ubiquitous in critical urban areas of the largest cities around the world. Although current applications of camera networks are mostly tailored to video surveillance, recent research projects are exploiting their use to aid robotic systems in people-assisting tasks. Such systems require precise calibration of the internal and external parameters of the distributed camera network. Despite the fact that camera calibration has been an extensively studied topic, the development of practical methods for user-assisted calibration that minimize user intervention time and maximize precision still pose significant challenges. These camera systems have non-overlapping fields of view, are subject to environmental stress, and are likely to suffer frequent recalibration. In this paper, we propose the use of a 3D map covering the area to support the calibration process and develop an automated method that allows quick and precise calibration of a large camera network. We present two cases of study of the proposed calibration method: one is the calibration of the Barcelona Robot Lab camera network, which also includes direct mappings (homographies) between image coordinates and world points in the ground plane (walking areas) to support person and robot detection and localization algorithms. The second case consist of improving the GPS positioning of geo-tagged images taken with a mobile device in the Facultat de Matemàtiques i Estadística (FME) patio at the Universitat Politècnica de Catalunya (UPC). PMID:25076221

  3. Two-layer wireless distributed sensor/control network based on RF

    NASA Astrophysics Data System (ADS)

    Feng, Li; Lin, Yuchi; Zhou, Jingjing; Dong, Guimei; Xia, Guisuo

    2006-11-01

    A project of embedded Wireless Distributed Sensor/Control Network (WDSCN) based on RF is presented after analyzing the disadvantages of traditional measure and control system. Because of high-cost and complexity, such wireless techniques as Bluetooth and WiFi can't meet the needs of WDSCN. The two-layer WDSCN is designed based on RF technique, which operates in the ISM free frequency channel with low power and high transmission speed. Also the network is low cost, portable and moveable, integrated with the technologies of computer network, sensor, microprocessor and wireless communications. The two-layer network topology is selected in the system; a simple but efficient self-organization net protocol is designed to fit the periodic data collection, event-driven and store-and-forward. Furthermore, adaptive frequency hopping technique is adopted for anti-jamming apparently. The problems about power reduction and synchronization of data in wireless system are solved efficiently. Based on the discussion above, a measure and control network is set up to control such typical instruments and sensors as temperature sensor and signal converter, collect data, and monitor environmental parameters around. This system works well in different rooms. Experiment results show that the system provides an efficient solution to WDSCN through wireless links, with high efficiency, low power, high stability, flexibility and wide working range.

  4. A hybrid deep neural network and physically based distributed model for river stage prediction

    NASA Astrophysics Data System (ADS)

    hitokoto, Masayuki; sakuraba, Masaaki

    2016-04-01

    We developed the real-time river stage prediction model, using the hybrid deep neural network and physically based distributed model. As the basic model, 4 layer feed-forward artificial neural network (ANN) was used. As a network training method, the deep learning technique was applied. To optimize the network weight, the stochastic gradient descent method based on the back propagation method was used. As a pre-training method, the denoising autoencoder was used. Input of the ANN model is hourly change of water level and hourly rainfall, output data is water level of downstream station. In general, the desirable input of the ANN has strong correlation with the output. In conceptual hydrological model such as tank model and storage-function model, river discharge is governed by the catchment storage. Therefore, the change of the catchment storage, downstream discharge subtracted from rainfall, can be the potent input candidate of the ANN model instead of rainfall. From this point of view, the hybrid deep neural network and physically based distributed model was developed. The prediction procedure of the hybrid model is as follows; first, downstream discharge was calculated by the distributed model, and then estimates the hourly change of catchment storage form rainfall and calculated discharge as the input of the ANN model, and finally the ANN model was calculated. In the training phase, hourly change of catchment storage can be calculated by the observed rainfall and discharge data. The developed model was applied to the one catchment of the OOYODO River, one of the first-grade river in Japan. The modeled catchment is 695 square km. For the training data, 5 water level gauging station and 14 rain-gauge station in the catchment was used. The training floods, superior 24 events, were selected during the period of 2005-2014. Prediction was made up to 6 hours, and 6 models were developed for each prediction time. To set the proper learning parameters and network

  5. Dynamics of bacterial communities before and after distribution in a full-scale drinking water network.

    PubMed

    El-Chakhtoura, Joline; Prest, Emmanuelle; Saikaly, Pascal; van Loosdrecht, Mark; Hammes, Frederik; Vrouwenvelder, Hans

    2015-05-01

    Understanding the biological stability of drinking water distribution systems is imperative in the framework of process control and risk management. The objective of this research was to examine the dynamics of the bacterial community during drinking water distribution at high temporal resolution. Water samples (156 in total) were collected over short time-scales (minutes/hours/days) from the outlet of a treatment plant and a location in its corresponding distribution network. The drinking water is treated by biofiltration and disinfectant residuals are absent during distribution. The community was analyzed by 16S rRNA gene pyrosequencing and flow cytometry as well as conventional, culture-based methods. Despite a random dramatic event (detected with pyrosequencing and flow cytometry but not with plate counts), the bacterial community profile at the two locations did not vary significantly over time. A diverse core microbiome was shared between the two locations (58-65% of the taxa and 86-91% of the sequences) and found to be dependent on the treatment strategy. The bacterial community structure changed during distribution, with greater richness detected in the network and phyla such as Acidobacteria and Gemmatimonadetes becoming abundant. The rare taxa displayed the highest dynamicity, causing the major change during water distribution. This change did not have hygienic implications and is contingent on the sensitivity of the applied methods. The concept of biological stability therefore needs to be revised. Biostability is generally desired in drinking water guidelines but may be difficult to achieve in large-scale complex distribution systems that are inherently dynamic.

  6. Stability Analysis of SIR Model with Distributed Delay on Complex Networks

    PubMed Central

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number R0 of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if R0≤1, then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if R0>1, then the system with distributed time delay stabilizes fastest; while R0≤1, the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  7. Evaluation of exposure scenarios on intentional microbiological contamination in a drinking water distribution network.

    PubMed

    Schijven, Jack; Forêt, Jean Marie; Chardon, Jurgen; Teunis, Peter; Bouwknegt, Martijn; Tangena, Ben

    2016-06-01

    Drinking water distribution networks are vulnerable to accidental or intentional contamination events. The objective of this study was to investigate the effects of seeding duration and concentration, exposure pathway (ingestion via drinking of water and tooth brushing and inhalation by taking a shower) and pathogen infectivity on exposure and infection risk in the case of an intentional pathogenic contamination in a drinking water distribution network. Seeding of a pathogen for 10 min and 120 min, and subsequent spreading through a drinking water distribution network were simulated. For exposure via drinking, actual data on drinking events and volumes were used. Ingestion of a small volume of water by tooth brushing twice a day by every person in the network was assumed. Inhalation of contaminated aerosol droplets took place when taking a shower. Infection risks were estimated for pathogens with low (r = 0.0001) and high (r = 0.1) infectivity. In the served population (48 000 persons) and within 24 h, about 1400 persons were exposed to the pathogen by ingestion of water in the 10-min seeding scenario and about 3400 persons in the 120-min scenario. The numbers of exposed persons via tooth brushing were about the same as via drinking of water. Showering caused (inhalation) exposure in about 450 persons in the 10-min scenario and about 1500 in the 120-min scenario. Regardless of pathogen infectivity, if the seeding concentration is 10(6) pathogens per litre or more, infection risks are close to one. Exposure by taking a shower is of relevance if the pathogen is highly infectious via inhalation. A longer duration of the seeding of a pathogen increases the probability of exposure. PMID:27038584

  8. Evaluation of exposure scenarios on intentional microbiological contamination in a drinking water distribution network.

    PubMed

    Schijven, Jack; Forêt, Jean Marie; Chardon, Jurgen; Teunis, Peter; Bouwknegt, Martijn; Tangena, Ben

    2016-06-01

    Drinking water distribution networks are vulnerable to accidental or intentional contamination events. The objective of this study was to investigate the effects of seeding duration and concentration, exposure pathway (ingestion via drinking of water and tooth brushing and inhalation by taking a shower) and pathogen infectivity on exposure and infection risk in the case of an intentional pathogenic contamination in a drinking water distribution network. Seeding of a pathogen for 10 min and 120 min, and subsequent spreading through a drinking water distribution network were simulated. For exposure via drinking, actual data on drinking events and volumes were used. Ingestion of a small volume of water by tooth brushing twice a day by every person in the network was assumed. Inhalation of contaminated aerosol droplets took place when taking a shower. Infection risks were estimated for pathogens with low (r = 0.0001) and high (r = 0.1) infectivity. In the served population (48 000 persons) and within 24 h, about 1400 persons were exposed to the pathogen by ingestion of water in the 10-min seeding scenario and about 3400 persons in the 120-min scenario. The numbers of exposed persons via tooth brushing were about the same as via drinking of water. Showering caused (inhalation) exposure in about 450 persons in the 10-min scenario and about 1500 in the 120-min scenario. Regardless of pathogen infectivity, if the seeding concentration is 10(6) pathogens per litre or more, infection risks are close to one. Exposure by taking a shower is of relevance if the pathogen is highly infectious via inhalation. A longer duration of the seeding of a pathogen increases the probability of exposure.

  9. Distributed consensus estimation for diffusion systems with missing measurements over sensor networks

    NASA Astrophysics Data System (ADS)

    Jiang, Zhengxian; Cui, Baotong; Lou, Xuyang

    2016-09-01

    In this paper, the problem of distributed consensus estimation with randomly missing measurements is investigated for a diffusion system over the sensor network. A random variable, the probability of which is known a priori, is used to model the randomly missing phenomena for each sensor. The aim of the addressed estimation problem is to design distributed consensus estimators depending on the neighbouring information such that, for all random measurement missing, the estimation error systems are guaranteed to be globally asymptotically stable in the mean square. By using Lyapunov functional method and the stochastic analysis approach, the sufficient conditions are derived for the convergence of the estimation error systems. Finally, a numerical example is given to demonstrate the effectiveness of the proposed distributed consensus estimator design scheme.

  10. Input Response of Neural Network Model with Lognormally Distributed Synaptic Weights

    NASA Astrophysics Data System (ADS)

    Nagano, Yoshihiro; Karakida, Ryo; Watanabe, Norifumi; Aoyama, Atsushi; Okada, Masato

    2016-07-01

    Neural assemblies in the cortical microcircuit can sustain irregular spiking activity without external inputs. On the other hand, neurons exhibit rich evoked activities driven by sensory stimulus, and both activities are reported to contribute to cognitive functions. We studied the external input response of the neural network model with lognormally distributed synaptic weights. We show that the model can achieve irregular spontaneous activity and population oscillation depending on the presence of external input. The firing rate distribution was maintained for the external input, and the order of firing rates in evoked activity reflected that in spontaneous activity. Moreover, there were bistable regions in the inhibitory input parameter space. The bimodal membrane potential distribution, which is a characteristic feature of the up-down state, was obtained under such conditions. From these results, we can conclude that the model displays various evoked activities due to the external input and is biologically plausible.

  11. Distributed Sleep Scheduling in Wireless Sensor Networks via Fractional Domatic Partitioning

    NASA Astrophysics Data System (ADS)

    Schumacher, André; Haanpää, Harri

    We consider setting up sleep scheduling in sensor networks. We formulate the problem as an instance of the fractional domatic partition problem and obtain a distributed approximation algorithm by applying linear programming approximation techniques. Our algorithm is an application of the Garg-Könemann (GK) scheme that requires solving an instance of the minimum weight dominating set (MWDS) problem as a subroutine. Our two main contributions are a distributed implementation of the GK scheme for the sleep-scheduling problem and a novel asynchronous distributed algorithm for approximating MWDS based on a primal-dual analysis of Chvátal's set-cover algorithm. We evaluate our algorithm with ns2 simulations.

  12. Neural network-based distributed attitude coordination control for spacecraft formation flying with input saturation.

    PubMed

    Zou, An-Min; Kumar, Krishna Dev

    2012-07-01

    This brief considers the attitude coordination control problem for spacecraft formation flying when only a subset of the group members has access to the common reference attitude. A quaternion-based distributed attitude coordination control scheme is proposed with consideration of the input saturation and with the aid of the sliding-mode observer, separation principle theorem, Chebyshev neural networks, smooth projection algorithm, and robust control technique. Using graph theory and a Lyapunov-based approach, it is shown that the distributed controller can guarantee the attitude of all spacecraft to converge to a common time-varying reference attitude when the reference attitude is available only to a portion of the group of spacecraft. Numerical simulations are presented to demonstrate the performance of the proposed distributed controller. PMID:24807141

  13. Evaluation of a Wind Turbine Generation System Connected to Distribution Network from Viewpoint of Acceptable Maximum Output

    NASA Astrophysics Data System (ADS)

    Hanai, Yuji; Hayashi, Yasuhiro; Matsuki, Junya; Kobayashi, Naoki

    Recently, the total number of Wind Turbine Generation System (WTGS) connected to distribution network has been increased drastically. Installation of WTGS can reduce the distribution loss and emission of CO2. However, the distribution network with WTGS must be operated keeping reliability of power supply and power quality. The WTGS's effects to distribution network depend on its structure. In order to accomplish both the stable operation of distribution network and the progress of WTGS's prevalence, it is necessary to evaluate the acceptable output of WTGS quantitatively. In this paper, the authors evaluate several WTGSs connected to distribution network from viewpoint of Acceptable Maximum Output (AMO). The operational constrains to calculate the AMO of a WTGS are the following, (1) voltage limit, (2) line current capacity, (3) no reverse flow to distribution transformer, (4) short circuit capacity, and (5) voltage dip by inrush current. In order to evaluate the WTGS from viewpoint of AMO, numerical simulations are accomplished for a distribution system model. Furthermore, characteristics of AMO of a WTGS connected to distribution feeder are analyzed by several numerical examples.

  14. An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

    NASA Astrophysics Data System (ADS)

    Leon, Barbara D.; Heller, Paul R.

    1987-05-01

    A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system

  15. Local multipoint distribution system (LDMS) versus free-space optical (FSO) networks

    NASA Astrophysics Data System (ADS)

    Willebrand, Heinz A.; Clark, Gerald R.; Willson, Bryan; Andreu von Euw, Christian G.; Roy, Joe; Mayhew, Laurel M.

    2001-11-01

    This paper compares two emerging broadband access methodologies, Free Space Optics (FSO) and Local Multipoint Distribution System (LMDS) and the atmospheric propagation characteristics of each when exposed to a dynamically changing channel. The comparison focuses on bandwidth, availability, and distance requirements for the new broadband market and how LMDS and FSO can be used to meet these requirements. Possible network topologies and their associated costs are examined. This comparison takes into account the total cost of deployment, including equipment costs, installation fees, access fees, and spectrum licensing fees. LMDS and FSO are compared on speed of deployment, scalability, aggregate bandwidth, and bandwidth per customer. Present and projected capabilities of each technology are considered for their suitability in different locations in the network, from the Wide Area Network (WAN), to the Metropolitan Area Network (MAN), all the way to Last Mile Access. There is a discussion on the relative performance of LMDS and FSO, focusing on the different factors that can affect link availability. Since network design is a large factor in assuring overall reliability, the flexibility of each technology with regard to network design is compared. LMDS and FSO are both line of sight, space-propagated technologies, and as such, they are both susceptible to path impediments and atmospheric attenuation, dispersion, scattering, and absorption. LMDS and FSO are affected very differently by different meteorological phenomena. Problematic atmospheric conditions are, specifically scintillation, rainfall, and fog, are examined. In addition to a discussion of these conditions, various techniques for minimizing atmospheric and environmental effects are investigated. The paper concludes with a summary of findings and recommendations for a number of broadband wireless applications.

  16. Spatially distributed effects of mental exhaustion on resting-state FMRI networks.

    PubMed

    Esposito, Fabrizio; Otto, Tobias; Zijlstra, Fred R H; Goebel, Rainer

    2014-01-01

    Brain activity during rest is spatially coherent over functional connectivity networks called resting-state networks. In resting-state functional magnetic resonance imaging, independent component analysis yields spatially distributed network representations reflecting distinct mental processes, such as intrinsic (default) or extrinsic (executive) attention, and sensory inhibition or excitation. These aspects can be related to different treatments or subjective experiences. Among these, exhaustion is a common psychological state induced by prolonged mental performance. Using repeated functional magnetic resonance imaging sessions and spatial independent component analysis, we explored the effect of several hours of sustained cognitive performances on the resting human brain. Resting-state functional magnetic resonance imaging was performed on the same healthy volunteers in two days, with and without, and before, during and after, an intensive psychological treatment (skill training and sustained practice with a flight simulator). After each scan, subjects rated their level of exhaustion and performed an N-back task to evaluate eventual decrease in cognitive performance. Spatial maps of selected resting-state network components were statistically evaluated across time points to detect possible changes induced by the sustained mental performance. The intensive treatment had a significant effect on exhaustion and effort ratings, but no effects on N-back performances. Significant changes in the most exhausted state were observed in the early visual processing and the anterior default mode networks (enhancement) and in the fronto-parietal executive networks (suppression), suggesting that mental exhaustion is associated with a more idling brain state and that internal attention processes are facilitated to the detriment of more extrinsic processes. The described application may inspire future indicators of the level of fatigue in the neural attention system.

  17. Distributed Storage Healthcare — The Basis of a Planet-Wide Public Health Care Network

    PubMed Central

    Kakouros, Nikolaos

    2013-01-01

    Background: As health providers move towards higher levels of information technology (IT) integration, they become increasingly dependent on the availability of the electronic health record (EHR). Current solutions of individually managed storage by each healthcare provider focus on efforts to ensure data security, availability and redundancy. Such models, however, scale poorly to a future of a planet-wide public health-care network (PWPHN). Our aim was to review the research literature on distributed storage systems and propose methods that may aid the implementation of a PWPHN. Methods: A systematic review was carried out of the research dealing with distributed storage systems and EHR. A literature search was conducted on five electronic databases: Pubmed/Medline, Cinalh, EMBASE, Web of Science (ISI) and Google Scholar and then expanded to include non-authoritative sources. Results: The English National Health Service Spine represents the most established country-wide PHN but is limited in deployment and remains underused. Other, literature identified and established distributed EHR attempts are more limited in scope. We discuss the currently available distributed file storage solutions and propose a schema of how one of these technologies can be used to deploy a distributed storage of EHR with benefits in terms of enhanced fault tolerance and global availability within the PWPHN. We conclude that a PWPHN distributed health care record storage system is technically feasible over current Internet infrastructure. Nonetheless, the socioeconomic viability of PWPHN implementations remains to be determined. PMID:23459171

  18. Unscheduled load flow effect due to large variation in the distributed generation in a subtransmission network

    NASA Astrophysics Data System (ADS)

    Islam, Mujahidul

    A sustainable energy delivery infrastructure implies the safe and reliable accommodation of large scale penetration of renewable sources in the power grid. In this dissertation it is assumed there will be no significant change in the power transmission and distribution structure currently in place; except in the operating strategy and regulatory policy. That is to say, with the same old structure, the path towards unveiling a high penetration of switching power converters in the power system will be challenging. Some of the dimensions of this challenge are power quality degradation, frequent false trips due to power system imbalance, and losses due to a large neutral current. The ultimate result is the reduced life of many power distribution components - transformers, switches and sophisticated loads. Numerous ancillary services are being developed and offered by the utility operators to mitigate these problems. These services will likely raise the system's operational cost, not only from the utility operators' end, but also reflected on the Independent System Operators and by the Regional Transmission Operators (RTO) due to an unforeseen backlash of frequent variation in the load-side generation or distributed generation. The North American transmission grid is an interconnected system similar to a large electrical circuit. This circuit was not planned but designed over 100 years. The natural laws of physics govern the power flow among loads and generators except where control mechanisms are installed. The control mechanism has not matured enough to withstand the high penetration of variable generators at uncontrolled distribution ends. Unlike a radial distribution system, mesh or loop networks can alleviate complex channels for real and reactive power flow. Significant variation in real power injection and absorption on the distribution side can emerge as a bias signal on the routing reactive power in some physical links or channels that are not distinguishable

  19. Shaping protein distributions in stochastic self-regulated gene expression networks

    NASA Astrophysics Data System (ADS)

    Pájaro, Manuel; Alonso, Antonio A.; Vázquez, Carlos

    2015-09-01

    In this work, we study connections between dynamic behavior and network parameters, for self-regulatory networks. To that aim, a method to compute the regions in the space of parameters that sustain bimodal or binary protein distributions has been developed. Such regions are indicative of stochastic dynamics manifested either as transitions between absence and presence of protein or between two positive protein levels. The method is based on the continuous approximation of the chemical master equation, unlike other approaches that make use of a deterministic description, which as will be shown can be misleading. We find that bimodal behavior is a ubiquitous phenomenon in cooperative gene expression networks under positive feedback. It appears for any range of transcription and translation rate constants whenever leakage remains below a critical threshold. Above such a threshold, the region in the parameters space which sustains bimodality persists, although restricted to low transcription and high translation rate constants. Remarkably, such a threshold is independent of the transcription or translation rates or the proportion of an active or inactive promoter and depends only on the level of cooperativity. The proposed method can be employed to identify bimodal or binary distributions leading to stochastic dynamics with specific switching properties, by searching inside the parameter regions that sustain such behavior.

  20. A Distributed Learning Method for ℓ1-Regularized Kernel Machine over Wireless Sensor Networks

    PubMed Central

    Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

    2016-01-01

    In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ1 norm regularization (ℓ1-regularized) is investigated, and a novel distributed learning algorithm for the ℓ1-regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. PMID:27376298

  1. An effective encoding scheme of obtaining radial topology structures in distribution networks.

    PubMed

    Wen, Juan; Tan, Yanghong; Zhang, Jianmin

    2016-01-01

    The structure of a distribution network has great effects on economy, power supply reliability and investment of a power system. To obtain an optimal topology from possible topologies, we need to solve an optimisation problem which aims to find a radial structure satisfying operating constraints. As a basis of solving this optimisation problem, the encoding scheme, is to represent the candidate configurations by a series of codes. Numerical candidate topologies and unfeasible codes would lead low efficiency or premature convergence. This paper presents an effective scheme which can rapidly produce all radial configurations of a distribution network. In order to reduce the computational requirement of solution space, initial network is simplified as a topological graph which reserves loop branches and T-nodes. And a loop-branch chain incidence matrix is derived from analyzing the relationship between any two loops. Then the principles of selecting switches of each variable are designed to determine the ranges of the variables. All radial candidate solutions are available rapidly through applying the theory of combination. The scheme presented minimizes the number of solutions and avoids tedious radial checking procedure in view of avoiding any infeasible solutions. The validity of the proposed scheme is verified by illustrative examples. PMID:27652038

  2. A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks.

    PubMed

    Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

    2016-07-01

    In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ 1 norm regularization ( ℓ 1 -regularized) is investigated, and a novel distributed learning algorithm for the ℓ 1 -regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost.

  3. A Distributed Learning Method for ℓ 1 -Regularized Kernel Machine over Wireless Sensor Networks.

    PubMed

    Ji, Xinrong; Hou, Cuiqin; Hou, Yibin; Gao, Fang; Wang, Shulong

    2016-01-01

    In wireless sensor networks, centralized learning methods have very high communication costs and energy consumption. These are caused by the need to transmit scattered training examples from various sensor nodes to the central fusion center where a classifier or a regression machine is trained. To reduce the communication cost, a distributed learning method for a kernel machine that incorporates ℓ 1 norm regularization ( ℓ 1 -regularized) is investigated, and a novel distributed learning algorithm for the ℓ 1 -regularized kernel minimum mean squared error (KMSE) machine is proposed. The proposed algorithm relies on in-network processing and a collaboration that transmits the sparse model only between single-hop neighboring nodes. This paper evaluates the proposed algorithm with respect to the prediction accuracy, the sparse rate of model, the communication cost and the number of iterations on synthetic and real datasets. The simulation results show that the proposed algorithm can obtain approximately the same prediction accuracy as that obtained by the batch learning method. Moreover, it is significantly superior in terms of the sparse rate of model and communication cost, and it can converge with fewer iterations. Finally, an experiment conducted on a wireless sensor network (WSN) test platform further shows the advantages of the proposed algorithm with respect to communication cost. PMID:27376298

  4. Metro-access integrated network based on optical OFDMA with dynamic sub-carrier allocation and power distribution.

    PubMed

    Zhang, Chongfu; Zhang, Qiongli; Chen, Chen; Jiang, Ning; Liu, Deming; Qiu, Kun; Liu, Shuang; Wu, Baojian

    2013-01-28

    We propose and demonstrate a novel optical orthogonal frequency-division multiple access (OFDMA)-based metro-access integrated network with dynamic resource allocation. It consists of a single fiber OFDMA ring and many single fiber OFDMA trees, which transparently integrates metropolitan area networks with optical access networks. The single fiber OFDMA ring connects the core network and the central nodes (CNs), the CNs are on demand reconfigurable and use multiple orthogonal sub-carriers to realize parallel data transmission and dynamic resource allocation, meanwhile, they can also implement flexible power distribution. The remote nodes (RNs) distributed in the user side are connected by the single fiber OFDMA trees with the corresponding CN. The obtained results indicate that our proposed metro-access integrated network is feasible and the power distribution is agile.

  5. A majorization-minimization approach to design of power distribution networks

    SciTech Connect

    Johnson, Jason K; Chertkov, Michael

    2010-01-01

    We consider optimization approaches to design cost-effective electrical networks for power distribution. This involves a trade-off between minimizing the power loss due to resistive heating of the lines and minimizing the construction cost (modeled by a linear cost in the number of lines plus a linear cost on the conductance of each line). We begin with a convex optimization method based on the paper 'Minimizing Effective Resistance of a Graph' [Ghosh, Boyd & Saberi]. However, this does not address the Alternating Current (AC) realm and the combinatorial aspect of adding/removing lines of the network. Hence, we consider a non-convex continuation method that imposes a concave cost of the conductance of each line thereby favoring sparser solutions. By varying a parameter of this penalty we extrapolate from the convex problem (with non-sparse solutions) to the combinatorial problem (with sparse solutions). This is used as a heuristic to find good solutions (local minima) of the non-convex problem. To perform the necessary non-convex optimization steps, we use the majorization-minimization algorithm that performs a sequence of convex optimizations obtained by iteratively linearizing the concave part of the objective. A number of examples are presented which suggest that the overall method is a good heuristic for network design. We also consider how to obtain sparse networks that are still robust against failures of lines and/or generators.

  6. Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

    PubMed

    Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

    2015-11-01

    Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data.

  7. A multi-period distribution network design model under demand uncertainty

    NASA Astrophysics Data System (ADS)

    Tabrizi, Babak H.; Razmi, Jafar

    2013-05-01

    Supply chain management is taken into account as an inseparable component in satisfying customers' requirements. This paper deals with the distribution network design (DND) problem which is a critical issue in achieving supply chain accomplishments. A capable DND can guarantee the success of the entire network performance. However, there are many factors that can cause fluctuations in input data determining market treatment, with respect to short-term planning, on the one hand. On the other hand, network performance may be threatened by the changes that take place within practicing periods, with respect to long-term planning. Thus, in order to bring both kinds of changes under control, we considered a new multi-period, multi-commodity, multi-source DND problem in circumstances where the network encounters uncertain demands. The fuzzy logic is applied here as an efficient tool for controlling the potential customers' demand risk. The defuzzifying framework leads the practitioners and decision-makers to interact with the solution procedure continuously. The fuzzy model is then validated by a sensitivity analysis test, and a typical problem is solved in order to illustrate the implementation steps. Finally, the formulation is tested by some different-sized problems to show its total performance.

  8. An Efficient Distributed Algorithm for Constructing Spanning Trees in Wireless Sensor Networks

    PubMed Central

    Lachowski, Rosana; Pellenz, Marcelo E.; Penna, Manoel C.; Jamhour, Edgard; Souza, Richard D.

    2015-01-01

    Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing. PMID:25594593

  9. Distributed multisensory integration in a recurrent network model through supervised learning

    NASA Astrophysics Data System (ADS)

    Wang, He; Wong, K. Y. Michael

    Sensory integration between different modalities has been extensively studied. It is suggested that the brain integrates signals from different modalities in a Bayesian optimal way. However, how the Bayesian rule is implemented in a neural network remains under debate. In this work we propose a biologically plausible recurrent network model, which can perform Bayesian multisensory integration after trained by supervised learning. Our model is composed of two modules, each for one modality. We assume that each module is a recurrent network, whose activity represents the posterior distribution of each stimulus. The feedforward input on each module is the likelihood of each modality. Two modules are integrated through cross-links, which are feedforward connections from the other modality, and reciprocal connections, which are recurrent connections between different modules. By stochastic gradient descent, we successfully trained the feedforward and recurrent coupling matrices simultaneously, both of which resembles the Mexican-hat. We also find that there are more than one set of coupling matrices that can approximate the Bayesian theorem well. Specifically, reciprocal connections and cross-links will compensate each other if one of them is removed. Even though trained with two inputs, the network's performance with only one input is in good accordance with what is predicted by the Bayesian theorem.

  10. An efficient distributed algorithm for constructing spanning trees in wireless sensor networks.

    PubMed

    Lachowski, Rosana; Pellenz, Marcelo E; Penna, Manoel C; Jamhour, Edgard; Souza, Richard D

    2015-01-01

    Monitoring and data collection are the two main functions in wireless sensor networks (WSNs). Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing.

  11. Distributed radar network for real-time tracking of bullet trajectory

    NASA Astrophysics Data System (ADS)

    Zhang, Yimin; Li, Xin; Jin, Yuanwei; Amin, Moeness G.; Eydgahi, Ali

    2009-05-01

    Gunshot detection, sniper localization, and bullet trajectory prediction are of significant importance in military and homeland security applications. While the majority of existing work is based on acoustic and electro-optical sensors, this paper develops a framework of networked radar systems that uses distributed radar sensor networks to achieve the aforementioned objectives. The use of radio frequency radar systems allows the achievement of subtime- of-flight tracking response, enabling to response before the bullet reaches its target and, as such, effectively leading to the reduction of injuries and casualties in military and homeland security operations. The focus of this paper is to examine the MIMO radar concept with concurrent transmission of low-correlation waveforms from multiple radar sets to ensure wide surveillance coverage and maintain a high waveform repetition frequency for long coherent time interval required to achieve return signal concentration.

  12. Parallel distributed processing and neuropsychology: a neural network model of Wisconsin Card Sorting and verbal fluency.

    PubMed

    Parks, R W; Levine, D S; Long, D L; Crockett, D J; Dalton, I E; Weingartner, H; Fedio, P; Coburn, K L; Siler, G; Matthews, J R

    1992-06-01

    Neural networks can be used as a tool in the explanation of neuropsychological data. Using the Hebbian Learning Rule and other such principles as competition and modifiable interlevel feedback, researchers have successfully modeled a widely used neuropsychological test, the Wisconsin Card Sorting Test. One of these models is reviewed here and extended to a qualitative analysis of how verbal fluency might be modeled, which demonstrates the importance of accounting for the attentional components of both tests. Difficulties remain in programming sequential cognitive processes within a parallel distributed processing (PDP) framework and integrating exceedingly complex neuropsychological tests such as Proverbs. PDP neural network methodology offers neuropsychologists co-validation procedures within narrowly defined areas of reliability and validity.

  13. Implications of Head Loss Path Choice in the Optimization of Water Distribution Networks

    NASA Astrophysics Data System (ADS)

    Goulter, Ian C.; Lussier, Bernard M.; Morgan, David R.

    1986-05-01

    The effects of varying the paths used to ensure adequate pressure throughout a water distribution network when using iterative linear programming-gradient search techniques for least cost solution of the network are analyzed. The path choice is shown to affect how the initial flows are changed, i.e., increased or decreased, by the gradient expressions in the flow modification step. The long-term implication of the difference in the way the flows are changed is a variation in the relative importance in terms of flows of the various links within the system. The amount of flow in a particular link in the final solution appears to be dependent on how often that link is included in the pressure-defining constraints.

  14. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

    PubMed

    Kim, Katherine K; Browe, Dennis K; Logan, Holly C; Holm, Roberta; Hack, Lori; Ohno-Machado, Lucila

    2014-01-01

    There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research.

  15. L-hop percolation on networks with arbitrary degree distributions and its applications

    NASA Astrophysics Data System (ADS)

    Shang, Yilun; Luo, Weiliang; Xu, Shouhuai

    2011-09-01

    Site percolation has been used to help understand analytically the robustness of complex networks in the presence of random node deletion (or failure). In this paper we move a further step beyond random node deletion by considering that a node can be deleted because it is chosen or because it is within some L-hop distance of a chosen node. Using the generating functions approach, we present analytic results on the percolation threshold as well as the mean size, and size distribution, of nongiant components of complex networks under such operations. The introduction of parameter L is both conceptually interesting because it accommodates a sort of nonindependent node deletion, which is often difficult to tackle analytically, and practically interesting because it offers useful insights for cybersecurity (such as botnet defense).

  16. L-hop percolation on networks with arbitrary degree distributions and its applications.

    PubMed

    Shang, Yilun; Luo, Weiliang; Xu, Shouhuai

    2011-09-01

    Site percolation has been used to help understand analytically the robustness of complex networks in the presence of random node deletion (or failure). In this paper we move a further step beyond random node deletion by considering that a node can be deleted because it is chosen or because it is within some L-hop distance of a chosen node. Using the generating functions approach, we present analytic results on the percolation threshold as well as the mean size, and size distribution, of nongiant components of complex networks under such operations. The introduction of parameter L is both conceptually interesting because it accommodates a sort of nonindependent node deletion, which is often difficult to tackle analytically, and practically interesting because it offers useful insights for cybersecurity (such as botnet defense). PMID:22060334

  17. A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks.

    PubMed

    Mi, Shichao; Han, Hui; Chen, Cailian; Yan, Jian; Guan, Xinping

    2016-01-01

    Heterogeneous wireless sensor networks (HWSNs) can achieve more tasks and prolong the network lifetime. However, they are vulnerable to attacks from the environment or malicious nodes. This paper is concerned with the issues of a consensus secure scheme in HWSNs consisting of two types of sensor nodes. Sensor nodes (SNs) have more computation power, while relay nodes (RNs) with low power can only transmit information for sensor nodes. To address the security issues of distributed estimation in HWSNs, we apply the heterogeneity of responsibilities between the two types of sensors and then propose a parameter adjusted-based consensus scheme (PACS) to mitigate the effect of the malicious node. Finally, the convergence property is proven to be guaranteed, and the simulation results validate the effectiveness and efficiency of PACS. PMID:26907275

  18. Nonlinear recurrent neural network predictive control for energy distribution of a fuel cell powered robot.

    PubMed

    Chen, Qihong; Long, Rong; Quan, Shuhai; Zhang, Liyan

    2014-01-01

    This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell.

  19. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders

    PubMed Central

    Kim, Katherine K; Browe, Dennis K; Logan, Holly C; Holm, Roberta; Hack, Lori; Ohno-Machado, Lucila

    2014-01-01

    There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research. PMID:24302285

  20. Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

    PubMed Central

    Chen, Qihong; Long, Rong; Quan, Shuhai

    2014-01-01

    This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

  1. A high-performance network for a distributed-control system

    NASA Astrophysics Data System (ADS)

    Cuttone, G.; Aghion, F.; Giove, D.

    1989-04-01

    Local area networks play a central rule in modern distributed-control systems for accelerators. For a superconducting cyclotron under construction at the University of Milan, an optical Ethernet network has been implemented for the interconnection of multicomputer-based stations. Controller boards, with VLSI protocol chips, have been used. The higher levels of the ISO OSI model have been implemented to suit real-time control requirements. The experimental setup for measuring the data throughput between stations will be described. The effect of memory-to-memory data transfer with respect to the packet size has been studied for packets ranging from 200 bytes to 10 Kbytes. Results, showing the data throughput to range from 0.2 to 1.1 Mbit/s, will be discussed.

  2. A Secure Scheme for Distributed Consensus Estimation against Data Falsification in Heterogeneous Wireless Sensor Networks

    PubMed Central

    Mi, Shichao; Han, Hui; Chen, Cailian; Yan, Jian; Guan, Xinping

    2016-01-01

    Heterogeneous wireless sensor networks (HWSNs) can achieve more tasks and prolong the network lifetime. However, they are vulnerable to attacks from the environment or malicious nodes. This paper is concerned with the issues of a consensus secure scheme in HWSNs consisting of two types of sensor nodes. Sensor nodes (SNs) have more computation power, while relay nodes (RNs) with low power can only transmit information for sensor nodes. To address the security issues of distributed estimation in HWSNs, we apply the heterogeneity of responsibilities between the two types of sensors and then propose a parameter adjusted-based consensus scheme (PACS) to mitigate the effect of the malicious node. Finally, the convergence property is proven to be guaranteed, and the simulation results validate the effectiveness and efficiency of PACS. PMID:26907275

  3. Data governance requirements for distributed clinical research networks: triangulating perspectives of diverse stakeholders.

    PubMed

    Kim, Katherine K; Browe, Dennis K; Logan, Holly C; Holm, Roberta; Hack, Lori; Ohno-Machado, Lucila

    2014-01-01

    There is currently limited information on best practices for the development of governance requirements for distributed research networks (DRNs), an emerging model that promotes clinical data reuse and improves timeliness of comparative effectiveness research. Much of the existing information is based on a single type of stakeholder such as researchers or administrators. This paper reports on a triangulated approach to developing DRN data governance requirements based on a combination of policy analysis with experts, interviews with institutional leaders, and patient focus groups. This approach is illustrated with an example from the Scalable National Network for Effectiveness Research, which resulted in 91 requirements. These requirements were analyzed against the Fair Information Practice Principles (FIPPs) and Health Insurance Portability and Accountability Act (HIPAA) protected versus non-protected health information. The requirements addressed all FIPPs, showing how a DRN's technical infrastructure is able to fulfill HIPAA regulations, protect privacy, and provide a trustworthy platform for research. PMID:24302285

  4. A code switching technique for distributed spread spectrum packet radio networks

    NASA Astrophysics Data System (ADS)

    Sousa, E. S.; Silvester, J. A.

    A protocol for the use of spreading codes in a spread spectrum packet radio network is presented. Throughput results for a single-hop homogeneous network in heavy traffic are given. With the protocol, each terminal is assigned two unique spreading codes: one that the terminal uses to monitor the channel when it is idle, and a different code that the terminal switches to after transmitting an initial addressing header, which is transmitted on the destination's monitoring code. Limiting throughput results are obtained. Under the assumption of exponentially distributed packet lengths a limiting throughput per terminal pair corresponding to a utilization of .3431 for a system with an infinite number of users and infinite bandwidth is obtained.

  5. A jazz-based approach for optimal setting of pressure reducing valves in water distribution networks

    NASA Astrophysics Data System (ADS)

    De Paola, Francesco; Galdiero, Enzo; Giugni, Maurizio

    2016-05-01

    This study presents a model for valve setting in water distribution networks (WDNs), with the aim of reducing the level of leakage. The approach is based on the harmony search (HS) optimization algorithm. The HS mimics a jazz improvisation process able to find the best solutions, in this case corresponding to valve settings in a WDN. The model also interfaces with the improved version of a popular hydraulic simulator, EPANET 2.0, to check the hydraulic constraints and to evaluate the performances of the solutions. Penalties are introduced in the objective function in case of violation of the hydraulic constraints. The model is applied to two case studies, and the obtained results in terms of pressure reductions are comparable with those of competitive metaheuristic algorithms (e.g. genetic algorithms). The results demonstrate the suitability of the HS algorithm for water network management and optimization.

  6. A university-based distributed satellite mission control network for operating professional space missions

    NASA Astrophysics Data System (ADS)

    Kitts, Christopher; Rasay, Mike

    2016-03-01

    For more than a decade, Santa Clara University's Robotic Systems Laboratory has operated a unique, distributed, internet-based command and control network for providing professional satellite mission control services for a variety of government and industry space missions. The system has been developed and is operated by students who become critical members of the mission teams throughout the development, test, and on-orbit phases of these missions. The mission control system also supports research in satellite control technology and hands-on student aerospace education. This system serves as a benchmark for its comprehensive nature, its student-centric nature, its ability to support NASA and industry space missions, and its longevity in providing a consistent level of professional services. This paper highlights the unique features of this program, reviews the network's design and the supported spacecraft missions, and describes the critical programmatic features of the program that support the control of professional space missions.

  7. Framework and Method for Controlling a Robotic System Using a Distributed Computer Network

    NASA Technical Reports Server (NTRS)

    Sanders, Adam M. (Inventor); Barajas, Leandro G. (Inventor); Permenter, Frank Noble (Inventor); Strawser, Philip A. (Inventor)

    2015-01-01

    A robotic system for performing an autonomous task includes a humanoid robot having a plurality of compliant robotic joints, actuators, and other integrated system devices that are controllable in response to control data from various control points, and having sensors for measuring feedback data at the control points. The system includes a multi-level distributed control framework (DCF) for controlling the integrated system components over multiple high-speed communication networks. The DCF has a plurality of first controllers each embedded in a respective one of the integrated system components, e.g., the robotic joints, a second controller coordinating the components via the first controllers, and a third controller for transmitting a signal commanding performance of the autonomous task to the second controller. The DCF virtually centralizes all of the control data and the feedback data in a single location to facilitate control of the robot across the multiple communication networks.

  8. Power-law distributed temporal heterogeneity of human activities promotes cooperation on complex networks

    NASA Astrophysics Data System (ADS)

    Liu, Chao; Li, Rong

    2016-09-01

    An evolutionary prisoner's dilemma game (PDG) with players located on Barabási-Albert scale-free networks is studied. The impact of players' heterogeneous temporal activity pattern on the evolution of cooperation is investigated. To this end, the normal procedure that players update their strategies immediately after a round of game is discarded. Instead, players update strategies according to their assigned reproduction time, which follows a power-law distribution. We find that the temporal heterogeneity of players' activities facilitates the prosperity of cooperation, indicating the important role of hubs in the maintenance of cooperation on scale-free networks. When the reproduction time is assigned to individuals negatively related to their degrees, a fluctuation of the cooperation level with the increase of the exponent β is observed.

  9. Low-Power Direct-Sequence Spread-Spectrum Modem Architecture for Distributed Wireless Sensor Networks

    SciTech Connect

    Chien, C; Elgorriaga, I; McConaghy, C

    2001-07-03

    Emerging CMOS and MEMS technologies enable the implementation of a large number of wireless distributed microsensors that can be easily and rapidly deployed to form highly redundant, self-configuring, and ad hoc sensor networks. To facilitate ease of deployment, these sensors should operate on battery for extended periods of time. A particular challenge in maintaining extended battery lifetime lies in achieving communications with low power. This paper presents a direct-sequence spread-spectrum modem architecture that provides robust communications for wireless sensor networks while dissipating very low power. The modem architecture has been verified in an FPGA implementation that dissipates only 33 mW for both transmission and reception. The implementation can be easily mapped to an ASIC technology, with an estimated power performance of less than 1 mW.

  10. Distributed robust control for synchronised tracking of networked Euler-Lagrange systems

    NASA Astrophysics Data System (ADS)

    Yang, Zi-Jiang; Shibuya, Yoshiyuki; Qin, Pan

    2015-03-01

    In this paper, we propose a distributed robust control method for synchronised tracking of networked Euler-Lagrange systems, where the time-varying reference trajectory is sent to only a subset of the agents. It is assumed that the agents can exchange information with their local neighbours on a bidirectionally connected communication graph. In the local controller equipped in each generalised coordinate of the agents, a disturbance observer is introduced to compensate for the low-passed-coupled uncertainties, and a sliding mode control term is employed to handle the uncertainties that the disturbance observer cannot compensate for sufficiently. By some damping terms, the boundedness of the signals of the overall networked nonlinear systems is first ensured. Then we show how the disturbance observer and sliding mode control term play in a cooperative way in each local generalised coordinate to achieve an excellent synchronised tracking performance. Simulation results are provided to support the theoretical results.

  11. Analysis of a distributed algorithm to determine multiple routes with path diversity in ad hoc networks.

    SciTech Connect

    Ghosal, Dipak; Mueller, Stephen Ng

    2005-04-01

    With multipath routing in mobile ad hoc networks (MANETs), a source can establish multiple routes to a destination for routing data. In MANETs, mulitpath routing can be used to provide route resilience, smaller end-to-end delay, and better load balancing. However, when the multiple paths are close together, transmissions of different paths may interfere with each other, causing degradation in performance. Besides interference, the physical diversity of paths also improves fault tolerance. We present a purely distributed multipath protocol based on the AODV-Multipath (AODVM) protocol called AODVM with Path Diversity (AODVM/PD) that finds multiple paths with a desired degree of correlation between paths specified as an input parameter to the algorithm. We demonstrate through detailed simulation analysis that multiple paths with low degree of correlation determined by AODVM/PD provides both smaller end-to-end delay than AODVM in networks with low mobility and better route resilience in the presence of correlated node failures.

  12. Mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks.

    PubMed

    Muralisankar, S; Manivannan, A; Balasubramaniam, P

    2015-09-01

    The aim of this manuscript is to investigate the mean square delay dependent-probability-distribution stability analysis of neutral type stochastic neural networks with time-delays. The time-delays are assumed to be interval time-varying and randomly occurring. Based on the new Lyapunov-Krasovskii functional and stochastic analysis approach, a novel sufficient condition is obtained in the form of linear matrix inequality such that the delayed stochastic neural networks are globally robustly asymptotically stable in the mean-square sense for all admissible uncertainties. Finally, the derived theoretical results are validated through numerical examples in which maximum allowable upper bounds are calculated for different lower bounds of time-delay.

  13. Community-Based Social Networks: Generation of Power Law Degree Distribution and IP Solutions to the KPP

    ERIC Educational Resources Information Center

    Wu, Wentao

    2012-01-01

    The objective of this thesis is two-fold: (1) to investigate the degree distribution property of community-based social networks (CSNs) and (2) to provide solutions to a pertinent problem, the Key Player Problem. In the first part of this thesis, we consider a growing community-based network in which the ability of nodes competing for links to new…

  14. Distributed Sensor Fusion for Scalar Field Mapping Using Mobile Sensor Networks.

    PubMed

    La, Hung Manh; Sheng, Weihua

    2013-04-01

    In this paper, autonomous mobile sensor networks are deployed to measure a scalar field and build its map. We develop a novel method for multiple mobile sensor nodes to build this map using noisy sensor measurements. Our method consists of two parts. First, we develop a distributed sensor fusion algorithm by integrating two different distributed consensus filters to achieve cooperative sensing among sensor nodes. This fusion algorithm has two phases. In the first phase, the weighted average consensus filter is developed, which allows each sensor node to find an estimate of the value of the scalar field at each time step. In the second phase, the average consensus filter is used to allow each sensor node to find a confidence of the estimate at each time step. The final estimate of the value of the scalar field is iteratively updated during the movement of the mobile sensors via weighted average. Second, we develop the distributed flocking-control algorithm to drive the mobile sensors to form a network and track the virtual leader moving along the field when only a small subset of the mobile sensors know the information of the leader. Experimental results are provided to demonstrate our proposed algorithms.

  15. Efficient calculation of steady state probability distribution for stochastic biochemical reaction network.

    PubMed

    Karim, Shahriar; Buzzard, Gregery T; Umulis, David M

    2012-01-01

    The Steady State (SS) probability distribution is an important quantity needed to characterize the steady state behavior of many stochastic biochemical networks. In this paper, we propose an efficient and accurate approach to calculating an approximate SS probability distribution from solution of the Chemical Master Equation (CME) under the assumption of the existence of a unique deterministic SS of the system. To find the approximate solution to the CME, a truncated state-space representation is used to reduce the state-space of the system and translate it to a finite dimension. The subsequent ill-posed eigenvalue problem of a linear system for the finite state-space can be converted to a well-posed system of linear equations and solved. The proposed strategy yields efficient and accurate estimation of noise in stochastic biochemical systems. To demonstrate the approach, we applied the method to characterize the noise behavior of a set of biochemical networks of ligand-receptor interactions for Bone Morphogenetic Protein (BMP) signaling. We found that recruitment of type II receptors during the receptor oligomerization by itself doesn't not tend to lower noise in receptor signaling, but regulation by a secreted co-factor may provide a substantial improvement in signaling relative to noise. The steady state probability approximation method shortened the time necessary to calculate the probability distributions compared to earlier approaches, such as Gillespie's Stochastic Simulation Algorithm (SSA) while maintaining high accuracy.

  16. Field-Scale Distributed Wireless Network for Monitoring Dynamic Hydrologic Processes

    NASA Astrophysics Data System (ADS)

    Campbell, C. S.; Crupper, J.; Brown, D. J.; Cobos, D. R.; Campbell, G. S.; Uberuaga, D.; Huggins, D. R.; Smith, J. L.; Gill, R. A.

    2007-12-01

    Measuring and monitoring field-scale hydrology is important to understanding the fate of water in the vadoze zone, especially in concert with pedological information. Historically, single point measurements of hydrologic and pedological information have been straightforward to obtain, while monitoring widely distributed locations over time has been more challenging, both in expense and labor. As radios have become more available, distributed wireless networks have been developed and constructed to meet this need. However, there remain relatively few commercially available, inexpensive, and simple options. The objective of this study was to test the viability of a distributed wireless network to monitor soil parameters (moisture, temperature, and electrical conductivity) across a growing season on the 36.5 hectare Cook Agronomy Farm in Eastern Washington. Using landscape analysis, 12 representative sites were selected using a stratified random procedure and sensors were installed at 30, 60, 90, 120, and 150 cm depths. Radio frequency wireless transmitters linked sensors to a central data station where data were made available anywhere in the world via a cell modem link. Data were analyzed to show relationships between soil features, crop type, and water use. Results show that a system can be assembled from commercially available components with excellent reliability across all communication links. Data from the system showed correlations between water use, directly sampled static soil features and crop type.

  17. The impact of capillary dilation on the distribution of red blood cells in artificial networks.

    PubMed

    Schmid, Franca; Reichold, Johannes; Weber, Bruno; Jenny, Patrick

    2015-04-01

    Recent studies suggest that pericytes around capillaries are contractile and able to alter the diameter of capillaries. To investigate the effects of capillary dilation on network dynamics, we performed simulations in artificial capillary networks of different sizes and complexities. The unequal partition of hematocrit at diverging bifurcations was modeled by assuming that each red blood cell (RBC) enters the branch with the faster instantaneous flow. Network simulations with and without RBCs were performed to investigate the effect of local dilations. The results showed that the increase in flow rate due to capillary dilation was less when the effects of RBCs are included. For bifurcations with sufficient RBCs in the parent vessel and nearly equal flows in the branches, the flow rate in the dilated branch did not increase. Instead, a self-regulation of flow was observed due to accumulation of RBCs in the dilated capillary. A parametric study was performed to examine the dependence on initial capillary diameter, dilation factor, and tube hematocrit. Furthermore, the conditions needed for an efficient self-regulation mechanism are discussed. The results support the hypothesis that RBCs play a significant role for the fluid dynamics in capillary networks and that it is crucial to consider the blood flow rate and the distribution of RBCs to understand the supply of oxygen in the vasculature. Furthermore, our results suggest that capillary dilation/constriction offers the potential of being an efficient mechanism to alter the distribution of RBCs locally and hence could be important for the local regulation of oxygen delivery. PMID:25617356

  18. Distributed Multi-Target Tracking and Data Association in Vision Networks.

    PubMed

    Kamal, Ahmed T; Bappy, Jawadul H; Farrell, Jay A; Roy-Chowdhury, Amit K

    2016-07-01

    Distributed algorithms have recently gained immense popularity. With regards to computer vision applications, distributed multi-target tracking in a camera network is a fundamental problem. The goal is for all cameras to have accurate state estimates for all targets. Distributed estimation algorithms work by exchanging information between sensors that are communication neighbors. Vision-based distributed multi-target state estimation has at least two characteristics that distinguishes it from other applications. First, cameras are directional sensors and often neighboring sensors may not be sensing the same targets, i.e., they are naive with respect to that target. Second, in the presence of clutter and multiple targets, each camera must solve a data association problem. This paper presents an information-weighted, consensus-based, distributed multi-target tracking algorithm referred to as the Multi-target Information Consensus (MTIC) algorithm that is designed to address both the naivety and the data association problems. It converges to the centralized minimum mean square error estimate. The proposed MTIC algorithm and its extensions to non-linear camera models, termed as the Extended MTIC (EMTIC), are robust to false measurements and limited resources like power, bandwidth and the real-time operational requirements. Simulation and experimental analysis are provided to support the theoretical results.

  19. Distributed Multi-Target Tracking and Data Association in Vision Networks.

    PubMed

    Kamal, Ahmed T; Bappy, Jawadul H; Farrell, Jay A; Roy-Chowdhury, Amit K

    2016-07-01

    Distributed algorithms have recently gained immense popularity. With regards to computer vision applications, distributed multi-target tracking in a camera network is a fundamental problem. The goal is for all cameras to have accurate state estimates for all targets. Distributed estimation algorithms work by exchanging information between sensors that are communication neighbors. Vision-based distributed multi-target state estimation has at least two characteristics that distinguishes it from other applications. First, cameras are directional sensors and often neighboring sensors may not be sensing the same targets, i.e., they are naive with respect to that target. Second, in the presence of clutter and multiple targets, each camera must solve a data association problem. This paper presents an information-weighted, consensus-based, distributed multi-target tracking algorithm referred to as the Multi-target Information Consensus (MTIC) algorithm that is designed to address both the naivety and the data association problems. It converges to the centralized minimum mean square error estimate. The proposed MTIC algorithm and its extensions to non-linear camera models, termed as the Extended MTIC (EMTIC), are robust to false measurements and limited resources like power, bandwidth and the real-time operational requirements. Simulation and experimental analysis are provided to support the theoretical results. PMID:26441444

  20. Blood flow distribution in an anatomically detailed arterial network model: criteria and algorithms.

    PubMed

    Blanco, Pablo J; Watanabe, Sansuke M; Dari, Enzo A; Passos, Marco Aurélio R F; Feijóo, Raúl A

    2014-11-01

    Development of blood flow distribution criteria is a mandatory step toward developing computational models and numerical simulations of the systemic circulation. In the present work, we (i) present a systematic approach based on anatomical and physiological considerations to distribute the blood flow in a 1D anatomically detailed model of the arterial network and (ii) develop a numerical procedure to calibrate resistive parameters in terminal models in order to effectively satisfy such flow distribution. For the first goal, we merge data collected from the specialized medical literature with anatomical concepts such as vascular territories to determine blood flow supply to specific (encephalon, kidneys, etc.) and distributed (muscles, skin, etc.) organs. Overall, 28 entities representing the main specific organs are accounted for in the detailed description of the arterial topology that we use as model substrate. In turn, 116 vascular territories are considered as the basic blocks that compose the distributed organs throughout the whole body. For the second goal, Windkessel models are used to represent the peripheral beds, and the values of the resistive parameters are computed applying a Newton method to a parameter identification problem to guarantee the supply of the correct flow fraction to each terminal location according to the given criteria. Finally, it is shown that, by means of the criteria developed, and for a rather standard set of model parameters, the model predicts physiologically realistic pressure and flow waveforms.

  1. Flow distribution analysis on the cooling tube network of ITER thermal shield

    NASA Astrophysics Data System (ADS)

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O.; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-01

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  2. Water quality modeling in the dead end sections of drinking water distribution networks.

    PubMed

    Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

    2016-02-01

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

  3. Water quality modeling in the dead end sections of drinking water distribution networks.

    PubMed

    Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim

    2016-02-01

    Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated

  4. River delta network hydraulic residence time distributions and their role in coastal nutrient biogeochemistry

    NASA Astrophysics Data System (ADS)

    Hiatt, M. R.; Castaneda, E.; Twilley, R.; Hodges, B. R.; Passalacqua, P.

    2015-12-01

    River deltas have the potential to mitigate increased nutrient loading to coastal waters by acting as biofilters that reduce the impact of nutrient enrichment on downstream ecosystems. Hydraulic residence time (HRT) is known to be a major control on biogeochemical processes and deltaic floodplains are hypothesized to have relatively long HRTs. Hydrological connectivity and delta floodplain inundation induced by riverine forces, tides, and winds likely alter surface water flow patterns and HRTs. Since deltaic floodplains are important elements of delta networks and receive significant fluxes of water, sediment, and nutrients from distributary channels, biogeochemical transformations occurring within these zones could significantly reduce nutrient loading to coastal receiving waters. However, network-scale estimates of HRT in river deltas are lacking and little is known about the effects of tides, wind, and the riverine input on the HRT distribution. Subsequently, there lacks a benchmark for evaluating the impact of engineered river diversions on coastal nutrient ecology. In this study, we estimate the HRT of a coastal river delta by using hydrodynamic modeling supported by field data and relate the HRT to spatial and temporal patterns in nitrate levels measured at discrete stations inside a delta island at Wax Lake Delta. We highlight the control of the degree of hydrological connectivity between distributary channels and interdistributary islands on the network HRT distribution and address the roles of tides and wind on altering the shape of the distribution. We compare the observed nitrate concentrations to patterns of channel-floodplain hydrological connectivity and find this connectivity to play a significant role in the nutrient removal. Our results provide insight into the potential role of deltaic wetlands in reducing the nutrient loading to near-shore waters in response to large-scale river diversions.

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

    NASA Astrophysics Data System (ADS)

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

    1998-05-01

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

  6. Effects on electrical distribution networks of dispersed power generation at high levels of connection penetration

    SciTech Connect

    Longrigg, P

    1983-07-01

    The advent and deployment of significant levels of photovoltaic and wind energy generation in the spatially dispersed mode (i.e., residential and intermediate load centers) may have deleterious effects upon existing protective relay equipment and its time-current coordination on radial distribution circuits to which power conditioning equipment may be connected for power sell-back purposes. The problems that may arise involve harmonic injection from power conditioning inverters that can affect protective relays and cause excessive voltage and current from induced series and parallel resonances on feeders and connected passive equipment. Voltage regulation, var requirements, and consumer metering can also be affected by this type of dispersed generation. The creation of islands of supply is also possible, particularly on rural supply systems. This paper deals mainly with the effects of harmonics and short-circuit currents from wind energy conversion systems (WECS) and photovoltaic (PV) systems upon the operating characteristics of distribution networks and relays and other protective equipment designed to ensure the safety and supply integrity of electrical utility networks. Traditionally, electrical supply networks have been designed for one-way power flow-from generation to load, with a balance maintained between the two by means of automatic generation and load-frequency controls. Dispersed generation, from renewables like WECS or PV or from nonrenewable resources, can change traditional power flow. These changes must be dealt with effectively if renewable energy resources are to be integrated into the utility distribution system. This paper gives insight into these problems and proposes some solutions.

  7. The formation and distribution of hippocampal synapses on patterned neuronal networks

    NASA Astrophysics Data System (ADS)

    Dowell-Mesfin, Natalie M.

    Communication within the central nervous system is highly orchestrated with neurons forming trillions of specialized junctions called synapses. In vivo, biochemical and topographical cues can regulate neuronal growth. Biochemical cues also influence synaptogenesis and synaptic plasticity. The effects of topography on the development of synapses have been less studied. In vitro, neuronal growth is unorganized and complex making it difficult to study the development of networks. Patterned topographical cues guide and control the growth of neuronal processes (axons and dendrites) into organized networks. The aim of this dissertation was to determine if patterned topographical cues can influence synapse formation and distribution. Standard fabrication and compression molding procedures were used to produce silicon masters and polystyrene replicas with topographical cues presented as 1 mum high pillars with diameters of 0.5 and 2.0 mum and gaps of 1.0 to 5.0 mum. Embryonic rat hippocampal neurons grown unto patterned surfaces. A developmental analysis with immunocytochemistry was used to assess the distribution of pre- and post-synaptic proteins. Activity-dependent pre-synaptic vesicle uptake using functional imaging dyes was also performed. Adaptive filtering computer algorithms identified synapses by segmenting juxtaposed pairs of pre- and post-synaptic labels. Synapse number and area were automatically extracted from each deconvolved data set. In addition, neuronal processes were traced automatically to assess changes in synapse distribution. The results of these experiments demonstrated that patterned topographic cues can induce organized and functional neuronal networks that can serve as models for the study of synapse formation and plasticity as well as for the development of neuroprosthetic devices.

  8. Flow distribution analysis on the cooling tube network of ITER thermal shield

    SciTech Connect

    Nam, Kwanwoo; Chung, Wooho; Noh, Chang Hyun; Kang, Dong Kwon; Kang, Kyoung-O; Ahn, Hee Jae; Lee, Hyeon Gon

    2014-01-29

    Thermal shield (TS) is to be installed between the vacuum vessel or the cryostat and the magnets in ITER tokamak to reduce the thermal radiation load to the magnets operating at 4.2K. The TS is cooled by pressurized helium gas at the inlet temperature of 80K. The cooling tube is welded on the TS panel surface and the composed flow network of the TS cooling tubes is complex. The flow rate in each panel should be matched to the thermal design value for effective radiation shielding. This paper presents one dimensional analysis on the flow distribution of cooling tube network for the ITER TS. The hydraulic cooling tube network is modeled by an electrical analogy. Only the cooling tube on the TS surface and its connecting pipe from the manifold are considered in the analysis model. Considering the frictional factor and the local loss in the cooling tube, the hydraulic resistance is expressed as a linear function with respect to mass flow rate. Sub-circuits in the TS are analyzed separately because each circuit is controlled by its own control valve independently. It is found that flow rates in some panels are insufficient compared with the design values. In order to improve the flow distribution, two kinds of design modifications are proposed. The first one is to connect the tubes of the adjacent panels. This will increase the resistance of the tube on the panel where the flow rate is excessive. The other design suggestion is that an orifice is installed at the exit of tube routing where the flow rate is to be reduced. The analysis for the design suggestions shows that the flow mal-distribution is improved significantly.

  9. On-Board Fiber-Optic Network Architectures for Radar and Avionics Signal Distribution

    NASA Technical Reports Server (NTRS)

    Alam, Mohammad F.; Atiquzzaman, Mohammed; Duncan, Bradley B.; Nguyen, Hung; Kunath, Richard

    2000-01-01

    Continued progress in both civil and military avionics applications is overstressing the capabilities of existing radio-frequency (RF) communication networks based on coaxial cables on board modem aircrafts. Future avionics systems will require high-bandwidth on- board communication links that are lightweight, immune to electromagnetic interference, and highly reliable. Fiber optic communication technology can meet all these challenges in a cost-effective manner. Recently, digital fiber-optic communication systems, where a fiber-optic network acts like a local area network (LAN) for digital data communications, have become a topic of extensive research and development. Although a fiber-optic system can be designed to transport radio-frequency (RF) signals, the digital fiber-optic systems under development today are not capable of transporting microwave and millimeter-wave RF signals used in radar and avionics systems on board an aircraft. Recent advances in fiber optic technology, especially wavelength division multiplexing (WDM), has opened a number of possibilities for designing on-board fiber optic networks, including all-optical networks for radar and avionics RF signal distribution. In this paper, we investigate a number of different novel approaches for fiber-optic transmission of on-board VHF and UHF RF signals using commercial off-the-shelf (COTS) components. The relative merits and demerits of each architecture are discussed, and the suitability of each architecture for particular applications is pointed out. All-optical approaches show better performance than other traditional approaches in terms of signal-to-noise ratio, power consumption, and weight requirements.

  10. Recent advances on optical reflectometry for access network diagnostics and distributed sensing

    NASA Astrophysics Data System (ADS)

    He, Zuyuan; Fan, Xinyu; Liu, Qingwen; Du, Jiangbing

    2015-07-01

    In this invited talk, we will present the advances in research and development activities of optical reflectometry in our laboratory. The performance of phase-sensitive coherent OTDR, which is developed for distributed vibration measurement, is reported with the results of field tests. The performance of time-gated digital OFDR, which is developed for optical access network diagnostics, is also reported. We will also discuss how to increase the frequency sweep span of the linearly-swept optical source, a very important part for improving the performance of optical reflectometry.

  11. Economic consideration of optimal vaccination distribution for epidemic Spreads in complex networks

    NASA Astrophysics Data System (ADS)

    Wang, Bing; Suzuki, Hideyuki; Aihara, Kazuyuki

    2013-02-01

    The main concern of epidemiological modeling is to implement an economical vaccine allocation to the population. Here, we investigate the optimal vaccination allocation in complex networks. We find that the optimal vaccine coverage depends not only on the relative cost of treatment to vaccination but also on the vaccine efficacy. Especially with a high cost of treatment, nodes with high degree are prioritized to vaccinate. These results may help us understand factors that may impact the optimal vaccination distribution in the control of epidemic dynamics.

  12. Distributed OTDR-interferometric sensing network with identical ultra-weak fiber Bragg gratings.

    PubMed

    Wang, Chen; Shang, Ying; Liu, Xiao-Hui; Wang, Chang; Yu, Hai-Hu; Jiang, De-Sheng; Peng, Gang-Ding

    2015-11-01

    We demonstrate a distributed sensing network with 500 identical ultra-weak fiber Bragg gratings (uwFBGs) in an equal separation of 2m using balanced Michelson interferometer of the phase sensitive optical time domain reflectometry (φ-OTDR) for acoustic measurement. Phase, amplitude, frequency response and location information can be directly obtained at the same time by using the passive 3 × 3 coupler demodulation. Lab experiments on detecting sound waves in water tank are carried out. The results show that this system can well demodulate distributed acoustic signal with the pressure detection limit of 0.122Pa and achieve an acoustic phase sensitivity of around -158dB (re rad/μPa) with a relatively flat frequency response between 450Hz to 600Hz. PMID:26561173

  13. Distributed network of integrated 3D sensors for transportation security applications

    NASA Astrophysics Data System (ADS)

    Hejmadi, Vic; Garcia, Fred

    2009-05-01

    The US Port Security Agency has strongly emphasized the needs for tighter control at transportation hubs. Distributed arrays of miniature CMOS cameras are providing some solutions today. However, due to the high bandwidth required and the low valued content of such cameras (simple video feed), large computing power and analysis algorithms as well as control software are needed, which makes such an architecture cumbersome, heavy, slow and expensive. We present a novel technique by integrating cheap and mass replicable stealth 3D sensing micro-devices in a distributed network. These micro-sensors are based on conventional structures illumination via successive fringe patterns on the object to be sensed. The communication bandwidth between each sensor remains very small, but is of very high valued content. Key technologies to integrate such a sensor are digital optics and structured laser illumination.

  14. Privacy and Security Research Group workshop on network and distributed system security: Proceedings

    SciTech Connect

    Not Available

    1993-05-01

    This report contains papers on the following topics: NREN Security Issues: Policies and Technologies; Layer Wars: Protect the Internet with Network Layer Security; Electronic Commission Management; Workflow 2000 - Electronic Document Authorization in Practice; Security Issues of a UNIX PEM Implementation; Implementing Privacy Enhanced Mail on VMS; Distributed Public Key Certificate Management; Protecting the Integrity of Privacy-enhanced Electronic Mail; Practical Authorization in Large Heterogeneous Distributed Systems; Security Issues in the Truffles File System; Issues surrounding the use of Cryptographic Algorithms and Smart Card Applications; Smart Card Augmentation of Kerberos; and An Overview of the Advanced Smart Card Access Control System. Selected papers were processed separately for inclusion in the Energy Science and Technology Database.

  15. Distributed Synchronization Technique for OFDMA-Based Wireless Mesh Networks Using a Bio-Inspired Algorithm

    PubMed Central

    Kim, Mi Jeong; Maeng, Sung Joon; Cho, Yong Soo

    2015-01-01

    In this paper, a distributed synchronization technique based on a bio-inspired algorithm is proposed for an orthogonal frequency division multiple access (OFDMA)-based wireless mesh network (WMN) with a time difference of arrival. The proposed time- and frequency-synchronization technique uses only the signals received from the neighbor nodes, by considering the effect of the propagation delay between the nodes. It achieves a fast synchronization with a relatively low computational complexity because it is operated in a distributed manner, not requiring any feedback channel for the compensation of the propagation delays. In addition, a self-organization scheme that can be effectively used to construct 1-hop neighbor nodes is proposed for an OFDMA-based WMN with a large number of nodes. The performance of the proposed technique is evaluated with regard to the convergence property and synchronization success probability using a computer simulation. PMID:26225974

  16. Distributed OTDR-interferometric sensing network with identical ultra-weak fiber Bragg gratings.

    PubMed

    Wang, Chen; Shang, Ying; Liu, Xiao-Hui; Wang, Chang; Yu, Hai-Hu; Jiang, De-Sheng; Peng, Gang-Ding

    2015-11-01

    We demonstrate a distributed sensing network with 500 identical ultra-weak fiber Bragg gratings (uwFBGs) in an equal separation of 2m using balanced Michelson interferometer of the phase sensitive optical time domain reflectometry (φ-OTDR) for acoustic measurement. Phase, amplitude, frequency response and location information can be directly obtained at the same time by using the passive 3 × 3 coupler demodulation. Lab experiments on detecting sound waves in water tank are carried out. The results show that this system can well demodulate distributed acoustic signal with the pressure detection limit of 0.122Pa and achieve an acoustic phase sensitivity of around -158dB (re rad/μPa) with a relatively flat frequency response between 450Hz to 600Hz.

  17. Orientational tomography of optical axes directions distributions of multilayer biological tissues birefringent polycrystalline networks

    NASA Astrophysics Data System (ADS)

    Zabolotna, Natalia I.; Dovhaliuk, Rostyslav Y.

    2013-09-01

    We present a novel measurement method of optic axes orientation distribution which uses a relatively simple measurement setup. The principal difference of our method from other well-known methods lies in direct approach for measuring the orientation of optical axis of polycrystalline networks biological crystals. Our test polarimetry setup consists of HeNe laser, quarter wave plate, two linear polarizers and a CCD camera. We also propose a methodology for processing of measured optic axes orientation distribution which consists of evaluation of statistical, correlational and spectral moments. Such processing of obtained data can be used to classify particular tissue sample as "healthy" or "pathological". For our experiment we use thin layers of histological section of normal and muscular dystrophy tissue sections. It is shown that the difference between mentioned moments` values of normal and pathological samples can be quite noticeable with relative difference up to 6.26.

  18. Application of new type of distributed multimedia databases to networked electronic museum

    NASA Astrophysics Data System (ADS)

    Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

    1999-01-01

    Recently, various kinds of multimedia application systems have actively been developed based on the achievement of advanced high sped communication networks, computer processing technologies, and digital contents-handling technologies. Under this background, this paper proposed a new distributed multimedia database system which can effectively perform a new function of cooperative retrieval among distributed databases. The proposed system introduces a new concept of 'Retrieval manager' which functions as an intelligent controller so that the user can recognize a set of distributed databases as one logical database. The logical database dynamically generates and performs a preferred combination of retrieving parameters on the basis of both directory data and the system environment. Moreover, a concept of 'domain' is defined in the system as a managing unit of retrieval. The retrieval can effectively be performed by cooperation of processing among multiple domains. Communication language and protocols are also defined in the system. These are used in every action for communications in the system. A language interpreter in each machine translates a communication language into an internal language used in each machine. Using the language interpreter, internal processing, such internal modules as DBMS and user interface modules can freely be selected. A concept of 'content-set' is also introduced. A content-set is defined as a package of contents. Contents in the content-set are related to each other. The system handles a content-set as one object. The user terminal can effectively control the displaying of retrieved contents, referring to data indicating the relation of the contents in the content- set. In order to verify the function of the proposed system, a networked electronic museum was experimentally built. The results of this experiment indicate that the proposed system can effectively retrieve the objective contents under the control to a number of distributed

  19. Stability analysis of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time varying delays

    NASA Astrophysics Data System (ADS)

    M. Syed, Ali

    2014-06-01

    In this paper, the global asymptotic stability problem of Markovian jumping stochastic Cohen—Grossberg neural networks with discrete and distributed time-varying delays (MJSCGNNs) is considered. A novel LMI-based stability criterion is obtained by constructing a new Lyapunov functional to guarantee the asymptotic stability of MJSCGNNs. Our results can be easily verified and they are also less restrictive than previously known criteria and can be applied to Cohen—Grossberg neural networks, recurrent neural networks, and cellular neural networks. Finally, the proposed stability conditions are demonstrated with numerical examples.

  20. An autonomous recovery mechanism against optical distribution network failures in EPON

    NASA Astrophysics Data System (ADS)

    Liem, Andrew Tanny; Hwang, I.-Shyan; Nikoukar, AliAkbar

    2014-10-01

    Ethernet Passive Optical Network (EPON) is chosen for servicing diverse applications with higher bandwidth and Quality-of-Service (QoS), starting from Fiber-To-The-Home (FTTH), FTTB (business/building) and FTTO (office). Typically, a single OLT can provide services to both residential and business customers on the same Optical Line Terminal (OLT) port; thus, any failures in the system will cause a great loss for both network operators and customers. Network operators are looking for low-cost and high service availability mechanisms that focus on the failures that occur within the drop fiber section because the majority of faults are in this particular section. Therefore, in this paper, we propose an autonomous recovery mechanism that provides protection and recovery against Drop Distribution Fiber (DDF) link faults or transceiver failure at the ONU(s) in EPON systems. In the proposed mechanism, the ONU can automatically detect any signal anomalies in the physical layer or transceiver failure, switching the working line to the protection line and sending the critical event alarm to OLT via its neighbor. Each ONU has a protection line, which is connected to the nearest neighbor ONU, and therefore, when failure occurs, the ONU can still transmit and receive data via the neighbor ONU. Lastly, the Fault Dynamic Bandwidth Allocation for recovery mechanism is presented. Simulation results show that our proposed autonomous recovery mechanism is able to maintain the overall QoS performance in terms of mean packet delay, system throughput, packet loss and EF jitter.